教链 · CoachLink
An AI movement training system for athletes, coaches, and studios. It connects planning, training logs, movement analysis, and coach operations so training can be understood, reviewed, and continuously improved.
AI that keeps understanding how people move, eat, and change
Visual AI, multimodal models, and wearable sensing turn real-world movement and nutrition into a personal health intelligence model.
CoachLink and FoodLink for two high-frequency health behaviors
CoachLink and FoodLink are not the endpoint. They are application entries into a broader human behavior perception system, solving today’s problems while generating the real feedback required for future health intelligence.
Open CoachLink
食探 · FoodLink
An AI nutrition management system for individuals and organizations. It combines food recognition, nutrition analysis, and personalized guidance to understand each meal with less friction and connect eating behavior to long-term goals.
Not two isolated apps, but one system for understanding human behavior
IntelliFit is building a next-generation AI human health perception system. We enter frequent, verifiable movement and nutrition scenarios through CoachLink and FoodLink, then use wearables to capture continuous real-world signals.
5,000+
100K+
2 + 1
The next step in health management: from manual logging to continuous understanding
Traditional health apps wait for users to enter data. We want AI to sense behavior in the real world, understand physical state, and recommend the next executable action.
01 · Log
02 · Sense
03 · Understand
04 · Decide
From application entries to wearable sensing and a human behavior intelligence platform
This is not a device bolted onto two apps. It is a staged path: validate users and scenarios, reduce sensing friction, then build a long-term model of human behavior across contexts.
A compact AI fitness sensing module can clip onto workout clothing or equipment as an entry point for movement and training understanding. Its sensors and scenarios remain under validation.
Stage 1 · Application validation
Stage 2 · Wearable sensing
Stage 3 · Behavior intelligence
Validate with real products before expanding the sensing boundary
Every screen below comes from a working CoachLink or FoodLink product. The application layer solves today’s problems and grounds the technology roadmap in real usage and feedback.
Coach plans, training execution, and cycle progress
Video analysis, strength tools, and scenario-based utilities
Coach discovery by direction before deeper conversation
Meal logging, calorie budget, and micronutrient overview
Health scores, AI analysis, and improvement priorities
Public feed, check-in leaderboard, and food-sharing interactions
A team at the intersection of AI, life science, and high-level training practice
IntelliFit starts from the founder’s AI and life-science research, serious strength-training practice, content reach, and the ability to build products with real users—not from an abstract health concept.
Jianwen Ma
PhD student at Peking University’s Academy for Advanced Interdisciplinary Studies, with an automation background from Nanjing University of Aeronautics and Astronautics. He works across AI for Science and multimodal intelligence, while bringing serious strength-training practice, strong execution, and first-hand judgment on training methods, body management, and real user needs into product building.
Personal websiteHuang Zhelong (Jin hui)
Known as Jinhui, he writes technical articles and contributes to OpenMCP and slidev-ai, winner of Alibaba Best App Award. He provides web full-stack development plus frontier Agent R&D and iteration support. Hobbies: fitness, coffee, cycling, and coding.
Personal websiteYa Ning
Ya Ning focuses on reliable backend systems and AI infrastructure, covering backend deployment, cloud-native infrastructure, performance tuning, and reliability engineering. His work spans Go, Kubernetes, observability, and high-concurrency service practices to keep core product systems available and efficient.
Personal websiteHiring early core members in Beijing
We are building an early AI + fitness and health company with real products, real users, early revenue, and active B2B opportunities. The bottleneck is not a lack of ideas; it is finding people who can own work and close loops.
AI perception and technical product
Build CoachLink and FoodLink while advancing movement video understanding, pose estimation, multimodal sensor fusion, wearable validation, and B2B delivery.
Founder IP growth and commercialization
Build founder IP into a real commercial asset across content, user conversion, private community, consulting, training camps, live commerce, and partnerships.
What we value most
Priority candidates
How to apply
Help advance AI understanding of real human behavior
We welcome collaboration with coaches and sports organizations, enterprise and university health programs, computer-vision and wearable partners, and early teammates who want to build the system with us.