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【2021 Solutions】 GoodLinker Cloud of War Room: The best helper for digital transformation of SMEs

The first difficulty that small and medium enterprise (SME) owners face in the digital transformation process is the purchase of hardware and software equipment, such as sensors and cloud servers, which requires considerable investment. In addition, the equipment will require dedicated personnel for maintenance and management after purchase, which has discouraged many business owners from undertaking digital transformation.

GoodLinker targets this pain point of SMEs when going through transformation and is committed to helping every factory benefit from smart manufacturing. It helps SMEs undergo digital transformation at low cost and without the need for professional talents. Founded in 2018, GoodLinker is a startup that focuses on AIoT technology. The R&D team used international public cloud service platforms to develop the "GoodLinker Cloud of War Room" SaaS subscription service, which can quickly visualize data on the operations of production line machinery, helping companies monitor the status of factory production lines at anytime and anywhere.

Data is the foundation of AI, and carbon reduction requires an inventory to be taken first. The key to the transformation of these enterprises is the digitization of production lines and data collection infrastructure. Digital transformation not only contributes to the success of factories, but also facilitates the upgrading of the overall manufacturing industry chain.

Targeting SMEs with 200 employees

Hui-Yi Feng, founder and president of GoodLinker, specializes in electric machinery. Before he founded the company, he worked for a well-known international mobile device OEM company and is familiar with the operation of Industry 4.0. He found that companies implementing Industry 4.0 were mostly large enterprises with more than 500 employees. Meanwhile, 97% of Taiwan's SMEs need easy-to-use cloud monitoring tools to take the first step in digital operations. Therefore, Hui-Yi Feng founded GoodLinker after returning to Taiwan in 2018, and offered smart manufacturing solutions specifically for SMEs in traditional industries with less than 200 employees.

Cloud of War Room Operations

GoodLinker uses the concept of a cloud platform to build module tools and import them into the war room. Enterprises only need to use smart manufacturing set-top boxes (BCS-M100) to save labor and maintenance costs. They can start using the "GoodLinker Cloud of War Room" without needing to set up their own hosts and maintain computer rooms. Companies can overview the operating status of production lines in their factories through the mobile app or webpage. If there is an abnormal situation, the Cloud of War Room will actively issue a warning to remind the person in charge to take emergency response measures.

This improves quality and management efficiency. There are web and mobile version service interfaces to achieve paperless, digital, and visual production data. Enterprises do not need to build their own computer rooms and maintenance teams, which lowers the threshold for realizing IoT, ESG energy consumption monitoring, and carbon inventory applications.

At present, more than 80% of GoodLinker's customer base are SMEs with less than 50 employees. The company mainly communicates with second generation business owners or factory directors, covering manufacturing, logistics, food processing, and high-density farming industries. The companies all achieved good results after using Cloud of War Room.

For example, farmers who raise tens of thousands of grass shrimps in Tainan needed to manually inspect the water temperature, water quality, and oxygen content in the past. Using GoodLinker's Cloud of War Room service, farmers only need handle matters when they receive a signal of abnormal water quality on their mobile app, and no longer need to monitor the shrimp pond day and night.

Another example is a well-known pork ball manufacturer in Hsinchu. The food processing process must be carried out in a low-temperature sterile environment, and the temperature of meat products is strictly monitored. The Cloud of War Room can provide non-contact temperature monitoring to ensure that meat is fresh and contamination free, while strictly monitoring whether on-site employees are following standard operating procedures (SOPs). The data can also provide production history records for supply chain quality control required by distributors, in order to ensure stable quality and peace of mind for consumers.

Factory directors only need to use the mobile app or website to gain an overview of the operating status of production lines through the Cloud of War Room.

Participation in the AI+ New Talent Selection: Shortens development time

The core technology of GoodLinker is smart manufacturing set-top boxes. The company has participated in the "AI+ New Talent Selection" of the Ministry of Economic Affairs Industrial Development Bureau's AI program for two consecutive years, and has won the favor of many major industrial computer edge computing hardware manufacturers. It rapidly developed products with its technology through technical cooperation, shortening development time, launching software and hardware integrating AIoT services, and applying AI to more efficient industrial data collection from production lines.

▲The core technology of GoodLinker is the smart manufacturing set-top box. At the same time, it will deepen technologies and optimize products and services.

