Hong Kong Exchanges and Clearing Limited and The Stock Exchange of Hong Kong Limited take no responsibility for the contents of this announcement, make no representation as to its accuracy or completeness and expressly disclaim any liability whatsoever for any loss howsoever arising from or in reliance upon the whole or any part of the contents of this announcement.

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**QINGDAO AINNOVATION TECHNOLOGY GROUP CO., LTD[*] 青島創新奇智科技集團股份有限公司**

(A joint stock company incorporated in the People’s Republic of China with limited liability)

(Stock Code: 2121)

ANNUAL RESULTS ANNOUNCEMENT FOR THE YEAR ENDED 31 DECEMBER 2022

The board of directors (the “ Board ”) of Qingdao AInnovation Technology Group Co., Ltd (the “ Company ”, and its subsidiaries, the “ Group ”) is pleased to announce the annual results of the Group in the fiscal year ended 31 December 2022 (the “ Reporting Period ”), together with the comparative figures for the last fiscal year (the fiscal year ended 31 December 2021).

– 1 –

FINANCIAL SUMMARY

Period from

	Period from
	6 February to
	31 December		Year ended 31	December
	2018	2019	2020	2021	2022
	RMB’000	RMB’000	RMB’000	RMB’000	RMB’000
Revenue	37,208	229,141	462,324	861,168	1,557,643
Gross profit	23,385	71,613	134,621	267,241	507,078
Operating loss	(69,537)	(221,956)	(286,801)	(622,841)	(392,291)
Loss for the period/year	(71,174)	(248,359)	(360,635)	(635,124)	(361,160)
Add:
Share-based payment expenses	23,339	53,230	133,750	406,967	173,294
Finance costs of financial
liabilities of redeemable shares	2,457	35,158	82,406	34,877	—
Listing expenses	—	—	—	51,500	26,457
Amortization of intangible assets
arising from acquisition	—	—	—	—	14,292
Changes in fair value of financial
assets/liabilities at fair value
through profit or loss	—	—	—	—	8,716
Adjusted net loss (Unaudited)	(45,378)	(159,971)	(144,479)	(141,780)	(138,401)

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		As at 31 December	As at 31 December
	2018	2019	2020	2021	2022
	RMB’000	RMB’000	RMB’000	RMB’000	RMB’000
Total assets	158,204	854,514	1,395,806	2,264,907	3,268,447
Cash and cash equivalent	74,396	605,631	1,042,502	1,553,150	1,642,665
Total liabilities	135,185	1,017,680	1,909,833	469,599	909,472

KA base revenue value

Number of premium customers Premium customer revenue (RMB in thousands) Premium customer dollar based repeating rate Total number of customers Total revenue (RMB in thousands)	Period from 6 February to 31 December 2018 — — n.a. 50 37,208	Year ended 31 December
		2019 2020 2021 2022 13 23 42 71 114,163 381,255 798,661 1,350,995 n.a. 112.7% 102.5% 82.1% 150 157 159 292 229,141 462,324 861,168 1,557,643

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Revenue-By Type of Products/Services

Period from

6 February

	6 February	6 February
	to 31 December					Year ended	31 December
	2018		2019		2020		2021		2022
	Amount	%	Amount	%	Amount	%	Amount	%	Amount	%
	RMB’000		RMB’000		RMB’000		RMB’000		RMB’000
Sales of products
and solutions	36,545	98.2	224,408	97.9	451,726	97.7	846,411	98.3	1,522,229	97.7
Services of
data solutions	663	1.8	4,733	2.1	10,598	2.3	14,757	1.7	35,414	2.3
Total	37,208	100.0	229,141	100.0	462,324	100.0	861,168	100.0	1,557,643	100.0

Revenue-By Customer Type

Period from

6 February

	6 February	6 February
	to 31 December					Year ended	31 December
	2018		2019		2020		2021		2022
	Amount	%	Amount	%	Amount	%	Amount	%	Amount	%
	RMB’000		RMB’000		RMB’000		RMB’000		RMB’000
System integrators	5,705	15.3	136,407	59.5	351,428	76.0	643,831	74.8	931,729	59.8
End–users	31,503	84.7	92,734	40.5	110,896	24.0	217,337	25.2	625,914	40.2
Total	37,208	100.0	229,141	100.0	462,324	100.0	861,168	100.0	1,557,643	100.0

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Revenue-By Industry Verticals

Period from

	Year ended 31 December
		2022
			% 60.9 18.3 6.8 8.6 8.3 6.4 5.4 7.1 24.5 13.4 2.0 9.1 14.6

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BUSINESS OVERVIEW

Part I: Business Review

Since its establishment in 2018, AInnovation has continued to promote the implementation of cutting-edge artificial intelligence technology in the real industry represented by the manufacturing sector to help industrial transformation and high-quality development. In the past year, we successfully completed the listing on the Hong Kong Stock Exchange and achieved solid business development despite the challenging environment. In 2022, our revenue reached RMB1,558 million, up 80.9% year-on-year; and gross profit amounted to RMB507 million, up 89.7% year-on-year. Our gross profit margin was 32.6%, improved 1.6 percentage points as compared to 2021. Adjusted net loss was RMB138 million, down by 2.4% year-on-year and adjusted net loss margin was 8.9%, narrowing by 46.1% year-on-year.

The report of 20th People’s Congress stated, “to build a modern industrial system, adhere to the focus of economic development on the real economy, promote a new type of industrialization, and accelerate the construction of a strong manufacturing country, a strong quality country, a strong aerospace country, a strong transportation country, a strong network country, and a digital China.” The upgrading and development of the manufacturing industry is the most important part of the upgrading and development of the real economy. Digitalization and intelligent technology can help to continuously stimulate application scenarios and business model innovation, and promote the high-quality development of the manufacturing industry. As the market leader of “AI + Manufacturing” solutions in China, AInnovation is actively developing intelligent manufacturing and industrial digital transformation and implements the strategy of “specialized and new”. We focus on key sub-sectors, and follow the business expansion path of “point-line-surface” to achieve 1*N replication and 1+N expansion for long term sustainable growth. In 2022, the revenue of “AI + Manufacturing” amounted to RMB948 million, up 111.2% year-on-year, accounting for 60.9% of the revenue.

During the year, we continued to expand our “AI + Manufacturing” layout by focusing on six sub-sectors: iron and steel metallurgy, panel semiconductor, 3C high-tech, engineering and construction, automotive equipment, energy and power. We have started to develop our business in the Food & Beverage and New Material and intelligent manufacturing practical training sectors since the second half of 2022. On the one hand, we consolidated endogenous business and promoted organic growth, on the other hand, we invested in and acquired enterprises that have outstanding performance in the sub-sectors of manufacturing industry, and they were included in the Group’s controlling interests to achieve complementary business and extensive expansion.

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In May 2022, we acquired 51% equity interests in each of Qingdao Aolipu Automation Control System Co., Ltd., a well-known industrial Internet solution provider in the field of Food & Beverage and New Material (now renamed as Qingdao Aolipu Qizhi Intelligent Industrial Technology Co., Ltd.), and Shanghai Higher Mechanical & Electrical Co., Ltd., an integrated solution provider of industrial automation systems which has been deeply involved in the field of automotive equipment for many years. In November 2022, AInnovation and Anhui Anlian Cloud Service Co., Ltd. (安徽安聯雲服務有限公司), a member enterprise of Anhui Anlian Holding Group (安徽安聯控股集團), established a joint venture named Anlian Qizhi (Anhui) Technology Co., Ltd. (安聯奇智 (安徽) 科技有限公司), an innovative technology enterprise with artificial intelligence industry solutions as the core, to promote the deep integration of AI and cloud computing and seize the climax of industrial Internet value. By the end of 2022, we have formed a comprehensive layout in Qingdao, Shandong Province, as our headquarters, and with subsidiaries located in 12 cities across China, including Chongqing CISAI Technology Co., Ltd., Qingdao Aolipu Qizhi Intelligent Industrial Technology Co. Ltd., RewinCloud (Chongqing) Technology Co., Ltd., Shanghai Higher Mechanical & Electrical Co. Ltd., and Anlian Qizhi (Anhui) Technology Co., Ltd.

AInnovation always focuses on the digital transformation of the sub-sectors market of manufacturing industry and empowers the high-quality development of the industry with AI. In 2022, we continued to focus on the manufacturing industry and became a small giant enterprise with strong innovation capability, high market share, key core technologies and excellent quality and efficiency. AInnovation was recognized by the Ministry of Industry and Information Technology as a “National Specialized and New Small Giant Enterprise”, and five of its subsidiaries were recognized as Specialized and New Enterprise at the provincial/municipal level. Thanks to our empowerment and contribution to real industries such as manufacturing, we were ranked as one of the Top 100 New Real Enterprises in China in 2022. In addition, our market share continues to expand. According to IDC’s “China Artificial Intelligence Software and Application Market Research Report for the First Half of 2022”, AInnovation was promoted to No. 4 in the market share of computer vision applications and continued to rank No. 4 in the market share of machine learning platforms, being the only company ranked among the top four in both AI technology branches. In the manufacturing sector, according to IDC’s reports of “IDC MarketScape: China Industrial Data Intelligence Vendor Assessment 2022” and “Market Share of AI-Enabled Industrial Quality Inspection Solutions in China”, AInnovation has been ranked in China’s Industrial Data Intelligence market leader quadrant and the 2nd largest AI industrial quality inspection vendor in China for three consecutive years. In Gartner’s report of “China AI Software Market Guide”, AInnovation was included in the report as a recommended Chinese AI software vendor, and MMOC AI technology platform was included as a representative product.

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As an AI company that stands on technological innovation, AInnovation has made breakthroughs in patent filing, AI platform construction, AIGC technology exploration, AI products and solutions, etc. in 2022.

Record high patent filing and excellent domestic level of intellectual property management

AInnovation always insists that technological innovation is the first productive force and continuously promotes the implementation of intellectual property strategy and high-value output. We strive to improve the technological innovation system and enhance the competitive advantage in the market, and have made a number of innovative achievements with independent intellectual property rights. As of 31 December 2022, a total of 1,064 AI-related patents have been applied for, of which 80% are invention patents amounting to 850, and 361 have been successfully registered. 430 new patents were applied for in 2022.

Thanks to our excellent performance in patents, we were awarded the “National IPR Advantage Enterprise” by the State Intellectual Property Office in 2022. The “National IPR Advantage Enterprise” is a key project of the State Intellectual Property Office to cultivate Chinese leading intellectual property enterprises with independent intellectual property rights and famous brands and international competitive advantages in the key industrial fields of national development. The selection not only marks AInnovation’s advancement to a new level in IP construction and management, but also means that it has reached the domestic excellent level in many aspects, such as the transformation of IP achievements, application of achievements and cultivation of talents.

Continuous development of MMOC artificial intelligence technology platform

MMOC AI technology platform is an end-to-end platform that supports AI solution innovation, development and delivery, which is made up of four platforms: ManuVision Intelligent Machine Vision Platform, MatrixVision Intelligent Edge Video Platform, Orion Distributed Machine Learning Platform and Cloud platform. In 2022, along with the MMOC Platform “3 Phase” Strategy, the Company continued to invest in R&D resources, upgrade the technology, improve the maturity of MMOC platform, and devote itself to making MMOC platform an open platform that can be easily “integrated”.

In 2022, MatrixVision further improved the edge video full-link tool set to enhance the efficiency of being integrated by internal/external customers, while enriching the core algorithms for manufacturing and continuing to lower the threshold of video intelligence analysis; ManuVision newly developed the Designer core module to continue to lower the threshold of use and continue to improve the efficiency and user friendliness of machine vision engineering design; Orion specifically launched AML-Vision vision training platform for manufacturing

– 8 –

vision application scenarios, focusing on improving vision model training capabilities and forming a functional closed loop from vision model training to vision model deployment with MatrixVision and ManuVision, which is more conducive to vision-related solution development and delivery; and Cloud improved the basic technical components, consolidated the level of distributed infrastructure, and as a basic base, continued to promote the construction of AInnovation on the cloud and open to the public.

