Making artificial intelligence no longer the exclusive domain of a few technical experts, but a powerful business tool that every frontline employee can harness and continuously grow with.
Recently, Valeo China has partnered with Feishu and jointly launched the "Valeo China x Feishu AI Pioneer Competition." The competition attracted over 400 employees, gathered 73 practical business applications across R&D, production, supply chain, sales, finance, HR, and quality departments, and ultimately saw 12 teams advance to the finals.
Notably, all participating projects were not conceptual demonstrations, but solutions already integrated into daily work practices—employees used Feishu's multi-dimensional tables, Miaoda, knowledge base, automation, and AI features to build their own tools, improving workflows previously reliant on manual data entry, email exchanges, and experiential judgment.
Valeo China x Feishu AI Pioneer Competition event scene
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Zhou Song, President of Valeo China, stated that Feishu is crucial to Valeo’s development in China. The group is now integrating it with existing cloud and AI tools. He noted that Valeo's major clients and numerous industry partners in China are using Feishu, and the company itself also needs collaboration platforms to enhance efficiency and support digital transformation.
Currently, more than 70% of the top 30 new energy vehicle manufacturers use Feishu. By 2025, approximately 60% of Valeo’s large orders in China are expected to come from domestic automakers—choosing the same collaboration platform means suppliers and OEMs can operate within the same toolset, enabling faster requirement alignment and project delivery.
As a global leader in automotive parts, Valeo's driver assistance technologies are applied in about one-third of new vehicles worldwide. According to the 2026 Top 100 Supplier Ranking released by *Automotive News*, Valeo ranks 13th globally. By the end of 2025, Valeo will have 22 manufacturing sites, 10 R&D centers, and around 17,000 employees in China, making China Valeo’s largest single market globally.
Aftermarket Parts Management
Over forty manual data entries completed within thirty seconds
The first-prize and Most Popular Pioneer Award winner of this competition—"AI Recognition and Automatic Registration for Aftermarket Parts Management"—focuses on a seemingly simple yet long-standing challenge for frontline staff: information entry for aftermarket management of oversized components.
Previously, technicians had to manually compare return cards and product labels, verify over forty complex data points—including VIN (Vehicle Identification Number), mileage, fault descriptions, production batches, and hardware/software versions—and then enter them manually into the internal business system. Processing each item took over ten minutes; when scaled to the company’s annual volume of returned parts, repetitive data entry consumed significant labor hours and carried risks of errors or omissions.
The red boxed areas indicate content technicians previously had to identify and fill in manually
The project team redesigned the workflow: technicians now only need to take two photos—one of the return card and one of the product label—and upload them to Feishu's multi-dimensional table. AI automatically recognizes handwritten text, 17-digit VIN codes, and small-font hardware/software version details, then organizes the information into standardized tabular data. The system then reads this data, matches it, and automatically writes it into the internal system, which generates a unique traceability code, forming a complete closed loop of "capture, recognition, review, registration, and feedback."
Form used by technicians to upload information
After optimization, processing time per item has been reduced from ten minutes to under thirty seconds, with 100% data entry accuracy. Approximately 3,800 working hours are expected to be saved annually. Employees are freed from repetitive data handling tasks and can now dedicate more effort to returned part inspection, failure cause analysis, and quality improvement initiatives.
Reduced from three days to two hours
Another standout case from the competition involved using Feishu Miaoda to reconstruct the ADAS R&D cost quotation evaluation process.
Valeo provides software development services for ADAS (Advanced Driver Assistance Systems)—such as automatic emergency braking and lane-keeping—to automakers. Whenever a client proposes a new project, the sales team must collaborate with system, software, testing, and project management departments to assess development workload and produce an R&D cost estimate. Because quotations involve specialized knowledge across both commercial and technical domains, extensive interdepartmental coordination is required. However, relevant data is scattered across emails, Excel files, and personal computers, so completing a full quotation typically takes three to five days. New employees also require substantial time to become familiar with the process, data sources, and assessment methods.
The project team used Feishu multi-dimensional tables to consolidate historical quotation data, standard man-hour costs for various functions, testing fees, and regulatory requirements into a unified rulebase. They then built an R&D cost estimation system using Feishu Miaoda. Now, employees simply input customer requirements, and AI automatically matches similar past projects, calculates development costs and risk factors for each phase, and generates a standardized R&D cost estimate. Department heads can conduct online reviews within the system, with approval progress visible in real time.
Detailed workflow of a quotation currently under approval
The system has now reduced the entire R&D cost evaluation cycle from three days to just two hours, improving overall efficiency by 90%. The time required for new employees to master the quotation process has also been shortened from six months to one month.
At the competition, Zhou Song emphasized that the AI applications showcased complement mature systems like SAP, extending into the "first mile" and "last mile" of business processes. He also pointed out that for similar scenarios, integration and replication of these applications should be accelerated to avoid redundant development, allowing proven practices to benefit more product lines and teams as quickly as possible.
For Valeo China, the 73 cases accumulated through this competition represent only the beginning of the bilateral partnership—the more critical shift being that control over AI application has moved from a handful of technical experts to frontline employees. Business personnel can now independently identify problems, build tools, and continuously iterate, transforming individual experience into reusable organizational knowledge and processes. As outstanding cases are further promoted, Feishu will continue supporting Valeo China in converting the one-time innovation enthusiasm generated during the event into sustainable business growth capabilities.
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