Future development direction

At present, in addition to being a strategic partner of global public cloud service providers, GoodLinker has also become a smart manufacturing service partner of telecom carriers in Taiwan, jointly providing smart factory services through Cloud of War Room. In terms of the company's future business strategy, it will provide more data value-added services in the short term and introduce GenAI technology to further improve internal management efficiency and data interpretation, so as to gain insights into feasible strategies for users. In the medium and long term, the company will integrate more upstream and downstream suppliers to create a "smart manufacturing service ecosystem" to further help SMEs solve their pain points, successfully upgrade, and achieve a resilient green supply chain.

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【解決方案】洞悉消費者行為 智能演譯運用AI協助餐飲業順利轉型
Insight into consumer behavior and intelligent interpretation using AI to assist the catering industry with smooth transformation

In May 2021, due to the local COVID-19 outbreak, a ban on internal use was adopted, making the catering industry feel like it has entered a cold winter, with business bleak and operations facing difficulties However, there are also catering companies that have turned the crisis into an opportunity and actively carried out digital transformation, introducing online ordering and delivery platform systems, establishing customer membership systems, etc, to effectively reduce inventory and increase sales Intelligent Interpretation, a new start-up company established just one year ago, acts as a transformation consultant for the catering and retail industry, collecting, connecting and analyzing consumer behavior data to provide the best solutions for the cateringretail industry Li Qihan, the founder of Intelligent Interpretation, is good at online marketing and website construction As AI technology continues to evolve, he graduated from the Northern Phase II Manager Class of Taiwan Artificial Intelligence School AIA and was impressed by the large number of website sales Data and marketing analysis data can help companies improve their competitiveness and reduce operating costs Therefore, we established an intelligent interpretation company with Taiwan Artificial Intelligence School alumni, hoping to use member information to start collecting more first-party data to help customers build customer vision Analyze the data and identify relevant sales opportunities Targeting the catering and retail industries, intelligent interpretation helps stores use AI to transform "There are many small and medium-sized restaurants in Taiwan We hope to help these small and medium-sized restaurants use simple cloud services and social tools, such as Line, to start collecting and establishing member information systems and collect relevant information Consumption data is used to establish behavioral models of different consumers" Li Qihan went on to say that the catering and retail industries will be targeted at the initial stage, and different consumption behavior analyzes will be used to help stores further increase the frequency of customers visiting the store and the frequency of dining or purchasing, and reduce the use of ingredients Preparation costs The main features of the AI service of intelligent interpretation Affected by the ongoing epidemic, which has severely impacted the performance of physical stores, intelligent interpretation also assists physical stores in establishing e-commerce websites or shopping malls, combining physical and virtual consumption data to provide 360-degree OMO consumers Analysis, and can send marketing messages to different consumers, reducing the large-scale and indiscriminate casting of traditional marketing methods that cause customers to blacklist merchants or block lines, and also increase consumers' willingness to click and purchase Will Li Qihan pointed out that the AI service of intelligent interpretation has the following characteristics 1 Use LINE combined with membership system 2 Use QR Code to replace membership card 3 Provide LINE online orderingreservation 4 Use AI to analyze consumers’ personal preferences 5 Send coupons based on consumer behavior and preferences Using Line ordering information, you can understand consumer behavior such as consumer type, taste, time period, ordering frequency, etc, find consumers of the same group, and conduct summary analysis, which is important for one-to-one customized marketing Reference Li Qihan emphasized that the cost of digital marketing at this stage is very high If there is no classification and grouping after acquiring customers, preferential information will be distributed randomly and easily blocked by consumers The conversion rate will become lower and lower, and the marketing budget invested previously will be in vain AI combines the advantages of MarTech to provide exclusive customized services Although Intelligent Interpretation is a new startup that has been established for nearly a year, in terms of the company's future development strategy, Li Qihan hopes to use MarTech combined with the advantages of AI to first assist the catering and retail industries that are currently most in need of digital transformation Quickly enter the first stage of digital transformation, establish member information and collect consumer data, and then assist these companies to enter the second stage of digital transformation, analyze and use these consumer data, and provide exclusive customized services Li Qihan said