MMOC Platform "3 Phase" Strategy

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----- Start of picture text -----

Phase 1 Phase 2 Phase 3
Internally integrated Externally integrated Open Ecology
Become the basic support platform for
the development and delivery of External integration companies pay to Partially open source and form an ecology
industrial vision scenarios within a use ManuVision for the delivery and based on ManuVision (customers and
integration of industrial vision scenarios. suppliers grow in the ecology).
company.
Partially open source and form an
Become the basic support platform for the development and delivery of edge vision scenarios within a company. External integration companies pay to use MatrixVision for the delivery and integration of edge vision scenarios. ecology based on MatrixVision (customers and suppliers grow in the
ecology).
Part of the OC module technology is open
Enrich Orion platform and Cloud Orion becomes the machine learning source and has formed an industry
infrastructure functions to become the platform used by external integration ecosystem with a certain influence in the
base for internal AI development and companies and Cloud becomes the base open source community, creating an
application implementation. for internal/external industry solutions. integration of AI developers, customers,
and suppliers.
----- End of picture text -----

Figure 1: MMOC Platform “3 Phase” Strategy

Strengthen perception algorithm R&D and reserve AIGC capability

In 2022, AInnovation continued to build core algorithms for manufacturing industry application needs, establish intelligent algorithm engines, significantly reduce model production costs, and provide key algorithm capabilities for model applications in the field of intelligent manufacturing.

The Company continues to delve into the research of small sample learning algorithms. To address the problem of insufficient training data in the manufacturing industry, we propose a semi-supervised image classification algorithm based on inverse label learning, and design an inverse label learning module. High-quality learning with label-free images can be achieved by labeling the label-free image data with a counter label and conducting learning. This helps to reduce the reliance on labeled data for AI algorithm applications in the industrial field, shorten the algorithm development cycle, and save the algorithm development cost. Pre-training large models

– 9 –

can be pre-trained based on massive data, reducing the difficulty of training application scenarios and improving the performance of models. For industries such as automotive parts manufacturing and consumer electronic equipment, product batches are changed frequently, and there are often problems with larger domain differences between the test data and the training data of the model. To address this problem, the company proposes a prototype-based classifier learning approach that bridges the domain gap between training data and test data by obtaining prototype representations of each item set category from single-item examples. The algorithm can be applied in scenarios where there is a demand for batch product inspection, speeding up the adaptation of the inspection algorithm and improving the accuracy of the inspection. Compared with general vision tasks, industrial vision tasks are more concerned with local texture changes and finer recognition granularity. To address this feature, the Company proposes a dual-attention mechanism-based few-sample learning algorithm, which improves the accuracy of fine-grained recognition by designing a fine-grained recognition framework with dual-attention streams to obtain both local key information and global aggregated information of images. The algorithm can be used to distinguish images belonging to different subclasses in the case of very few labeled samples in fields such as manufacturing. The Company’s research innovation for small sample learning algorithm not only brings tangible business value to customers, but also has authored several academic papers published in the world’s top artificial intelligence conferences and journals.

At the end of 2022, OpenAI launched ChatGPT to prove the great potential of content generation (AIGC) technology. Based on small-sample learning, AInnovation further aggregated previous R&D achievements in the content generation field, reserved AIGC technology capabilities, and developed industry-oriented AIGC solution - AInnoGC. AInnoGC uses modular design to serve multiple scenarios in the manufacturing field to achieve cost reduction and efficiency. In response to the problem of insufficient training samples in industrial vision, we propose a dual-stage guided defect sample generation, which automatically generates defect sample images and combines with less sample learning technology for industrial model training. It can further improve the model accuracy under the situation of insufficient sample information. In response to the high requirements for algorithm stability and accuracy in the manufacturing field, the Company uses AIGC for image quality improvement and proposes Imaging-Diffusion model. It gradually separates environmental interference factors such as light and rain fog from images, enhances image semantic information, and realizes image quality improvement as well as imaging normalization, whereby reducing the influence of environmental factors and improving the accuracy and stability of subsequent visual analysis. For the light weight and realtime requirements of AI applications in manufacturing, the Company adopts the knowledge distillation method to lightly compress the high-precision generative models and reduce the computation volume and computation time of model inference, so as to meet the requirements of production line deployment.

– 10 –

Meanwhile, the Company also actively established layout of the technical development of AIGC in the field of data intelligence, using AIGC for interactive report generation. By using Transformer to deeply analyze and correlate the meaning and text behind the report data, it can realize user-guided report generation based on the algorithm, while the algorithm can further analyze and identify potential problems in the report based on semantic analysis, establishing risk warning mechanism and auditing mechanism.

Continuous enrichment of AI products and solutions

In 2022, we continued to invest in R&D in AIGC areas such as pre-trained models and data generation. Relying on our self-developed MMOC AI technology platform, we began to develop AIGC capabilities to meet our own needs, which significantly enhanced the technical competitiveness of our manufacturing-oriented products and solutions. We focus on the continuous value enhancing in sub-sectors such as iron and steel metallurgy, panel semiconductor, automotive equipment, energy and power, Food & Beverage and New Material, intelligent manufacturing practical training, and finance, etc., to realize the integration and expansion of advanced AI infrastructure and diversified business scenarios, so that AI can empower more scenarios and industries.

In the direction of AIGC technology, different from the pan-scene big model represented by ChatGPT and LLM, AInnovation has developed AInnoGC solution (industry-oriented AIGC) based on years of industry and technology accumulation. Relying on self-developed MMOC AI technology platform and implementation experience, we apply industrial pre-training big model to pendant scenarios. While collecting human feedback and through reinforcement learning, we continuously iterate the industrial pre-trained big model to form a positive cycle.

In the field of iron and steel metallurgy, we continue to improve the standardization and enrich the functions of the intelligent molten iron transportation solution. We promote the in-depth integration of “platform + product” and focus on the platformization and generalization of our main product - intelligent molten iron transportation scenarios, so as to realize the application of the same technology in different scenarios. We have formed the overall solution of “hardware + software” and independently develop core intelligent hardware products through product iteration to continuously improve the product technology access threshold. We have enhanced the “1*N” strategy and established cooperation with a large steel company in Northwest China to complete the unmanned transformation of the first domestic GK1C internal combustion locomotive in the industry, which realized unmanned molten iron transportation in low-temperature, sandy, long-distance and cross-regional environments, and ensured that our solutions can deliver stable value to our customers in different production environments. We implement the “1+N” strategy of deeper serving for large customers, and cooperate further

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with entities that have built molten iron transportation system. Our team makes researches on the automatic lidadding and unloading software control system, conduct full research and multiple discussions for lid selection, material and lid-adding and unloading pipeline, to realize the full automation of lid-adding and unloading work. We have made breakthrough from “zero” in TPC automatic capping in the industry, helping customers to achieve targeted 10℃ temperature lowering for molten iron.

In the field of panel semiconductor, we provide glass panel edge quality inspection solutions and silicon wafer intelligent quality inspection all-in-one products. Among them, using the pre-training model provided by MMOC platform and cutting-edge small sample learning training algorithm, our glass panel inspection solution continues to optimize the inspection algorithm and the overall solution, increasing the types of defect detection and configuration solutions to adapt to multiple scenarios, forming a more standardized and rapidly deliverable product solution. It has completed hundreds of sets of delivery tasks within a number of large domestic panel companies this year. In the silicon wafer semiconductor industry, based on the combination of the Company’s MMOC platform and automated equipment, the detection accuracy and efficiency of deep learning technology are applied to create the first domestic silicon wafer intelligent quality inspection integrated machine products. It contributes to the domestic silicon wafer production of the whole process yield optimization, and the product has been validated in a leading domestic silicon wafer production enterprises through and officially put into production use.

In the field of automotive equipment, we have created advanced full lifecycle intelligent automation solutions covering automotive intelligent factories, new energy intelligent bases, semiconductor digital assembly workshops, discrete automated industrial production lines and high-end equipment packages to meet customer requirements for quality, production time, cost, transparency and responsiveness. The incoming material quality inspection, production quality control and product factory inspection are realized at the whole process level and incorporated into the whole process cycle management to obtain real-time quality status on site and identify quality problems in order to quickly locate and rectify these problems. At the same time, through the sharing of data from various departments, product quality is fully traceable and product quality is improved in all aspects. At present, the full lifecycle intelligent automation solution has been put into production use on a large scale by the leading domestic automotive equipment manufacturing enterprises.

– 12 –

In the field of energy power, we continue to improve the level of standardization and the richness of functions of power plant intelligent solutions. Against the background of the double carbon target, renewable energy is developing rapidly, however, the clean energy with the characteristics of intermittent power generation has a negative impact on the safety of grid operation. Based on the MMOC platform, we independently developed the thermal power plant flexible peaking and heat return system quality improvement and safety monitoring system, which ensures the flexible peaking and low-pollution operation of on-site equipment under safe working conditions through real-time dynamic safety control of on-site equipment and production systems by means of Orion automated machine learning and MatrixVision intelligent edge analysis. It has improved the level of deep peaking operation of thermal power units and ensured the key technical issues of continuous production of thermal power units under the spot trading system of power market.

In the field of Food & Beverage and New Material, we provide customers with production digital MOM system solutions, which are used to promote digital intelligent factory management through MES platform construction and equipment management to implement marketing, energy management upgrade construction and other services. With its help, customers can realize the integration from factory to headquarters, and aggregate operation data. It also assists customers in standard setting and operation analysis. In addition, we use MMOC platform to automatically analyze operation data and make intelligent decisions, thus greatly improving the comprehensive management efficiency of our customers. Besides, through process reengineering, technology interface and system integration, we can realize the precise control of the whole process from the source of production to the end of consumption, the prevention of defects and errors, and the comprehensive application of green manufacturing technology, whereby the integrated solution of “horizontal integration and vertical penetration” is realized.

In the field of intelligent manufacturing practical training, we rely on our rich practical experience in intelligent manufacturing business and regional advantages to build a trinity of “platform, base and service” to help universities cultivate practical and professional talents. Based on MMOC platform, we have realized the infrastructure of AI safety production and AI machine vision as the direction of practical training, and through MTStudio (Manufacture Training Studio) platform, we realize the carrying of practical training content and complete the learning and management of theoretical and practical courses. Through the teaching and training in the practice base, we have completed the experience and demonstration of real drill scenarios. Through collaborative cooperation with local colleges and universities, incubators and government employment authorities, we have completed the output of professional practical talents to the society.

– 13 –

In the financial industry, we focus on intelligent computing center solutions to provide customers with operational and management tools to help them achieve the goal of cost reduction and efficiency. Based on Orion platform, we have realized flexible scheduling of heterogeneous computing resources and optimized the efficiency of large-scale parallel computing to meet customers’ multi-scenario and multi-process needs. We have developed data center energy-efficiency management solutions that are driven by artificial intelligence, accurately control equipment usage based on machine learning features, improve management efficiency, and save energy and create green and low-carbon data centers. We continue to solidify our proprietary AIOps intelligent operation and maintenance solution, which detects abnormalities in advance, locates problems efficiently, gives solution suggestions, reduces manual intervention, and improves data center operation and maintenance efficiency. We continue to explore financial scenarios and use AI technology for product development in scenarios such as intelligent underwriting and financial automation to empower customers in the process of digital transformation.

