POI

Mar 2019 — Oct 2024 · Full-time

Product Manager (TL)

Guangzhou POI-TECH Intelligent Information Technology Co., Ltd.

Led a team of 3 PMs building POI big data products — from end-to-end data services and no-code SaaS tools to AI-powered operations research and AIGC applications serving 400+ enterprises across China.

Years

Mar 2019 – Oct 2024

400+

Enterprises

Products deployed

20K+

Users

Reached through SaaS tools

$3M

Cost Saved

Annually via AI

2024

WAIC

Award recognition

Product Scope

Product Ecosystem

Owned product strategy across POI-TECH's industrial data ecosystem, connecting data integration, metric management, visualization, AI applications, AIGC services, and MOM platform modules into one scalable enterprise product portfolio.

Product Contributions

SQLAPIMySQL

Data Integration Tool

Situation

Siloed enterprise data systems led to high integration costs and fragmented visibility across business units, making consistent data access nearly impossible.

Task

Design and deploy a comprehensive data service platform that standardizes data collection, storage, and access — reducing friction for 20+ enterprise clients.

Action

Data IntegrationBuilt a configurable data collection & storage system with MySQL backend, enabling flexible ingestion from diverse sources.

Metric LibraryCreated a drag-and-drop interface for dataset mapping and visualization, with transparent calculation logic for business users.

OpenAPIStandardized business data access through unified CRUD APIs, enabling consistent integration across all downstream systems.

Result

Served 20 enterprises with 150 API integrations in 1 year. Reduced integration costs by 60% with high scalability.

HTMLJavaScriptD3.js

Data Visualization Products (SaaS)

Digital Factory & Reporting Tools

Situation

Manufacturing analysts struggled with fragmented data and no self-service reporting tools, resulting in slow decision-making and heavy reliance on engineering teams.

Task

Lead product strategy and delivery for a no-code SaaS suite — a Dashboard Tool and Reporting Tool — targeting manufacturing data analysis pain points.

Action

Roadmap & StrategyDesigned comprehensive data management strategies aligned with real manufacturing pain points, translating user research into a concrete product roadmap.

Cross-functional DeliveryCollaborated with a team of 20+ engineers, coordinating 100+ sprints to ship two full-featured data visualization products on time.

No-code Product DesignShipped 2 no-code data products — Dashboard Tool and Reporting Tool — enabling low-cost, self-serve data analysis for non-technical users.

Result

Deployed to 400+ enterprises, reaching 20,000+ users. Earned two Best Team Award nominations for exceptional impact on Data Visualization innovation.

Linear RegressionMMOEXGBoost

Industrial AI Operations Research Application

Situation

Manufacturing quality control relied on manual inspection, leading to high defect rates and reactive cost overruns across multiple production lines.

Task

Lead business research and AI product planning to build a real-time quality prediction system, coordinating AI engineers across model development and deployment.

Action

Product DefinitionLed business research and data analysis to define AI model goals; wrote the PRD and launched the product on schedule.

Model CoordinationLed AI engineers in model development (LinearRegression → XGBoost → MMOE), achieving 90%+ real-time prediction accuracy in Quality Prediction.

Post-deployment OptimizationEnhanced model performance through continuous abnormal data collection and iterative retraining post-deployment.

Result

Deployed across 23 production lines in 5 enterprises, reducing costs by $3M annually. Recognized as an outstanding case of AI-powered industrial innovation at 2024 WAIC (World Artificial Intelligence Conference).

RAGSupervised Fine-Tuning

AIGC Application Service

Situation

Industrial enterprises lacked intelligent tools to query and analyze operational data using natural language, creating a bottleneck for data-driven decision-making.

Task

Lead the product team to research, plan, and ship AIGC-powered services — including an industry knowledge base and fine-tuned LLM for operational analytics.

Action

Market ResearchLed product team in market research of 6+ mainstream LLMs and completed end-to-end AIGC product planning and design.

Knowledge BaseBuilt an industry knowledge base with documents, IoT data, and metrics using RAG — enabling 90%+ accurate natural language operational analysis.

Launch & AdoptionCoordinated engineers for product development and supervised fine-tuning; successfully launched 3 AI and data-driven services within 3 months.

Result

Acquired 10+ customers for production training within 3 months of launch, with 20+ potential paying clients in the pipeline.

IoTAPSMESEAMWMSBig Data

Process Cloud MOM⁺ 3.0–4.0

Situation

Industrial operations lacked an integrated platform to manage diverse factory systems — from IoT data to ERP modules — resulting in data silos and operational inefficiencies.

Task

Collaborate on building a comprehensive industrial MOM platform with 8+ modules, supporting high-performance data integration at enterprise scale.

Action

Platform DevelopmentCollaborated with the product team to develop an industrial platform with 8+ modules, including IoT, APS, MES, EAM, and WMS.

Big Data IntegrationCoordinated with big data engineers to clean and integrate 100 TB/yr+ of data, enabling high-performance and real-time queries.

Result

Platform currently serves 400+ enterprises with 2,000+ daily active users.

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