that Taiwan’s MarTech market still has considerable room for development Most companies think that advertising on the Internet is the so-called MarTech, or that combining website data with advertising conversion rates and looking at the GA report Google Analytics every day is the so-called MarTech However, he believes that the above situation is only It stops at the collection and analysis of marketing data and is not integrated into the corporate sales and management levels In fact, after the data is collected, it still needs to be integrated, analyzed, and applied according to individual business scenarios This is the real MarTech application method Li Qihan, founder of Intelligent Interpretation, shared his smart retail experience at the AIGO forum As for most companies that believe that as long as they have data, AI algorithm analysis can solve all problems, Li Qihan suggested that companies should have a correct concept of data First, it does not have to be big data AI algorithms can also work with small data Great effect 2 Data is accumulated year by year To collect information, you need to understand the purpose and needs After collecting data, you need to find out its correlation That is to say, first define the use situation and the problem you want to solve, collect data, Only by analyzing data and using machine learning to identify undiscovered sales opportunities can we start to provide marketing application suggestions "The key to the success of using technology for digital transformation lies not in technical issues, but in concepts AI is not a magic pill that will take effect after taking it AI is more like a health food and must be taken continuously to help adjust the corporate body" This is Li Qihan realization He also mentioned that there is an 8020 rule in customer management How to define the 20 customer group What is the definition of VIP customer What issues does the company want to analyze What data should be disassembled It is necessary to peel off the cocoons layer by layer and clarify the above issues one by one This is the "basic project of the sewer" If the foundation is stable, there will be no problem in building a few more floors on top The Industrial Bureau of the Ministry of Economic Affairs’ AI problem-solving competition creates a win-win situation for enterprises and innovations Intelligent Interpretation has assisted the internationally renowned catering chain Din Tai Fung to participate in the AIGO "Problem Solving" competition of the Industrial Bureau of the Ministry of Economic Affairs It understands that almost all catering industries have problems with how much to prepare Many times, when there are too many guests, there is insufficient preparation There are fewer customers, resulting in a waste of ingredients Therefore, it is very important for restaurants to predict the number of customers every day Intelligent interpretation suggestions can be based on weather, store location, and special holidays such as Valentine's Day, Mother's Day, etc through AI , special time parents’ birthday, wedding anniversary and other data correlation analysis, the estimated number of guests is expected to increase the accuracy by more than 80, effectively using AI to solve the problems of catering operators Restaurant Consumer Service Flow Chart Li Qihan pointed out that "industry problem solving, new innovation problem solving" can help enterprises and AI startups find common goals, and also solve the dilemma of new startups not getting usable data, and provide identification through matchmaking on the enterprise side Based on the data, AI startups can put algorithms into practical application, and enterprises can also get solutions for digital transformation, creating a win-win situation After the epidemic, digital transformation is related to the life and death of enterprises How should the cateringretail industry choose AI companies and introduce them Li Qihan, who currently serves as an AIGO smart retail coach for the Industrial Bureau of the Ministry of Economic Affairs and a number of AI consultants, said frankly that if data analysis does not have a certain degree of understanding of AI and practical implementation experience, there may be a high chance of failure in project execution In the retail industry, when it comes to choosing an AI project company, it is best to choose a company that has actually introduced AI projects or has experience in operating e-commerce The recommended principles and steps for introducing AI into the cateringretail industry are If the problem the company asks is too big, it needs to continue to dismantle it Because different problems naturally require different ways of collecting data, with the help of consultants step by step After dismantling, use the data collected according to the usage situation to analyze, and you will naturally get the answer to the problem you want to solve After you find a certain accuracy, you can then use transfer learning to solve similar problems one by one Looking to the future, Intelligent Interpretation hopes to become the number one AI company in Taiwan in the catering and retail industries, using simple and practical methods to help the catering and retail industries implement AI and improve the competitiveness of Taiwan's industry「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】滴水不漏的智慧工安巡檢 鑫蘊林科Linker Vision的影像分析AI平台 創造巡檢時間從100分鐘降至3秒新紀錄
Watertight smart industrial safety inspection Linker Vision’s image analysis AI platform sets a new record of inspection time reduced from 100 minutes to 3 seconds