Part II: Future Outlook

Our strong operating results in 2022 demonstrate that the commercialization of AI applications has entered into a period of scale development and that our business model is extremely resilient and proven. Going forward, we will continue to strengthen our long-term fundamental capabilities, focus on specialization, pursue high-quality growth, enhance customer experience, consolidate our competitive advantages, and continuously improve operational efficiency through refined management to achieve profitability early.

In the AI 2.0 era, we will continue to use the technology and implementation experience accumulated in the AI 1.0 era, actively explore the combination of AIGC technology and industry scenarios for implementation, continue to work to promote the digital transformation of the manufacturing industry, use technological innovation to create more value for all participants, and contribute to the high-quality development of the digital economy and fulfill social responsibility.

Continue to promote MMOC platform R&D and technological innovation

MMOC platform is the core technology platform of the Company. In the coming year, the Company will continue to increase investments in R&D and continue to move forward based on the MMOC Platform “3 Phase” Strategy. Meanwhile, we will closely follow the theme of generative AI development in AI2.0 era and strengthen the technological innovation and application breakthrough in the direction of AIGC.

– 14 –

Guided by implementation of applications, we will promote platform application by developing more scenariobased applications such as intelligent manufacturing practical training, wafer defect detection, glass defect detection, and vision alignment.

With technical assets as the core, we will continue to precipitate and manage the Company’s core data, algorithms, models and other technical assets to promote asset reuse, so as to reduce costs and increase efficiency.

Supported by AI platform, we will strengthen the platform engineering capability to meet the technical challenges of high reliability and high performance brought by scale implementation and focus on creating manufacturing industry features.

With the cloud platform as the base, we will consolidate the infrastructure capability, promote more systems, products and solutions to adopt cloud-native solutions, build AInnovation on the cloud and gradually open it to the public.

We will increase investment in AIGC-related technologies to further enhance AInnoGC capabilities, including industrial pre-training large models, large model development platform, MAAS platform, etc., to help innovation, R&D and delivery of the Company’s AIGC-related solutions.

MMOC Platform 2023 R&D Strategy

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----- Start of picture text -----

Standardization
Application External application/programming
implementation oriented
oriented Internal community-based operations
Technology assets Key algorithms/models/data assets
as the core Reusable software/hardware
component assets
Technology
Platformization Applicationization
assets
Supported by AI Multi-level, full-flow MMOC platform
platform Focus on creating intelligent
manufacturing industry features
Cloud platform as Solidifying AIGC Basic Technology
the base Building AInnovation on the Cloud and
opening it to the public
Communitization
----- End of picture text -----

Figure 2: MMOC Platform 2023 R&D Strategy

– 15 –

Strengthen the combination of AIGC and industry, and apply industrial pre-training large models in vertical scenarios

With the advent of AI 2.0 era, the Company will further combine algorithms with scenarios based on the algorithm research in 2022 to solve the deficiency and difficulties of industry applications and enhance AI applications with application implementation as the guide.

The Company will further combine the algorithm with scenarios to enhance the application of AIGC in various scenarios in the manufacturing industry. [1] The Company will further deepen the combination of AIGC algorithm and industry. We will integrate industry domain knowledge and use AInnoGC to simulate production line generation process to create AIGC algorithms with industry characteristics, generate higher quality, physically realistic samples, improve the performance of large industrial models, and promote efficient and lowcost application of algorithms. [2] The Company will further expand the application scope of AIGC algorithm. In addition to data generation and image quality improvement, we will further study the application of AIGC in the field of label generation to achieve end-to-end data quality improvement and result output of visual analysis, and improve the accuracy and precision of visual analysis. [3] The Company will further broaden the application scenarios of AIGC, and make research on algorithms related to intelligent production line layout and automatic scheduling for its needs in industries such as production line automation and training centers, and combine AIGC with knowledge mapping to research intelligent solution algorithms for specific fields.

The Company will conduct research on the deficiencies of industry applications, in order to improve the usability of algorithms in manufacturing scenarios. In order to meet the real-time requirements of manufacturing scenarios, the Company will also further strengthen the research on model light-weighting and acceleration, draw on the characteristics of many different models, perform model blending, and improve the expressiveness and processing speed of models.

The Company will combine the construction of MMOC platform to improve the user friendliness of algorithms. The Company will integrate algorithm research results and provide model services for AI developers based on MMOC platform to further reduce R&D costs and promote the standardization of AI solution performance.

– 16 –

Continue to enrich AI products and solutions

In 2023, we will continue to invest in R&D in the direction of AIGC. Relying on the MMOC artificial intelligence technology platform, we will explore more business application scenarios, enhance the technical competitiveness of products and solutions, and help manufacturing enterprises to upgrade digitally and intelligently.

In the field of iron and steel metallurgy, we will continue to refine and precipitate the standardized modules in the intelligent molten iron transportation solution, improve the delivery speed and reduce the delivery cost, and take the molten iron transportation-related products as the core to realize the diversified operation of molten iron transportation through vertical scenario expansion. We will explore deeper into the demand of iron and steel scenarios. In terms of horizontal application expansion, we will explore new applications of the iron and steel scenarios, expand the application scenarios of the infield rail transportation industry, and increase the productization layout, so as to support the expanding business needs of the program and business to achieve 1*N replication from the current seed customers to other steel manufacturing enterprises.

In the field of panel semiconductor, we will continue to enrich and improve the panel glass quality inspection product solutions and the functions of the silicon wafer intelligent quality inspection all-in-one machine based on the existing customers’ production flow, production process, quality improvement and other requirements for intelligent manufacturing upgrade. In the panel glass quality inspection industry, we will expand the functions of comprehensive glass inspection based on the existing product functions, and use deep learning technology to solve the defects in complex scenarios. In the semiconductor industry, we will continue to optimize the functions of existing products, promote and replicate existing successful products in the industry, and simultaneously expand our product series to meet the demand for different sizes of silicon wafer inspection.

– 17 –

In the field of automotive equipment, we will further optimize our full lifecycle intelligent automation solutions by providing digital and visualization means to physically enable digital assets such as new product development, factory planning and production line upgrades. By combining physical simulation and data analysis with digital twin technology and creating detailed simulations in a fully virtual environment, we provide companies with easy access, standardization, efficiency and security, and systematic innovation. In using of a dual-engine intelligent decision-making algorithm that incorporates operations optimization and machine learning, global dynamic resource allocation optimization has been achieved and users can make fast and accurate business decisions in a complex and dynamically changing environment. This contributes not only to promote refined global management of factories, but also significantly improves their production performance and efficiency.

In the field of energy and power, we will continue to accumulate and improve product standardization in solutions for intelligent thermal power, intelligent wind power and intelligent new energy power plants, improve delivery speed, ensure delivery quality and reduce delivery costs. With our refined products and quality services, we will enhance our brand value and gradually become an excellent industrial leader in intelligent power plant solutions.

In the field of Food & Beverage and New Material, based on the existing production digital MOM system solution, we fully respond to the national requirements for manufacturing enterprises on “localization, intelligence, informationization, digital construction”, and further extend to the whole chain of Food & Beverage and New Material production digitalization and intelligent MOM solutions such as source, grid, load and energy storage. For solution extension in the Food & Beverage and New Material production scenario amidst of rapid recovery after the pandemic, AIGC may be used to generate storage drawings and optimize production line productivity based on supply chain and storage rules. Meanwhile, we will support more operational data collection and analysis in the future to provide digital intelligent operation and maintenance support for more factories including production lines and equipment, while combining our MOM platform and AIGC capabilities to generate reports by interactively guiding users. Through intelligent analysis capabilities, potential problems in reports are automatically analyzed and identified, risk warning mechanisms and auditing mechanisms are established, and a highly efficient intelligent closed-loop MOM platform for the Food & Beverage and New Material sector is realized.

– 18 –

In the field of intelligent manufacturing practical training, we will continue to refine the combination of business practice and practical training content, deepen the practical implementation of AI + intelligent manufacturing field, continue to iterate the platform construction, expand the base practice scenarios and applications, and continuously improve and enrich the talent training program. We will conduct application teaching for more people and continue to help colleges and universities cultivate professional talents of AI + intelligent manufacturing for the society. For students’ own knowledge level differences, we have embed the AIGC technology into the post-class quiz module, customizing questions according to students’ previous answer level to ensure that students fully master the key points of relevant knowledge.

In the financial industry, we will continue to take the advantage of AInnovation AI, through the intelligent calculation center solution, data governance solutions to provide high-quality digital infrastructure and data resources tools for the industry. We will adhere to the strategy of scenario-based solutions for the financial industry, continuous investment in intelligent marketing, intelligent underwriting, wealth management and other scenarios, to create standardized products to meet the business needs of financial customers, and to help customers in quick digital transformation.

MANAGEMENT DISCUSSION AND ANALYSIS

OVERVIEW

In the past five years since the establishment of AInnovation, we are continuously committed to promoting the implementation of cutting-edge artificial intelligence technology in the real industry represented by the manufacturing industry, assisting in new industrialization and high-quality development, and promoting the integration and development of the digital economy and the real economy. As the market leader of “AI + Manufacturing” solutions in China, we adhered to the “specialized and new” strategy and are pursuing longterm sustainable organic growth by strengthening our business in eight sub-sectors of manufacturing industry (iron and steel metallurgy, panel and semiconductors, 3C high-tech, engineering and construction, automotive equipment, energy and power, Food & Beverage and New Material, and intelligent manufacturing training) and financial services industry. Thanks to the right corporate development strategy, deep technical product accumulation and profound insight into the industry scenario, we have achieved excellent results in terms of quantity and quality in the fiscal year 2022.

– 19 –

REVENUE

Our revenue increased by 80.9% from RMB861.2 million in the fiscal year ended 31 December 2021 to RMB1,557.6 million in the fiscal year ended 31 December 2022. The increase was primarily attributable to (i) the increase in revenue realized from manufacturing industry and financial services industry; (ii) the increase in total number of customers and number of premium customers; and (iii) the acquisition of two new subsidiaries during the period resulted in revenue growth by broadening the business areas.

Manufacturing industry. Revenue from manufacturing industry increased by 111.2% from RMB449.0 million in the fiscal year ended 31 December 2021 to RMB948.2 million in the fiscal year ended 31 December 2022.

Financial services industry. Revenue from financial services industry increased by 39.5% from RMB274.1 million in the fiscal year ended 31 December 2021 to RMB382.3 million in the fiscal year ended 31 December 2022.

Our total number of customers increased from 159 in the fiscal year ended 31 December 2021 to 292 in the fiscal year ended 31 December 2022.

We define the customer with revenue contribution of RMB4.5 million or more in a fiscal year as a premium customer. The number of premium customers increased from 42 in the fiscal year ended 31 December 2021 to 71 in the fiscal year ended 31 December 2022. The total revenue contributed by the premium customers was RMB798.7 million and RMB1,351.0 million in 2021 and 2022 respectively.

COST OF SALES

Our cost of sales increased by 76.9% from RMB593.9 million in the fiscal year ended 31 December 2021 to RMB1,050.5 million in the fiscal year ended 31 December 2022. The increase was caused by business expansion in manufacturing industry and financial services industry, and the acquisition of two new subsidiaries during the Reporting Period, which broadened the business areas and resulted in cost increases.

– 20 –

Manufacturing industry. Cost of sales from manufacturing industry increased by 107.2% from RMB287.0 million in the fiscal year ended 31 December 2021 to RMB594.8 million in the fiscal year ended 31 December 2022, primarily due to the expansion of manufacturing business, which increased 111.2% from RMB449.0 million in the fiscal year ended 31 December 2021 to RMB948.2 million in the fiscal year ended 31 December 2022.

Financial services industry. Cost of sales from financial services industry increased by 40.7% from RMB199.8 million in the fiscal year ended 31 December 2021 to RMB281.2 million in the fiscal year ended 31 December 2022, primarily due to the expansion of financial services business, which increased 39.5% from RMB274.1 million in the fiscal year ended 31 December 2021 to RMB382.3 million in the fiscal year ended 31 December 2022.