With the rise of smart manufacturing, there is a demand for industrial safety inspections in high-risk industries such as chemical, energy, and electrical industries Take pipeline inspection in the chemical industry as an example It relies heavily on manual regular inspection and monitoring, and lacks intelligent monitoring by a professional AI team This is not only time-consuming and labor-intensive, but may also cause accidental risks to employees in various industrial safety environments The image analysis AI platform developed by Xinyun Linke not only improves employee personal safety and reduces risk factors, but also significantly reduces the time for human visual inspection of pipeline abnormalities from an average of 100 minutes to 3 seconds Paul Shieh, founder and chairman of Linker Vision Co, Ltd Linker Vision, said, "The overall technological development and progress in the United States comes from entrepreneurship Linker Vision's original intention to start a business in Taiwan has been I hope that through my past experience in entrepreneurship in the United States, I can introduce the American entrepreneurial spirit and culture to Taiwan's budding entrepreneurial fertile ground and truly implement it "American entrepreneurial culture encourages employees to value ownership and emphasizes that employees regard themselves as owners of the company Be a part of the company, with a work attitude and spirit that would be better than mine The company's achievements are your own achievements, breaking the original employer-employee relationship The company will reward outstanding employees with stocks, share the glory together, and establish a partnership with employees Partnership On the other hand, Taiwan still has room for efforts in entrepreneurial culture and management, and it retains the traditional thinking of employers and employees It is expected that Xinyun Linke's establishment of American entrepreneurial culture and values in Taiwan will serve as a starting point to drive more domestic new companies to follow suit, and then Only by upgrading the business constitution of new software AI entrepreneurs can they break out of the cocoon and go global Facing the market, most international players focus on developing AI models and algorithms They are less willing to invest in data-centered Data-Centric AI services They think that processing large amounts of 2D or 3D data is quite time-consuming It’s also energy-consuming Seeing the gap in AI technology and encouraged by Microsoft, Xinyunlinke decided to fully invest in Data-Centric's AI technology layout and deep roots many years ago, and specialize in technical energy in data processing, filtering and accuracy Therefore, Become an important partnership with Microsoft for AI technology supply In addition, due to the gap in industrial demand, domestic large factories, whose strength is chemical manufacturing, still rely heavily on manpower for inspection of pipelines in the factory, which is time-consuming and labor-intensive However, in order to cater to the AI industry, the owner reorganized the IT department originally engaged in database management and control into an AI team However, due to the owner's lack of professional experience in AI software technology, AI models and related domain know-how, the owner introduced AI implementation Industrial safety monitoring in the chemical industry is even more challenging The world's first AI automatic labeling technology surpasses manual labeling and can visually identify objects with an accuracy of over 95 In terms of AI technology power, Xinyunlinke has launched the world's first dual-core innovative technology of automatic labeling Auto-labeling and automatic machine learning to create an efficient and stable image analysis AI platform to provide customers with the best Advanced and complete AI solutions In terms of automatic annotation, this AI technology can overcome the most difficult challenge in deep learning, which is to provide customers with the highest quality training data Taking self-driving cars as an example, how to enable one self-driving car to effectively identify another car is the importance of labeling In the past labeling methods, we first needed to collect digital images of millions of vehicles, roads, signs, and pedestrians, and spent a lot of manpower Manually labeling one image at a time was time-consuming, labor-intensive, high in labor cost, and inefficient Through automatic labeling AI technology, combined with automatic machine learning to automatically label digital images, AI can exclude human error labeling and then throw the correct data into the vehicle's brain for vehicle identification Compared with manual labeling accuracy of only 60, the accuracy of automatically labeling and identifying objects with AI can be as high as over 95 It can also reduce manual labeling time by more than 80 and save at least 80 of labor costs AI automatically marks AI behavior recognition for high-altitude operations In the automatic machine learning part, Xinyunlinke established an AI visual model with continuous learning capabilities to adapt to data changes By optimizing the overall development process, from AI data ingestion and filtering Data Selection to AI labeling AI Labeling , model training and verification, deployment and monitoring, so that AI computer vision can continue to learn more quickly and easily Automatic machine learning can currently be applied to different business cases such as object identification and counting, personnel entry and exit