GROSS PROFIT AND GROSS MARGIN

As a result of foregoing, our overall gross profit increased by 89.7% from RMB267.2 million in the fiscal year ended 31 December 2021 to RMB507.1 million in the fiscal year ended 31 December 2022. In 2021 and 2022, our overall gross margin was 31.0% and 32.6% respectively. This was primarily attributable to (i) economies of scales; (ii) increased pricing power; and (iii) more standardized products and solutions with more technology assets accumulated upon our platforms.

SELLING AND DISTRIBUTION EXPENSES

Our selling and distribution expenses increased by 40.3% from RMB116.0 million in the fiscal year ended 31 December 2021 to RMB162.7 million in the fiscal year ended 31 December 2022, primarily due to (i) the expansion of our sales team to support the expansion of our business and the increase in sales employee compensation and benefit expenses; (ii) the increase in AInnovation brand promotion efforts; and (iii) amortization of intangible assets arising from acquisition.

– 21 –

Selling and distribution expenses as a percentage of revenue decreased from 13.5% in the fiscal year ended 31 December 2021 to 10.4% in the fiscal year ended 31 December 2022. Selling and distribution expenses (excluding share-based payments and amortization of intangible assets arising from acquisition) as a percentage of revenue was 7.1% in the fiscal year ended 31 December 2022, a decrease of 1.1% compared to 8.2% in the fiscal year ended 31 December 2021, as our revenue grew at a faster rate.

GENERAL AND ADMINISTRATIVE EXPENSES

Our general and administrative expenses decreased by 26.7% from RMB449.4 million in the fiscal year ended 31 December 2021 to RMB329.5 million in the fiscal year ended 31 December 2022, primarily due to (i) the decrease in share-based payment expenses, from RMB290.5 million in the fiscal year ended 31 December 2021 to RMB112.5 million in the fiscal year ended 31 December 2022; and (ii) the decrease in listing expenses from RMB51.5 million in the fiscal year ended 31 December 2021 to RMB26.5 million in the fiscal year ended 31 December 2022.

General and administrative expenses as a percentage of revenue decreased from 52.2% in the fiscal year ended 31 December 2021 to 21.2% in the fiscal year ended 31 December 2022. General and administrative expenses as a percentage of revenue (excluding share-based payments and listing expenses) was 12.2% in the fiscal year ended 31 December 2022, a decrease of 0.3% from 12.5% in the fiscal year ended 31 December 2021, as our revenue grew at a faster rate.

RESEARCH AND DEVELOPMENT EXPENSES

Our research and development expenses increased by 27.0% from RMB327.7 million in the fiscal year ended 31 December 2021 to RMB416.3 million in the fiscal year ended 31 December 2022, primarily due to (i) the increase in overall research and development investment due to business expansion; and (ii) amortization of intangible assets arising from acquisition.

– 22 –

Research and development expenses as a percentage of revenue decreased from 38.1% in the fiscal year ended 31 December 2021 to 26.7% in the fiscal year ended 31 December 2022. Research and development expenses as a percentage of revenue (excluding share-based payments and amortization of intangible assets arising from acquisition) was 25.3% in the fiscal year ended 31 December 2022, a decrease of 4.5% from 29.8% in the fiscal year ended 31 December 2021, as our revenue grew at a faster rate.

NET IMPAIRMENT LOSSES ON FINANCIAL ASSETS

Our net impairment loss on financial assets in the fiscal year ended 31 December 2022 was RMB37.0 million, compared to a net impairment loss of RMB24.1 million in the fiscal year ended 31 December 2021, mainly due to an increase in the provision for impairment of trade and other receivables during the Reporting Period.

OTHER INCOME

Other income consists primarily of government grants, which mainly relate to financial assistance from local governments in PRC.

Our other income increased from RMB28.1 million in the fiscal year ended 31 December 2021 to RMB56.0 million in the fiscal year ended 31 December 2022, primarily due to the increased government grants we obtained.

OTHER LOSSES, NET

Our other losses, net primarily consist of (i) foreign exchange gains (losses); and (ii) changes in the fair value of financial assets and liabilities at fair value through profit or loss.

In the fiscal year ended 31 December 2022, we had a net other loss of RMB9.2 million compared to RMB1.0 million in the fiscal year ended 31 December 2021, mainly due to the increase in losses on financial assets and liabilities at fair value through profit or loss.

– 23 –

OPERATING LOSS

As a result of the foregoing, our operating loss decreased by 37.0% from RMB622.8 million in the fiscal year ended 31 December 2021 to RMB392.3 million in the fiscal year ended 31 December 2022, mainly due to the increase in our overall revenue and gross profit.

FINANCE INCOME

Our financial income increased from RMB24.0 million in the fiscal year ended 31 December 2021 to RMB38.7 million in the fiscal year ended 31 December 2022, mainly due to an increase in interest income from bank deposits.

FINANCE COSTS

Our finance costs are primarily comprised of (i) interest expenses on lease liabilities; (ii) interest expenses on bank borrowings; and (iii) interest expenses on convertible bonds.

Our finance costs decreased from RMB36.1 million in the fiscal year ended 31 December 2021 to RMB8.1 million in the fiscal year ended 31 December 2022, mainly due to the finance costs of financial liabilities of redeemable shares reduced to nil during the Reporting Period.

LOSS FOR THE YEAR

As a result of the foregoing, our loss for the year decreased by 43.1% from a loss of RMB635.1 million in the fiscal year ended 31 December 2021 to RMB361.2 million in the fiscal year ended 31 December 2022.

NON-IFRS MEASURES

Adjusted Net Loss

We define adjusted net loss as the net loss for the year adjusted by adding back share-based payment expenses, finance costs of financial liabilities of redeemable shares, listing expenses, amortization of intangible assets arising from acquisition and changes in fair value of financial assets/liabilities at fair value through profit or loss. The changes in fair value of financial assets/liabilities at fair value through profit or loss mainly include fair value changes of fund investments, other financial investments, contingent considerations and convertible bonds.

– 24 –

The following table reconciles our adjusted net loss for the years presented to the most directly comparable financial measure calculated and presented in accordance with IFRSs, which are net loss or income for the years.

Reconciliation of net loss to adjusted net loss: Loss for the year Add: Share-based payment expenses Finance costs of financial liabilities of redeemable shares Listing expenses Amortization of intangible assets arising from acquisition Changes in fair value of financial assets/liabilities at fair value through profit or loss Adjusted net loss (Unaudited)	Year ended 31 December 2021 2022 RMB’000 RMB’000 (635,124) (361,160) 406,967 173,294 34,877 — 51,500 26,457 — 14,292 — 8,716 (141,780) (138,401)

LIQUIDITY AND CAPITAL RESOURCES

Cash and Cash Equivalents

As at 31 December 2022, cash and cash equivalents of the Group was approximately RMB1,642.7 million, compared to approximately RMB1,553.2 million as at 31 December 2021. The change was mainly from the proceeds we received from our IPO and cash outflow from investing and operating activities. Most of the cash and cash equivalents of the Group were denominated in RMB.

Gearing Ratio

The Group monitors capital on basis of the gearing ratio, which is calculated as net debt divided by total equity. Net debt is calculated as total borrowings (including related party borrowing), convertible bonds and lease liabilities less cash and cash equivalents. As of 31 December 2022, the Group had a net cash position and the gearing ratio was not applicable.

– 25 –

MATERIAL ACQUISITIONS AND DISPOSALS

The Acquisition of 51% Equity Interest in Two Target Companies

Share Transfer Agreement I

Date:

20 May 2022

Contracting Parties:

The Company, as the Purchaser;

Chen Hong, as the Vendor;

Liao Lu, as the Vendor;

He Li, as the Vendor;

Shanghai Higher Mechanical & Electrical Co., Ltd. (“ Target Company I ”);

Shanghai Haochen Business Development Partnership Enterprise (Limited Partnership) (“ Shanghai Haochen ”); and

Shanghai Xiyao Business Management Consulting Partnership Enterprise (Limited Partnership) (“ Shanghai

Xiyao ”).

To the best of the Directors’ knowledge, information and belief after making all reasonable enquiries, Chen Hong, Liao Lu, He Li, Target Company I, Shanghai Haochen and Shanghai Xiyao are third parties independent of the Company and its associates.

– 26 –

Subject Matters and Contract Consideration:

The Company has agreed to conditionally purchase, and Chen Hong, Liao Lu and He Li (collectively as “ Vendors I ”) as the Vendors, have agreed to conditionally sell, an aggregate of 51% equity interest in Target Company I at the total consideration of RMB153.0 million. The total consideration of Share Transfer Agreement I is RMB153.0 million. The total consideration is determined after arm’s length negotiation between the Company and Vendors I based on the projected revenue of Target Company I in 2022 and price-to-sales ratio of five comparable companies in 2022, with reference to the marketability discount and transaction discount for cash-only transaction of Target Company I as a non-listed company. The five comparable companies are listed on the Shanghai Stock Exchange or the Shenzhen Stock Exchange.

Share Transfer Agreement II

Date:

20 May 2022

Contracting Parties:

The Company, as the Purchaser;

Li Weiguo, as the Vendor;

Li Junhong, as the Vendor;

Zhou Changbin, as the Vendor;

Qingdao Aolipu Qizhi Intelligent Industrial Technology Co., Ltd. (“ Target Company II ”);

Qingdao Aolizhiyuan Business Management Service Partnership Enterprise (Limited Partnership) (“ Qingdao Aolizhiyuan ”); and

Qingdao Aoliruiyuan Business Management Service Partnership Enterprise (Limited Partnership) (“ Qingdao Aoliruiyuan ”).

– 27 –

To the best of the Directors’ knowledge, information and belief after making all reasonable enquiries, Li Weiguo, Li Junhong, Zhou Changbin, Target Company II, Qingdao Aolizhiyuan and Qingdao Aoliruiyuan are third parties independent of the Company and its associates.

Subject Matters and Contract Consideration:

The Company has agreed to conditionally purchase, and Li Weiguo, Li Junhong and Zhou Changbin (collectively as “ Vendors II” ) as the Vendors, have agreed to conditionally sell, an aggregate of 51% equity interest in Target Company II at the total consideration of RMB122.4 million. The total consideration of Share Transfer Agreement II is RMB122.4 million. The total consideration is determined after arm’s length negotiation between the Company and Vendors II based on the projected revenue of Target Company II in 2022 and priceto-sales ratio of six comparable companies in 2022, with reference to the marketability discount and transaction discount for cash-only transaction of Target Company II as a non-listed company. The six comparable companies are listed on the Shanghai Stock Exchange or the Shenzhen Stock Exchange.

Despite that the unaudited net assets and profit of Target Company II in 2021 recorded a loss, the Board is of the view that the consideration of the acquisition of 51% equity interest in Target Company II is fair and reasonable based on the following reasons:

(1) the consideration is determined mainly based on the projected revenue of Target Company II in 2022 amounting to RMB105 million. The financial data of Target Company II as of 31 December 2021 as set out in the announcement by the Company is unable to reflect the latest financial position of Target Company II. In consideration of the booming potential business opportunities arising from the adequate existing orders of Target Company II and high customer repurchase rate, it is likely to achieve breakthroughs in results performance with a total revenue amounting to RMB105 million in 2022;
(2) immediately prior to the entering into of Share Transfer Agreement II, the former shareholders of Target Company II have fully paid their respective subscribed registered capital of Target Company II and a capital injection of RMB27.64 million was made by the largest shareholder to Target Company II with an intention to reduce the debt level of Target Company II, and the financial position of Target Company II saw significant improvement immediately following the closing;

– 28 –

(3) after years of technology improvement and accumulation, Target Company II enhanced its project implementation efficiency and reduced costs, hence it is foreseeable that the profit of Target Company II will increase in 2022;
(4) Target Company II is engaged in the industrial software industry which has immense potential and is strongly supported by national policies. Therefore, the Board is optimistic on the future business prospect of Target Company II and considers the acquisition as a good investment opportunity to increase the Group’s investment return;
(5) the revenue of Target Company II is expected to increase in the next few years, with its amount being basically at the same level of the amount of consideration. Even if Target Company II fails to deliver the expected growth rate of revenue in the future, the consideration to be actually paid by the Company will be adjusted accordingly based on the performance of Target Company II as the acquisition introduced a performance commitment mechanism. As such, the Board believes that the performance commitment mechanism in the acquisition can effectively ensure the consideration to be paid by the Company will match the actual value of Target Company II, and mitigate the risks arising from improper operation of Target Company II which may cause damages to the Company.