security detection, product defect detection, people flow identification, product shortages on shelves, etc Looking at domestic companies such as TSMC, Formosa Plastics and Hon Hai towards intelligent AI management and purchasing a large number of cameras to meet the image recognition needs of industrial safety surveillance, coupled with the introduction caused by the unfamiliarity of existing customer organizations with AI applications Thresholds and preliminary preparations for image recognition include complicated workflows such as data screening and annotation To this end, Xinyunlinke has been committed to accelerating the development of AI computer vision applications in recent years, providing client-to-end services, and can flexibly deploy according to customer needs Complete automated AI solution services in the cloud, on-premises, or cloud on-premises Xie Yuanbao said that the AI automation technology process provides data selection Data Selection AI technology through domain-type pictures given by customers, helping customers automatically filter out precise such as 10,000 transactions from a large amount of data such as 1 million transactions Data, and by using the AI algorithm technology of Auto-Labeling to replace manual labeling, it can effectively save customers a lot of labor costs and achieve efficient data labeling processing In addition, the AI technology of automated machine learning can help clients customize automatic AI model training or repeated training when the factory environment changes, providing more accurate AI models and allowing customers to operate autonomously Through the above-mentioned key features and advantages of the automated AI technology provided by Xinyunlinke, we believe that it can definitely meet the needs of customers for an automated end-to-end AI independent learning platform, and at the same time, it can significantly save customers the cost of AI team establishment In terms of technological competitiveness, in addition to providing the chemical industry with AI image analysis applications in smart industrial safety, Xie Yuanbao said that Xinyunlinke can also extend the process application of automatic annotation and automated machine learning to different industrial landing services, such as Various fields such as self-driving cars, smart warehousing self-propelled robots and self-driving buses in future smart cities are all in line with the spirit of automated mobility of Mobility as a Service We look forward to the role played by Xinyunlinke The process of image annotation in different industries accelerates the efficiency of developing image recognition services in different fields We believe that by providing client-to-end AI solutions and a complete set of automated AI image analysis pre-operation processes from Data Selection AI technology, Auto-Labeling AI technology, and automated machine learning AI technology, we can greatly satisfy our customers The demand for AI autonomous learning platform Image analysis AI platform sets a new record for smart industrial safety inspections from 100 minutes to 3 seconds Seeing the high demand for industrial safety supervision in high-risk industries such as the chemical industry in recent years, Xinyunlinke launched the "Vision AI Platform", which uses AI image recognition technology Its main functions include real-time AI streaming It has four major functions detection, event notification, defining customer-specific AI models and continuous learning In the real-time AI stream detection part, the Vision AI system can use the customer's factory camera combined with the AI module to perform real-time stream detection of AI image events It can help customers manage various operations and factory environments and keep track of them anytime and anywhere Various work situations in terms of event notification, the Vision AI platform can provide a web version or APP or LINE instant messaging software to provide customers with video records of the events at that time, so that the team does not miss any events, maintains daily production capacity and reduces accidents in defining customers In terms of exclusive AI models, a variety of basic AI models are available, including 8 detection scenarios electronic fences, personal safety equipment, construction safety equipment, construction operations, personnel counting, screen availability, smoke detection, pipeline corrosion and damage , illegal stacking for use in different industries, customers can build exclusive AI models without spending time writing programs in the continuous learning part, the Vision AI system can provide customers with the performance and accuracy of AI models, and have the ability to adapt as the environment changes Continuous learning ability Vision AI has a simple user interface and intuitive operation For cross-field industries, this platform has automated and flexible AI capabilities Customers can build self-defined AI models without spending time writing programs, and Vision AI gives AI models the ability to continuously learn and improve, allowing customers to save the labor cost of building an AI team In addition, the platform can significantly reduce the manpower allocation for routine inspections required for operational safety management, improve employee safety in the working environment, and reduce on-site accidentsrisk factors at various work sites In the platform operation mode, customers can reduce the risk of manual monitoring operations through remote operations, ensuring normal work operations and uninterrupted