Please refer to the announcement of the Company dated 20 May 2022 for details of the acquisition of 51% equity interest in two target companies.

Save as disclosed above, the Group did not have any material acquisitions or disposals of subsidiaries, consolidated affiliated entities or associated companies for the year ended 31 December 2022.

– 29 –

Disclosure made pursuant to Rule 14.36B of the Listing Rules

1. Discloseable transaction in relation to the acquisition of 51% equity interest in Target Company I

As for Target Company I, all parties agreed that the years of 2022, 2023 and 2024 will be the performance commitment period (the “ Performance Commitment Period ”) of Vendors I, during which, except for the matters that shall be considered and approved by the board of directors, the board of supervisors and the shareholders’ meeting of Target Company I as required by the laws and rules, the articles of association of Target Company I and the transaction documents or the matters that shall be agreed in writing by the Company before being implemented, the major operation and management matters of Target Company I shall be the sole responsibility of Chen Hong, an existing shareholder of Target Company I. Chen Hong undertakes that the following performance indicators will be satisfied:

Item	Performance Commitment	Performance Commitment	Indicator
Fiscal Year	20221	2023	2024
Revenue (RMB0’000)	21,818	33,000	44,000
Sales gross margin2	Meeting	Meeting	Meeting
	the annual	the annual	the annual
	business	business	business
	guideline	guideline	guideline
	of the Company	of the Company	of the Company
Financial gross margin3	Meeting	Meeting	Meeting
	the annual	the annual	the annual
	business	business	business
	guideline	guideline	guideline
	of the Company	of the Company	of the Company
Net profit (excluding extraordinary gains	660	1,320	1,760
and losses)4(RMB0’000)

Notes:

The performance indicators for 2022 refer to the performance indicators consolidated after the Company acquired Target Company I only.
Sales gross margin = (turnover – external procurement costs)/revenue.
Financial gross margin = (turnover – costs of revenue)/revenue.
Net profit (excluding extraordinary gains and losses) refers to the net profit after deducting the extraordinary gains and losses.

– 30 –

During the Performance Commitment Period, the Company shall calculate the Share Transfer Payment (each amount being referred to as “ Adjusted Share Transfer Price ”) to be paid in the year according to the fulfillment of the Performance Commitment Indicator, and pay it to each of Vendors I separately according to the following formula: Adjusted Share Transfer Payment = Share Transfer Payment before Adjustment × The performance achievement rate after taking into account the collection of payments.

From the date of consolidation after the acquisition of Target Company I to 31 December 2022, the revenue of Target Company I was RMB219,468,000 and the net profit (excluding extraordinary gains and losses) (unaudited) was RMB7,335,000.

According to the Company’s announcement dated 20 May 2022, 30 June of each year or the date on which the Vendors I make payment application (whichever is earlier) shall be the closing date for collection of payments for the previous year (the “ Collection Date ”). The Company shall calculate the performance achievement rate after taking into account the collection of payments based on the actual collection status before the Collection Date. As at the date of this announcement, the Company has not yet been able to calculate the performance achievement rate after taking into account the collection of payments as the agreed Collection Date is yet pending. Accordingly, the performance commitment of Target Company I for the year ending 31 December 2022 is still in progress and the Company will closely monitor the completion of the said performance commitment.

– 31 –

2. Discloseable transaction in relation to the acquisition of 51% equity interest in Target Company II

As for Target Company II, all parties agreed that the years of 2022, 2023 and 2024 will be the performance commitment period (the “ Performance Commitment Period ”) of Vendors II, during which, except for the matters that shall be considered and approved by the board of directors, the board of supervisors and the shareholders’ meeting of Target Company II as required by the laws and rules, the articles of association of Target Company II and the transaction documents or the matters that shall be agreed in writing by the Company before being implemented, the major operation and management matters of Target Company II shall be the sole responsibility of Li Weiguo, an existing shareholder of Target Company II. Li Weiguo undertakes that the following performance indicators will be satisfied:

Item	Performance Commitment	Performance Commitment	Indicator
Fiscal Year	20221	2023	2024
Revenue (RMB0’000)	8,000	15,000	22,500
Sales gross margin2	Meeting	Meeting	Meeting
	the annual	the annual	the annual
	business	business	business
	guideline	guideline	guideline
	of the Company	of the Company	of the Company
Financial gross margin3	Meeting	Meeting	Meeting
	the annual	the annual	the annual
	business	business	business
	guideline	guideline	guideline
	of the Company	of the Company	of the Company
Net profit (excluding extraordinary gains	600	1,100	2,300
and losses)4(RMB0’000)

Notes:

The performance indicators for 2022 refer to the performance indicators consolidated after the Company acquired Target Company II only.
Sales gross margin = (turnover – external procurement costs)/revenue.
Financial gross margin = (turnover – costs of revenue)/revenue.
Net profit (excluding extraordinary gains and losses) refers to the net profit after deducting the extraordinary gains and losses.

– 32 –

During the Performance Commitment Period, the Company shall calculate the Share Transfer Payment (each amount being referred to as “ Adjusted Share Transfer Price ”) to be paid in the year according to the fulfillment of the Performance Commitment Indicator, and pay it to each of Vendors II separately according to the following formula: Adjusted Share Transfer Payment = Share Transfer Payment before Adjustment × The performance achievement rate after taking into account the collection of payments.

From the date of consolidation after the acquisition of Target Company II to 31 December 2022, the revenue of Target Company I was RMB81,608,000 and the net profit (excluding extraordinary gains and losses) (unaudited) was RMB7,040,000.

According to the Company’s announcement dated 20 May 2022, 30 June of each year or the date on which the Vendors II make payment application (whichever is earlier) shall be the closing date for collection of payments for the previous year (the “ Collection Date ”). The Company shall calculate the performance achievement rate after taking into account the collection of payments based on the actual collection status before the Collection Date. As at the date of this announcement, the Company has not yet been able to calculate the performance achievement rate after taking into account the collection of payments as the agreed Collection Date is yet pending. Accordingly, the performance commitment of Target Company II for the year ended 31 December 2022 is still in progress and the Company will closely monitor the completion of the said performance commitment.

– 33 –

FUTURE PLANS FOR MATERIAL INVESTMENTS OR CAPITAL ASSET

As at 31 December 2022, save as disclosed in this announcement, we did not have other future plans for material investments or capital assets.

FOREIGN EXCHANGE EXPOSURE

During the fiscal year ended 31 December 2022, the Group mainly operated in PRC with most of the transactions settled in RMB. The functional currency of our Company and the subsidiaries is RMB. As of 31 December 2022, our balance of the cash and cash equivalents was mainly denominated in RMB and Hong Kong Dollars. The Group manages its foreign exchange risk by closely monitoring the movement of the exchange rates and will consider hedging significant foreign currency exposure if necessary. As at 31 December 2022, our business is not exposed to any significant foreign exchange risk.

PLEDGE OF ASSETS

As at 31 December 2022, the Group had no material pledge of assets.

BORROWINGS

As at 31 December 2022, borrowings of the Group were RMB57.6 million (31 December 2021: Nil), mainly include short-term borrowings of subsidiaries acquired during the year.

CONTINGENT LIABILITIES

As at 31 December 2022, we did not have any material contingent liabilities.

SUBSEQUENT EVENT

There was no significant event subsequent to the end of the Reporting Period and up to the date of this announcement.

– 34 –

OTHER INFORMATION

Dividend

The Board does not recommend a final dividend for the year ended 31 December 2022.

Purchase, Sale or Redemption of the Company’s Listed Securities

Since the Listing Date and up to the date of this announcement, the Company repurchased a total of 13,343,800 H Shares (the “ Repurchased Shares ”) on the Stock Exchange for a total consideration of approximately HK$296,765,429. Details of the Repurchased Shares are as follows.

Month of Repurchase 2022 May June July September November December 2023 January Total	Number of Repurchased Shares Price per share paid Highest Price (HK$) Lowest Price (HK$) 1,394,300 23.30 22.50 6,415,600 23.95 19.76 824,200 20.70 16.84 37,700 18.68 17.58 3,219,400 22.60 19.64 1,429,200 23.75 21.60 23,400 25.30 25.25 13,343,800	Total Consideration (HK$) 32,241,430.00 143,580,922.00 16,292,468.00 694,842.00 70,363,052.00 33,000,800.00 591,915.00 296,765,429.00

As at the date of this announcement, the Repurchased Shares have not been cancelled and the balance of the issued shares of the Company was 559,304,838. The repurchase of the Shares as referred to in the circular of the Company dated 14 April 2022 was for the purpose of stabilizing the share price of the Company and safeguarding the value of the Company and the interests of the shareholders.

– 35 –

Except as disclosed in this announcement, neither the Company nor the Group has purchased, sold or redeemed any of the Company’s listed securities during the Reporting Period and up to the date of this announcement.

Corporate Governance Practices

The Board is committed to maintaining high corporate governance standards. The Board believes that high corporate governance standards are essential in providing a framework for the Group to safeguard the interests of shareholders of the Company, enhance corporate value, formulate its business strategies and policies, and enhance its transparency and accountability.

The Company has adopted the principles and code provisions of the Corporate Governance Code (“ CG Code ”) contained in Appendix 14 of the Listing Rules as the basis of the Company’s corporate governance practices. The Company is committed to the view that the Board should include a balanced composition of executive Directors and independent non-executive Directors so that there is a strong independent element on the Board, which can effectively exercise independent judgement.

The Company has complied with all applicable code provisions set out in the CG Code throughout the period from the Listing Date up to the date of this announcement.

The Company has also put in place certain recommended best practices as set out in the CG Code.

Model Code for Securities Transactions by Directors, Supervisors and Employees

The Company has adopted the Model Code to regulate all dealings by Directors, Supervisors and relevant employees of securities in the Company and other matters covered by the Model Code since the Listing Date.

All Directors, Supervisors and relevant employees, having been made specific enquiries, confirmed that they have been in compliance with the Model Code during the period from the Listing Date up to the date of this announcement.

The Company has also adopted the model code for securities transactions by employees who may hold pricesensitive information of the Company that is not publicly available. The Company was not aware of any incompliance with the Model Code by any employee during the period from the Listing Date up to the date of this announcement.

– 36 –

Scope of Work of the Auditor

The figures in respect of the Group’s consolidated balance sheet, consolidated statement of comprehensive income and the related notes thereto for the year ended 31 December 2022 as set out in announcement have been agreed by the Group’s auditor, PricewaterhouseCoopers, to the amounts set out in the Group’s audited consolidated financial statements for the year. The work performed by PricewaterhouseCoopers in this respect did not constitute an audit, review or other assurance engagement, and consequently no assurance has been expressed by the PricewaterhouseCoopers on this announcement.

Audit Committee

The Audit Committee has reviewed the annual results of the Group for 2022 and the audited consolidated financial statements for the year ended 31 December 2022 which were prepared in accordance with the International Financial Reporting Standards.

PUBLICATION OF THE ANNUAL RESULTS AND ANNUAL REPORT

This annual results announcement is published on the websites of the Stock Exchange (www.hkexnews.hk) and the Company (www.ainnovation.com). The annual report of the Group in the fiscal year ended 31 December 2022 will be dispatched to the Company’s shareholders and made available for review on the same websites in due course.

– 37 –

FINANCIAL STATEMENTS

CONSOLIDATED STATEMENT OF COMPREHENSIVE INCOME

FOR THE YEAR ENDED 31 DECEMBER 2022

Note
Revenue
4
Cost of sales
5
Gross profit
Selling and distribution expenses
5
General and administrative expenses
5
Research and development expenses
5
Net impairment losses on financial assets
Share of net losses of investments accounted for using the equity method
Other income
6
Other losses, net
7
Operating loss
Finance costs
8
Finance income
8
Loss before income tax
Income tax credit/(expense)
9
Loss for the year
(Loss)/profit for the year attributable to:
Owners of the Company
Non-controlling interests

Year ended 31 December
2022
2021
RMB’000
RMB’000
1,557,643
861,168
(1,050,565)
(593,927)
507,078
267,241
(162,703)
(115,975)
(329,531)
(449,375)
(416,309)
(327,698)
(37,022)
(24,057)
(575)
—
56,009
28,067
(9,238)
(1,044)
(392,291)
(622,841)
(8,089)
(36,097)
38,708
24,022
(361,672)
(634,916)
512
(208)
(361,160)
(635,124)
(363,042)
(636,599)
1,882
1,475
(361,160)
(635,124)

– 38 –

CONSOLIDATED STATEMENT OF COMPREHENSIVE INCOME (CONTINUED)

FOR THE YEAR ENDED 31 DECEMBER 2022

Note
Other comprehensive income, net of tax
Items that will not be reclassified subsequently to profit or loss
Changes in the fair value of equity investments at fair
value through other comprehensive income
Items that will be reclassified subsequently to profit or loss
Currency translation difference
Other comprehensive income for the year, net of tax
Total comprehensive loss for the year, net of tax
Total comprehensive (loss)/income for the year attributable to:
Owners of the Company
Non-controlling interests
Total comprehensive loss for the year
Basic and diluted loss per share for loss
attributable to the owners of the Company (in RMB)
11

Year ended 31 December
2022
2021
RMB’000
RMB’000
—
22
192
—
192
22
(360,968)
(635,102)
(362,944)
(636,577)
1,976
1,475
(360,968)
(635,102)
(0.66)
(1.43)

– 39 –

CONSOLIDATED BALANCE SHEET

AS AT 31 DECEMBER 2022

Note
ASSETS
Non-current assets
Property, plant and equipment
Right-of-use assets
Intangible assets
12
Goodwill
13
Investments accounted for using the equity method
Other non-current assets
Total non-current assets
Current assets
Inventories
Trade and notes receivables
14
Prepayments and other receivables
15
Financial assets at fair value through other comprehensive income
Financial assets at fair value through profit or loss
16
Amounts due from related parties
Restricted cash
Cash and cash equivalents
Total current assets
Total assets
EQUITY
Equity attributable to owners of the Company
Share capital
Share premium
Less: Treasury share
Other reserves
Accumulated losses
Non-controlling interests
Total equity

As at 31 December
2022
2021
RMB’000
RMB’000
81,943
79,212
75,089
87,072
206,620
5,672
194,552
—
342
—
24,767
11,810
583,313
183,766
107,772
71,723
534,422
362,000
190,939
54,032
5,310
34,333
156,020
—
38,091
3,206
9,915
2,697
1,642,665
1,553,150
2,685,134
2,081,141
3,268,447
2,264,907
559,305
514,560
2,562,978
1,674,871
(258,821)
—
671,882
498,490
(1,265,915)
(902,873)
2,269,429
1,785,048
89,546
10,260
2,358,975
1,795,308

– 40 –

CONSOLIDATED BALANCE SHEET (CONTINUED)

AS AT 31 DECEMBER 2022

Note LIABILITIES Non-current liabilities Lease liabilities Deferred income tax liabilities Other non-current liabilities Financial liabilities at fair value through profit or loss 19 Total non-current liabilities Current liabilities Borrowings Lease liabilities Trade and notes payables 17 Contract liabilities Other payables and accruals 18 Amounts due to related parties Current income tax liabilities Financial liabilities at fair value through profit or loss 19 Total current liabilities Total liabilities Total equity and liabilities	As at 31 December 2022 2021 RMB’000 RMB’000 70,153 78,289 27,322 — 15,523 26,579 73,166 — 186,164 104,868 57,590 — 19,958 9,282 280,324 227,719 105,183 43,649 162,375 83,873 20,451 — 3,056 208 74,371 — 723,308 364,731 909,472 469,599 3,268,447 2,264,907	As at 31 December 2022 2021 RMB’000 RMB’000 70,153 78,289 27,322 — 15,523 26,579 73,166 — 186,164 104,868 57,590 — 19,958 9,282 280,324 227,719 105,183 43,649 162,375 83,873 20,451 — 3,056 208 74,371 — 723,308 364,731 909,472 469,599 3,268,447 2,264,907
		104,868
		— 9,282 227,719 43,649 83,873 — 208 —
		364,731
		469,599
		2,264,907

– 41 –

NOTES TO THE CONSOLIDATED FINANCIAL STATEMENTS

FOR THE YEAR ENDED 31 DECEMBER 2022

1 General information of the Group

Qingdao AInnovation Technology Group Co., Ltd. was incorporated in the People’s Republic of China (the “PRC”) on 6 February 2018 as a limited liability company. On 19 May 2021, the Company changed the type of enterprise from a limited liability company to a joint stock company. The address of the Company’s registered office is Room 501, Block A, Haier International Plaza, No. 939 Zhenwu Road, Economic Development Zone, Jimo District, Qingdao, Shandong, PRC.

The Company and its subsidiaries (collectively, the “Group”) conduct research and development of Artificial Intelligence technologies and provide Artificial Intelligence based software and hardware technology solutions services in the PRC.

The Company’s shares have been listed on the Main Board of The Stock Exchange of Hong Kong Limited since 27 January 2022.

These consolidated financial statements are presented in Renminbi (“RMB”) unless otherwise stated.

2 Summary of significant accounting policies

The principal accounting policies applied in the preparation of the consolidated financial statements are set out below. These policies have been consistently applied to all the years presented, unless otherwise stated.

2.1 Basis of preparation

The consolidated financial statements of the Group have been prepared in accordance with International Financial Reporting Standards (“IFRSs”) and disclosure requirements of the Hong Kong Companies Ordinance Cap. 622. The consolidated financial statements have been prepared under the historical cost basis, except for certain financial assets and liabilities that are measured at fair value.

The preparation of the consolidated financial statements in conformity with IFRSs requires the use of certain critical accounting estimates. It also requires management to exercise its judgment in the process of applying the Group’s accounting policies. The areas involving a higher degree of judgment or complexity, or areas where assumptions and estimates are significant to the consolidated financial statements are disclosed in the 2022 annual report.

– 42 –

New and amended standards adopted by the Group

A number of amended standards became applicable for the current reporting period. The Group did not have to change its accounting policies or make retrospective adjustments as a result of adopting these standards.

		Effective for annual periods
		beginning on or after
Amendments to IAS 16	Property, Plant and Equipment:	1 January 2022
	Proceeds before intended use
Amendments to IAS 37	Onerous Contracts	1 January 2022
	– Cost of Fulfilling a Contract
Amendments to IFRS 3	Reference to the Conceptual Framework	1 January 2022
AG 5 (Revised)	Merger Accounting for Common	1 January 2022
	Control Combinations
Annual Improvements to		1 January 2022
IFRS Standards 2018 – 2020

Certain new accounting standards, amendments to accounting standards and interpretations have been published that are not mandatory for 31 December 2022 reporting periods and have not been early adopted by the group. These standards, amendments or interpretations are not expected to have a material impact on the entity in the current or future reporting periods and on foreseeable future transactions.

The following new standards, new interpretations and amendments to standards and interpretations have been issued but are not effective for the financial year beginning on 1 January 2022 and have not been early adopted by the Group:

		Effective for annual periods
		beginning on or after
Amendments to IAS 1	Classification of liabilities as current or non-current	1 January 2023
IFRS 17	Insurance Contracts	1 January 2023
Amendments to IAS 1 and IFRS	Disclosure of Accounting Policy	1 January 2023
Practice Statement 2
Amendments to IAS 8	Definition of Accounting Estimate	1 January 2023
Amendments to IAS 12	Deferred Tax related to Assets and Liabilities arising	1 January 2023
	from a Single Transaction
Amendments to IFRS 10 and	Sale or contribution of assets between an investor and its	To be determined
IAS 28	associate or joint venture

– 43 –

The Group has already commenced an assessment of the impact of these new or revised standards and amendments, which are relevant to the Group’s operations. According to the preliminary assessment made by the directors, no significant impact on the financial performance and positions of the Group is expected when they become effective. The Group does not expect to adopt these new standards and amendments until their effective dates.

3 Segment information

The executive director of the Company has been identified as the chief operating decision-maker of the Group who reviews the Group’s internal reporting in order to assess performance of the Group on a regular basis and allocate resources.

The revenue of the Group is primarily derived from artificial intelligence products and services. Therefore, the Group regards that there is only one segment which is used to make strategic decisions.

No geographical segment information is presented as most of the revenue and operating losses of the Group are derived within the PRC and most of the operating assets of the Group are located in the PRC, which is considered as one geographic location with similar risks and returns.

Revenue from customers contributing over 10% of the total revenue of the Group in 2022 and 2021 is as follows:

	Year ended 31 December	Year ended 31 December
	2022	2021
	RMB’000	RMB’000
Customer A	*	87,545
*Less than 10%

No customer contributed over 10% of the total revenue of the Group for the year ended 31 December 2022.

– 44 –

4 Revenue

An analysis of revenue is as follows:

Point in time – Sales of products and solutions Over time – Sales of products and solutions – Services of data solutions	Year ended 31 December 2022 2021 RMB’000 RMB’000 1,458,327 846,411 63,902 — 35,414 14,757 1,557,643 861,168	Year ended 31 December 2022 2021 RMB’000 RMB’000 1,458,327 846,411 63,902 — 35,414 14,757 1,557,643 861,168
		861,168

5 Expenses by nature

Materials costs Subcontracting costs Employee benefit expenses Professional service and other consulting fees Depreciation of property, plant and equipment Listing expenses Depreciation of right-of-use assets Amortisation of intangible assets (Note 12) Marketing expenses Travelling expenses Auditors’ remuneration – audit services – non-audit services Rental and property management expenses Recruiting and training expenses Provision for write-down of inventories Other expenses	Year ended 31 December 2022 2021 RMB’000 RMB’000 746,662 422,807 528,950 327,763 469,322 590,937 32,555 10,814 31,310 24,223 26,457 51,500 21,877 9,260 19,341 700 18,324 8,321 16,395 6,950 4,500 3,000 1,577 228 2,806 7,452 1,467 3,505 1,126 — 36,439 19,515 1,959,108 1,486,975	Year ended 31 December 2022 2021 RMB’000 RMB’000 746,662 422,807 528,950 327,763 469,322 590,937 32,555 10,814 31,310 24,223 26,457 51,500 21,877 9,260 19,341 700 18,324 8,321 16,395 6,950 4,500 3,000 1,577 228 2,806 7,452 1,467 3,505 1,126 — 36,439 19,515 1,959,108 1,486,975
		1,486,975

– 45 –

6 Other income

	Year ended 31 December	Year ended 31 December
	2022	2021
	RMB’000	RMB’000
Government grants	56,009	28,067

Government grants provided to the Group mainly related to financial subsidy from the local government in the PRC.