production operations They can also review high-risk operating situations and collect data to assist in the planning and correction of operating processes In addition, in order to ensure that customers comply with government regulations, Vision AI can help customers control the equipment and safety regulations required in different workplaces at any time through the platform's event notification and management detection The image analysis AI platform is used in cross-field AI image recognition technology Generally, for industrial safety inspections in the chemical industry, most rely on the naked eye of personnel to regularly inspect pipeline abnormalities It takes an average of 100 minutes to scan an area each time, which is time-consuming and laborious, and the pipeline location is difficult to visually observe, which may cause Employees are exposed to accidental risks in various work safety environments In order to reduce the pain points of industrial safety inspections in the chemical industry, Xinyunlinke assists well-known domestic chemical industry players by using an automated image analysis AI platform, combined with customized virtual electronic fences, and using in-plant cameras to configure AI pipeline leakage modules , the AI automatic inspection method can effectively reduce the abnormal detection time to less than 3 seconds In addition, cameras deployed in the factory can automatically record inspection schedules to achieve full-time monitoring, allowing customers to instantly discover and fully control pipelines, minimizing risks In addition, the automated image analysis AI platform can help customers apply fire warnings in factories It is conservatively estimated that the return on investment can be less than 9 months to pay back the investment The longer the platform is used, the higher the cost-effectiveness Build an automatic learning image analysis AI platform for Mobility as a Service in various fields Xie Yuanbao observed that the biggest challenge facing the entrepreneurial culture of software companies in Taiwan is that young new entrepreneurs or employees in Taiwan do not understand the entrepreneurial model and lack the awareness to regard themselves as part of the company owners This has caused It is a pity that your future is unclear or you have a past-experience mentality that prevents you from staying competent in a new start-up company for a long time I believe that the essence of true entrepreneurship lies in every employee rolling up their sleeves and working hard, so that they can truly enjoy the fruits of entrepreneurial profits Otherwise, for young entrepreneurs or employees who often change tracks, it will be like a rolling stone that gathers no moss , I am unable to take a deep root on the road of entrepreneurship, and I lose my ability to solidly accumulate financial independence Regarding the business promotion challenges of Xinyun Linke, Xie Yuanbao said with emotion that because the Taiwan market does not have a deep understanding of AI software applications, it relies more on open source AI visual analysis or machine learning and other resources on the market, but in fact These AI technology resources are limited in their ability to support customers' AI model needs, resulting in uneven quality of AI visual analysis software in the market Therefore, the impact is more indirect on Xinyunlinke's ability to truly provide customers with professional and data-centric AI image analysis services, and it also reduces the company's original business value in customer reference In terms of technical research and development challenges, the visual analysis AI platform cannot rely solely on AI model experts It must gather talents in various fields such as cloud, machine learning, data science, front-end and back-end and other professional team combinations to make the platform operate successfully Xie Yuanbao said that he believes that only through the automatic learning of the visual analysis AI platform, automatic fast and accurate data processing capabilities, and providing customers with complete AI solution services in the cloud, cloud ground Hybrid to pure ground, can we truly Convince customers and stand out from the competition Looking to the future, Xie Yuanbao hopes that Xinyunlin Technology can build an image analysis AI platform for Mobility as a Service to automatically learn in various fields such as self-driving cars, smart warehousing robots, and unmanned buses in smart cities At the same time, I am also grateful to the support of the Industrial Bureau of the Ministry of Economic Affairs for the smooth landing of Xinyunlin Technology in Taiwan and the opportunity to recruit talents from all walks of life to work together In the short-term layout, the company will actively cooperate with domestic players such as Hon Hai and TSMC to implement image analysis AI technology in fields such as self-driving cars, smart industrial safety, and smart warehousing robots In the medium to long term, Xinyunlinke will target the United States, Europe, Japan and other countries as its global market layout, establish investment and cooperation partnerships with major international companies such as Microsoft, and replicate its successful experience and promote it internationally Xinyunlinke official website Xie Yuanbao, founder and chairman of Xinyunlinke 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】AI電眼取代人眼 慧演智能運用AI幫製造業做品管
Using AI vision to replace human vision, Claireye Intelligence uses AI to help the manufacturing industry with quality control