7 Other losses, net

Foreign exchange gains/(losses) Donation Losses on disposal of property, plant and equipment Fair value losses on financial assets and liabilities at FVPL Interests received on financial assets at FVPL Liquidated damages Others	Year ended 31 December 2022 2021 RMB’000 RMB’000 5,046 (5,750) (284) (400) (334) (6) (8,716) — 632 4,883 (6,400) — 818 229 (9,238) (1,044)	Year ended 31 December 2022 2021 RMB’000 RMB’000 5,046 (5,750) (284) (400) (334) (6) (8,716) — 632 4,883 (6,400) — 818 229 (9,238) (1,044)
		(1,044)

– 46 –

8 Finance income/(cost)

	Year ended 31 December	Year ended 31 December
	2022	2021
	RMB’000	RMB’000
Finance income:
Interest income from bank deposits	38,708	24,022
Finance costs:
Interest expenses on lease liabilities	(4,227)	(1,220)
Interest expenses on bank borrowings	(2,462)	—
Interest expenses on convertible bonds	(1,400)	—
Finance costs of financial liabilities of redeemable shares	—	(34,877)
	(8,089)	(36,097)
Finance income/(cost), net	30,619	(12,075)

9 Income tax (credit)/expense

The amount of income tax charged to the consolidated statement of comprehensive income represents:

Current tax on profits for the year Deferred income tax Income tax (credit)/expense	Year ended 31 December 2022 2021 RMB’000 RMB’000 3,667 208 (4,179) — (512) 208	Year ended 31 December 2022 2021 RMB’000 RMB’000 3,667 208 (4,179) — (512) 208
		208

– 47 –

The difference between the actual income tax expense charged to the consolidated statement of comprehensive income and the amounts which would result from applying the enacted tax rates to loss before taxation can be reconciled as follows:

	Year ended 31 December	Year ended 31 December
	2022	2021
	RMB’000	RMB’000
Loss before taxation	(361,672)	(634,916)
Tax calculated at tax rates applicable to profits of the respective subsidiaries	(90,418)	(158,729)
Preferential tax of certain subsidiaries	32,452	14,283
Expenses not deductible for tax purposes	27,182	107,839
Super deductions from research and development expenditures	(18,157)	(19,282)
Utilisation of the tax losses unrecognized deferred income tax previously	(2,644)	(1,079)
Temporary difference for which no deferred tax asset was recognized	14,837	14,674
Tax losses for which no deferred tax asset was recognized	36,236	42,502
Income tax (credit)/expense	(512)	208

The Group’s subsidiaries in the PRC are subject to the PRC corporate income tax at a rate of 25% on estimated assessable profits.

A number of subsidiaries of the Group obtained the status as High and New Technology Enterprises in 2022. According to the tax incentives of the Corporate Income Tax Law of the People’s Republic of China (the “CIT Law”) for High New Tech Enterprises, these companies are subject to a reduced corporate income tax rate of 15% for three years commencing from the years when these companies are recognized as High New Tech Enterprises.

10 Dividends

The Board does not recommend a final dividend for the year ended 31 December 2022 (2021:Nil).

– 48 –

11 Loss per share

(a) Basic loss per share

Basic loss per share is calculated by dividing the loss attributable to the owners of the Company by the weighted average number of shares in issue or deemed to be in issue during the reporting periods. The weighted average number of ordinary shares deemed in issue before the conversion into a joint stock company in May 2021 was determined as assuming that:

(1) The Redeemable Shares were treated as treasury share before the cancellation of redeemable rights. As a result, the amount of 2,507,000 shares was deducted from the paid-in capital before the cancellation of redeemable rights for the purpose of calculating the number of ordinary shares deemed in issue;
(2) The remaining paid-in capital had been fully converted into number of ordinary shares deemed in issue at conversion ratio of 1:1 as upon transformation into joint stock company;
(3) The above number of ordinary shares had been further retrospectively adjusted for the effect of shares conversion from share premium into share capital at the conversion ratio of 1:17.

	Year ended 31 December	Year ended 31 December
	2022	2021
	RMB’000	RMB’000
Loss from continuing operation attributable to the owners of the Company	(363,042)	(636,599)
Weighted average number of ordinary shares in issue	550,722	444,903
Basic loss per share (RMB)	(0.66)	(1.43)

– 49 –

The calculation of weighted average number of ordinary shares in issue is as below:

	Year ended 31 December	Year ended 31 December
	2022	2021
	’000	’000
Weighted average number of shares in paid-in capital/share capital	555,995	27,224
Less: Weighted average number of Redeemable Shares in paid-in capital before
the cancellation of redeemable rights	—	(2,507)
Weighted average number of treasury shares	(5,273)	—
Weighted average number of shares in remaining paid-in capital/share capital	550,722	24,717
Weighted average number of ordinary shares in issue at the conversion ratio of 1:1	—	24,717
Add: Shares conversion from share premium into share capital
at the conversion ratio of 1:17	—	420,186
Weighted average number of ordinary shares in issue	550,722	444,903

(b) Diluted loss per share

As the Group incurred losses for the reporting periods, the potential ordinary shares were not included in the calculation of diluted loss per share as their inclusion would be anti-dilutive. Accordingly, diluted loss per share for the reporting periods are the same as basic loss per share for the respective year.

– 50 –

12 Intangible assets

Year ended 31 December 2022 Opening net book amount Additions Acquisition of subsidiaries Amortisation charge (Note 5) Net book amount As at 31 December 2022 Cost Accumulated amortisation Net book amount Year ended 31 December 2021 Opening net book amount Additions Amortisation charge (Note 5) Net book amount As at 31 December 2021 Cost Accumulated amortisation Net book amount	Software RMB’000 5,672 1,786 2,203 (5,049) 4,612 10,792 (6,180) 4,612 603 5,769 (700) 5,672 6,803 (1,131) 5,672	Customer Relationships RMB’000 — — 177,400 (9,911) 167,489 177,400 (9,911) 167,489 — — — — — — —	Technology RMB’000 — — 38,900 (4,381) 34,519 38,900 (4,381) 34,519 — — — — — — —	Total RMB’000 5,672 1,786 218,503 (19,341) 206,620 227,092 (20,472) 206,620 603 5,769 (700) 5,672 6,803 (1,131) 5,672

– 51 –

Amortisation of the intangible assets has been recognized as follows:

General and administrative expenses Research and development expenses Selling and distribution expenses Goodwill Cost additions on business combination	Year ended 31 December 2022 2021 RMB’000 RMB’000 669 247 8,761 453 9,911 — 19,341 700 Year ended 31 December 2022 2021 RMB’000 RMB’000 194,552 —

13 Goodwill

Impairment tests for CGUs containing goodwill

The goodwill arose from the following acquisitions during the year ended 31 December 2022: 1) the acquisition of Shanghai Higher Mechanical & Electrical Co., Ltd. and its subsidiaries (“Shanghai Higher”) on 31 May 2022; 2) the acquisition of Qingdao Aolipu Qizhi Intelligent Industrial Technology Co., Ltd. and its subsidiaries (“Qingdao Aolipu Qizhi”) on 31 May 2022; and 3) the acquisition of Huiyan Automation Technology (Shenzhen) Co.,LTD. (“Shenzhen Huiyan”) on 31 October 2022. The amount of goodwill resulting from these acquisitions are RMB96,377 thousand, RMB88,529 thousand and RMB9,646 thousand respectively. Shanghai Higher is mainly engaged in developing and delivering AI-based products and solutions for the manufacture industries in the PRC. Qingdao Aolipu Qizhi mainly provides integrated solutions for intelligent industrial automation systems in area of intelligent manufacturing. Shenzhen Huiyan is a system integrator providing hardware components development, agency services and softwares for manufacturing businesses.

– 52 –

The Group carries out annual impairment test on goodwill by comparing the recoverable amounts of CGU to the carrying amounts. Goodwill arising from the acquisition of Shanghai Higher, Qingdao Aolipu Qizhi and Shenzhen Huiyan was monitored separately and assessed as separate CGUs for the purpose of impairment testing.

The recoverable amounts of these CGUs are determined based on value-in-use calculations. These calculations use cash flow projections based on financial budgets approved by management generally covering a five-year period. Cash flows beyond the projection period are extrapolated using the estimated terminal growth rates stated below.

The key assumptions used for value-in-use calculations in 2022 were as follows:

Year ended 31 December 2022

		Qingdao
	Shanghai Higher	Aolipu Qizhi	Shenzhen Huiyan
Revenue (% annual growth rate)	7.9%~36.8%	7.7%~63.5%	3.0%~68.6%
Budgeted gross margin (%)	28.6%~31.0%	47.0%~48.2%	8.5%
Pre-tax discount rate (%)	14.0%	14.0%	14.0%

Management has determined the values assigned to each of the above key assumptions as follows:

Assumption	Approach used to determine values
Revenue	Average annual growth rate over the five-year forecast period;
	based on current industry trends, past performance and management’s
	expectations for the future.
Budgeted gross margin	Historic performance and management’s expectations for the future.
Pre-tax discount rate	Specific risks relating to the relevant segments and the country in which they operate.

– 53 –

There was no impairment required from the review on goodwill. The directors and management have considered and assessed reasonably possible changes for key assumptions and have not identified any reasonably possible change in assumptions would result in impairment provision.

Based on the headroom of the impairment assessments, management believed that any reasonably possible change in any of the key assumptions would not result in an impairment provision of goodwill.

14 Trade and notes receivables

	As at 31 December	As at 31 December
	2022	2021
	RMB’000	RMB’000
Accounts receivable	586,353	406,271
Less: Provision for impairment	(84,996)	(49,150)
	501,357	357,121
Notes receivables	33,065	4,879
	534,422	362,000

As at 31 December 2022 and 2021, notes receivables were bank and commercial notes receivables aged less than six months.

– 54 –

The majority of the Group’s receivables are with credit term mostly from 30 days to 180 days. At 31 December 2022 and 2021, the aging analysis of trade receivables based on the recognition date of the gross trade receivables at the respective reporting dates are as follows:

	As at 31	December
	2022	2021
	RMB’000	RMB’000
Accounts receivable
Less than 3 months	347,114	255,302
3 months to 6 months	73,457	54,881
6 months to 12 months	94,904	62,048
1 year to 2 years	44,997	22,979
2 years to 3 years	25,881	11,061
	586,353	406,271

The movements in provision for impairment of trade and notes receivables are as follows:

At the beginning of the year Acquisition of subsidiaries Provisions for trade receivables Written off as uncollectible Disposal of Subsidiaries At the end of the year	As at 31 December 2022 2021 RMB’000 RMB’000 49,150 25,144 28,807 — 34,301 24,006 (26,216) — (1,046) — 84,996 49,150	As at 31 December 2022 2021 RMB’000 RMB’000 49,150 25,144 28,807 — 34,301 24,006 (26,216) — (1,046) — 84,996 49,150
		49,150

For the trade receivables, the Group has assessed the expected credit losses by taking into account historical default rates, existing market conditions and forward-looking information. Based on the assessment, the creation and reversal for impaired receivables have been included in the net impairment losses on financial assets. Amounts charged to allowance account are written off when there is no expectation of receiving the receivables.

– 55 –

The carrying amounts of the Group’s trade and notes receivables, excluding provision for impairment, are denominated in the following currencies:

RMB USD EUR 15 Prepayments and other receivables Other receivables -Deposits for share repurchase -Staff advances -Deposits -Others Other receivables, gross Provision for impairment Other receivables, net Prepayments to vendors Recoverable value–added tax (“VAT”) Recoverable income tax	As at 31 December 2022 2021 RMB’000 RMB’000 607,634 411,150 11,127 — 657 — 619,418 411,150 As at 31 December 2022 2021 RMB’000 RMB’000 16,296 — 1,749 366 8,371 4,663 11,546 4,962 37,962 9,991 (2,305) — 35,657 9,991 109,322 22,505 45,424 18,997 536 2,539 190,939 54,032	As at 31 December 2022 2021 RMB’000 RMB’000 607,634 411,150 11,127 — 657 — 619,418 411,150 As at 31 December 2022 2021 RMB’000 RMB’000 16,296 — 1,749 366 8,371 4,663 11,546 4,962 37,962 9,991 (2,305) — 35,657 9,991 109,322 22,505 45,424 18,997 536 2,539 190,939 54,032
		9,991 —
		9,991
		22,505 18,997 2,539
		54,032

– 56 –

The carrying amounts of the Group’s other receivable, excluding provision for impairment, are denominated in the following currencies:

	As at 31	December
	2022	2021
	RMB’000	RMB’000
RMB	21,666	9,991
HKD	16,296	—
	37,962	9,991

The carrying amounts of other receivables approximate their fair values.

16 Financial assets at fair value through profit or loss

Investment fund(a) Wealth management products(b) Listed equity securities(c) Other financial investment instrument(d)	As at 31 December 2022 2021 RMB’000 RMB’000 69,260 — 14,125 — 2,920 — 69,715 — 156,020 —	As at 31 December 2022 2021 RMB’000 RMB’000 69,260 — 14,125 — 2,920 — 69,715 — 156,020 —
		—

(a) In April 2022, the Company made investment in a private equity fund, with amount of RMB73,150 thousand. The private equity fund represented assets measured at fair value, and the fair value was determined using valuation model for which not all inputs are observable and is therefore within level 3 of the fair value hierarchy. Changes in fair value of the private equity fund was recognized in other loss, net.
(b) The wealth management products represented the financial products issued by public monetary funds. The public monetary fund mainly invests in financial instruments permitted by laws and regulations, including cash, short-term bank deposits, bond repurchase, bank bills and other money market instruments with good liquidity.

– 57 –

(c) The listed equity securities are listed stocks purchased in the public secondary market. The fair values of the listed securities are determined based on the closing price quoted in active markets.
(d) In June 2022, the Company invested about RMB 71,890 thousand to purchase a total return swaps financial product, swapped out fixed interest, and exchanged in the income or loss of the equivalent shares of a listed stock. The product is accounted for assets measured at fair value, and the fair value was determined using the observable inputs, and is therefore within level 2 of the fair value hierarchy.

17 Trade and notes payables

	As at 31	December
	2022	2021
	RMB’000	RMB’000
Accounts payable	275,700	222,086
Notes payable	4,624	5,633
	280,324	227,719

As at 31 December 2022 and 2021, the aging analyses of the trade and notes payables based on transaction date were as follows:

Within 3 months Between 3 months and 6 months Between 6 months and 1 year Between 1 year and 2 years Between 2 years and 3 years	As at 31 December 2022 2021 RMB’000 RMB’000 206,126 161,929 25,872 34,947 24,005 28,144 18,846 2,465 5,475 234 280,324 227,719	As at 31 December 2022 2021 RMB’000 RMB’000 206,126 161,929 25,872 34,947 24,005 28,144 18,846 2,465 5,475 234 280,324 227,719
		227,719

The carrying amounts of trade and notes payables approximate their fair values.

– 58 –

18 Other payables and accruals

	As at 31	December
	2022	2021
	RMB’000	RMB’000
Accruals and other payables	51,164	39,875
Payroll and welfare payables	80,917	38,765
Interest payable on convertible bonds	7,733	—
Warranty	3,838	—
Other taxes payable	18,723	5,233
	162,375	83,873

The carrying amounts of other payables and accruals approximate their fair values.

19 Financial liabilities at fair value through profit or loss

Contingent considerations (a) Convertible bond (b)	As at 31 December 2022 2021 RMB’000 RMB’000 117,606 — 29,931 — 147,537 —	As at 31 December 2022 2021 RMB’000 RMB’000 117,606 — 29,931 — 147,537 —
		—

(a) In May 2022, the Company entered into two share transfer agreements with shareholders of two companies to acquire an aggregate 51% interests in each of the two companies with fixed considerations and contingent considerations which would be adjusted according to the performance commitment. The contingent considerations represented liabilities measured at fair value, and the fair value was determined using valuation model for which not all inputs are observable and is therefore within level 3 of the fair value hierarchy. The contingent considerations at date of acquisition in May 2022 amounted to RMB109,416 thousand and it was increased to RMB117,606 thousand as at 31 December 2022.

– 59 –

(b) Jiangsu Epsa Automation Technology Co., Ltd. (“Jiangsu Epsa”), a subsidiary newly acquired by the Group in May 2022, entered into an investment agreement with an investor for the issuance of convertible bonds with principal amount of RMB30,000 thousand in October 2019. According to the terms of the investment agreement, during the 48 months since the date of issuance, at the investor’s option, the conversion right was exercisable on the investor’s demand in exchange for shares of Jiangsu Epsa, and the investor has the right to request Jiangsu Epsa to redeem the convertible bonds or shares if converted, with 100% of its issue price plus 8% annual simple interest rate.

The conversion price is based on negotiation between Jiangsu Epsa and the investor. The Group designate the entire hybrid contract at fair value through profit or loss and recognised financial liabilities of RMB29,882 thousand at date of acquisition in May 2022. As at 31 December 2022, the total fair value of the convertible bonds amounted to approximately RMB29,931 thousand and the changes in fair value of RMB49 thousand was recognized as loss in the consolidated statements of comprehensive loss in 2022.

– 60 –

DEFINITIONS

“Audit Committee”

audit committee of the Board

“Board” or “Board of Directors” “China” or “PRC” “Company” or “our Company” or “the Company” or “AInnovation”

the board of directors of our Company

the People’s Republic of China, but for the purpose of this announcement only, do not apply to Hong Kong, the Special Administrative Region of Macau and Taiwan

Qingdao AInnovation Technology Group Co., Ltd (青島創新奇智科技集團股份有限公司), which was established with limited liabilities under the laws of the PRC on 6 February 2018 and converted into a joint stock limited company on 19 May 2021, whose H shares are listed on the Main Board of Stock Exchange on 27 January 2022 (stock code: 2121)

“Director(s)” the director(s) of our Company “Group” or “our Group” or our Company and our subsidiaries

“Group” or “our Group” or our Company and our subsidiaries “we” or “us” “H Share(s)” overseas-listed shares in the share capital of our Company, with a nominal value of RMB1.00 each, which are to be traded in Hong Kong dollars and are listed and traded on the Stock Exchange “HK$” or “Hong Kong Dollars” Hong Kong dollars, the lawful currency of Hong Kong “Hong Kong” or “HK” the Hong Kong Special Administrative Region of the PRC “Hong Kong Stock Exchange” The Stock Exchange of Hong Kong Limited or “Stock Exchange”

– 61 –

“Listing Date” the date on which the H Shares are listed on the Stock Exchange and from which dealings in the Shares are permitted to commence on the Hong Kong Stock Exchange, i.e. 27 January 2022 “Listing Rules” The Rules Governing the Listing of Securities on The Stock Exchange of Hong Kong Limited, as amended, supplemented or otherwise modified from time to time “RMB” or “Renminbi” the lawful currency of the PRC “Share(s)” H share(s) “Shareholder(s)” holder(s) of the Shares “Supervisor(s)” the supervisor(s) of our Company “%” per cent

By Order of the Board QINGDAO AINNOVATION TECHNOLOGY GROUP CO., LTD 青島創新奇智科技集團股份有限公司 Xu Hui Executive Director and Chief Executive Officer

Hong Kong, 31 March 2023

As at the date of this announcement, the Board of the Company comprises Mr. Xu Hui as executive Director; Dr. Kai-Fu Lee and Mr. Wang Hua and Mr. Wang Jinqiao as non-executive Directors; Mr. Xie Deren, Ms. Ko Wing Yan Samantha and Ms. Jin Keyu as independent non-executive Directors.

For identification purposes only

– 62 –

AI assistant

AInnovation Technology Group Co., Ltd — Annual Report 2022

50382_rns_2023-03-31_58ae91bf-0fd0-498e-b6d9-1a30fbc8dde8.pdf

QINGDAO AINNOVATION TECHNOLOGY GROUP CO., LTD[*] 青島創新奇智科技集團股份有限公司

ANNUAL RESULTS ANNOUNCEMENT FOR THE YEAR ENDED 31 DECEMBER 2022

FINANCIAL SUMMARY

Period from

KA base revenue value

Period from

6 February

Revenue-By Customer Type

Period from

6 February

Revenue-By Industry Verticals

Period from

BUSINESS OVERVIEW

Part I: Business Review

Record high patent filing and excellent domestic level of intellectual property management

Continuous development of MMOC artificial intelligence technology platform

MMOC Platform "3 Phase" Strategy

Strengthen perception algorithm R&D and reserve AIGC capability

Continuous enrichment of AI products and solutions

Part II: Future Outlook

Continue to promote MMOC platform R&D and technological innovation

MMOC Platform 2023 R&D Strategy

Strengthen the combination of AIGC and industry, and apply industrial pre-training large models in vertical scenarios

Continue to enrich AI products and solutions

MANAGEMENT DISCUSSION AND ANALYSIS

OVERVIEW

REVENUE

COST OF SALES

GROSS PROFIT AND GROSS MARGIN

SELLING AND DISTRIBUTION EXPENSES

GENERAL AND ADMINISTRATIVE EXPENSES

RESEARCH AND DEVELOPMENT EXPENSES

NET IMPAIRMENT LOSSES ON FINANCIAL ASSETS

OTHER INCOME

OTHER LOSSES, NET

OPERATING LOSS

FINANCE INCOME

FINANCE COSTS

LOSS FOR THE YEAR

NON-IFRS MEASURES

Adjusted Net Loss

LIQUIDITY AND CAPITAL RESOURCES

Cash and Cash Equivalents

Gearing Ratio

MATERIAL ACQUISITIONS AND DISPOSALS

Share Transfer Agreement I

Date:

Contracting Parties:

Xiyao ”).

Subject Matters and Contract Consideration:

Share Transfer Agreement II

Date:

Contracting Parties:

Subject Matters and Contract Consideration:

Disclosure made pursuant to Rule 14.36B of the Listing Rules

1. Discloseable transaction in relation to the acquisition of 51% equity interest in Target Company I

Notes:

2. Discloseable transaction in relation to the acquisition of 51% equity interest in Target Company II

Notes:

FUTURE PLANS FOR MATERIAL INVESTMENTS OR CAPITAL ASSET

FOREIGN EXCHANGE EXPOSURE

PLEDGE OF ASSETS

BORROWINGS

CONTINGENT LIABILITIES

SUBSEQUENT EVENT

OTHER INFORMATION

Dividend

Purchase, Sale or Redemption of the Company’s Listed Securities

Corporate Governance Practices

Model Code for Securities Transactions by Directors, Supervisors and Employees

Scope of Work of the Auditor

Audit Committee

PUBLICATION OF THE ANNUAL RESULTS AND ANNUAL REPORT

FINANCIAL STATEMENTS

CONSOLIDATED STATEMENT OF COMPREHENSIVE INCOME

CONSOLIDATED STATEMENT OF COMPREHENSIVE INCOME (CONTINUED)

CONSOLIDATED BALANCE SHEET

AInnovation Technology Group Co., Ltd Annual Report 2022

**QINGDAO AINNOVATION TECHNOLOGY GROUP CO., LTD[*] 青島創新奇智科技集團股份有限公司**