In response to customer demand on a wide variety of products in small quantities in the manufacturing industry, there is an urgent need to find AI solutions from the cloud to terminals Claireye Intelligence provides a solution that integrates software and hardware - BailAI image inspection solution to assist traditional manufacturing industries in improving process efficiency and product quality, thereby achieving the initial goal of transformation After the government declared 2017 to be Taiwan's "First Year of AI," AI startups have sprung up in Taiwan Established in 2018, Claireye Intelligence targets smart manufacturing and provides a platform for AI image analysis and process optimization, using the power of deep learning to detect product defects and abnormalities in the assembly process It assists companies in building infrastructure from terminals to the cloud, which enables automated monitoring of factory production to improve process efficiency and quality Focusing on AI image inspection based on its familiarity with the production line quality control process Shirley Liu, founder and CEO of Claireye Intelligence, is a young entrepreneur She entered the manufacturing industry after graduating from college and held a quality control position in the plastic injection process of hard disk parts "She was already on the production line at the time, and is familiar with the production line process of production machinery" She later switched career paths to marketing and planning, and then worked as an AI product manager When the time came, Shirley Liu decided to start a business, focusing on AI image recognition in the manufacturing industry "The difficulty for enterprises is the lack of an AI development team Even if an enterprise has an AI team, development projects will take a lot of time, at least 6-12 months" said Shirley Liu, who is well versed in the market's pain points The problem that needs to be solved by platforms is to provide services that allow traditional manufacturing industries to build their own AI models without needing employees with a programming background, and to remotely assist production lines with troubleshooting and subsequent system maintenance, helping companies save development time and labor costs BailAI image inspection platform usage scenarios Facing the large number of competitors that provide AI image recognition in the market, what are the technical advantages of Claireye Intelligence Shirley Liu said that many companies currently have AOI equipment, but the bottleneck in the application of AOI is that it can only be used for defect inspection in fast production of large quantities, and parameters need to be adjusted after each inspection or production Based on her understanding of the industry, most SMEs are limited by their financial resources due to AOI equipment often costing over NT1 million, but they also want to use automated inspection This is where Claireye Intelligence comes in Shirley Liu went on to say that it is impossible for traditional manufacturing industries to maintain a technical team that includes AI engineers, data engineers, cloud architects, and terminal architects Claireye Intelligence specializes in software and hardware integration Enterprises can use the BailAI image inspection platform to easily solve inspection problems on the production line In other words, customers only need to provide images or samples for Claireye Intelligence to carry out model training, model deployment, and system integration, and they can easily use AI technology to optimize and monitor production line processes Participated in the AI New Talent Selection and achieved a recognition rate of over 90 in assembly behavioral image recognition For example, a certain connector manufacturer only has 1-2 AI engineers in its technical team The main problem that needs to be solved is that most operators are on the production line, while quality control and senior managers are not on site, and the company wants to understand the actual situation of the production line through remote monitoring Claireye Intelligence uses industrial cameras to capture production line images, and transmits AI image analysis to the remote end Supervisors and quality control personnel can observe if there are any errors in the production line assembly, such as whether the connectors and lines are connected properly, through the monitor Claireye Intelligence's AI image inspection operates on Microsoft's Azure cloud platform, and also utilizes terminal equipment, such as NVIDIA's edge computing equipment placed around the inspection station, to assist traditional manufacturing industries with improving production line efficiency and detecting problems early through an integrated solution from the cloud to terminals Claireye Intelligencersquos customers currently include aviation, electronic peripherals, connectors, and metal industries Assembly process solution for human behavior recognition in assembly lines achieves an accuracy of over 90 In order to demonstrate the depth of technology, Claireye Intelligence participated in the 2021 AI New Talents Selection of the Industrial Development Bureau, Ministry of Economic Affairs, and provided Lite-On Technology with the "assembly process solution for human behavior recognition in assembly lines" The solution determines effective working hours and ineffective working hours of operators on the production line through cameras and AI image recognition It recognizes hand posture and position through images to determine the operator's assembly behavior, achieving an accuracy of over 90 Shirley Liu added that the assembly process of electronic components is complex, mostly carried out manually, and cannot be replaced by robotic arms Claireye Intelligence used cameras to film the assembly process of operators at Lite-On's assembly station The algorithm is then trained and corrected based on the video, and the final trained model can directly determine whether there are any errors in the assembly process to improve the overall process Project development time is expected to be shortened to 1 month by using the BailAI image inspection platform Since its establishment more than three years ago, Claireye Intelligence has accumulated a considerable amount of project experience and hopes to commercialize the project experience Shirley Liu pointed out that the trial version of BailAI image inspection will be completed this year 2022 Customers can choose industrial cameras or video cameras based on the detail of the object being inspected It can even use X-rays to capture images, and then the images are automatically marked by the platform Claireye Intelligence will provide customers with AI application models suitable for the field Inferences can also be made in the cloud or terminals for launch in the manufacturing industry The metals industry, metal casings of industrial computers, connectors, electronic peripherals, and mechanical parts can all use the platform for defect detection and object identification Claireye Intelligence will continue to improve its technical capabilities, accumulate customer experience to complete commercialization, and also accelerate the implementation of AI inspection applications In the mid-term, it will build terminal and cloud infrastructure and shorten the development time of enterprise AI projects from 6-12 months to 1 month, reducing usage time and lowering the threshold for enterprises The long-term goal is to target the Southeast Asian market where Taiwanese businesses are gathered, expand software and hardware integrated AI solutions to overseas markets, and expand the scale of operations