Your machines have sensors. Your workers don’t.
TIM (Tangerine iFactory Model) reads worker behavior from a wrist sensor — fatigue, focus, compliance — and turns it into decisions with dollar impact. Every alert tells your line manager exactly what to do and how much it saves.
PCB Factory — Line 3
41 workersRotate Liu M. off plating — fatigue 91%, defect risk +340%. Est. $2,400 savings.
How It Works
From wrist to decision in 200ms
Wear
A lightweight wrist sensor captures 50Hz accelerometer data during every shift. No cameras, no invasion of privacy. Workers forget it’s there after 10 minutes.
PIPL compliant — raw data stays on-premise
Analyze
Edge AI extracts 7 behavioral dimensions in real-time: fatigue, focus, task rhythm, SOP compliance, micro-tremor, transition patterns, and team dynamics.
Models calibrate to each factory in 90 days
Act
Every insight comes with a specific action and estimated dollar impact. ‘Rotate Worker C19 now — est. $2,400 savings.’ Not reports. Decisions.
WeChat/DingTalk alerts to line managers
The Blind Spot
Every factory has MES for machines and ERP for materials. Nobody has intelligence for workers.
Direct medical and compensation costs per incident. Indirect costs multiply this 4–6x. Most are preventable with early fatigue detection.
Fatigue, distraction, and skill gaps — not machine failure — account for the majority of quality escapes on the production line.
Industrial automation ($82B) + workforce mgmt ($19B) + safety tech ($12B) + IIoT ($43B). All optimizing around the worker, never the worker itself.
Not Vaporware
Built on 9 papers and 33 datasets
This isn’t a pitch deck company. Our behavioral models are validated against public academic benchmarks. Our algorithms are documented in peer-reviewed research. Our IP is protected by 7 drafted patents.
Case Study — Sihui Fuji Electronics (300852.SZ)
$180K annual savings from one factory deployment
4 production lines. 41 operators. 12 months of data. Lamination, drilling, plating, and final QC — each line with measurable, specific improvements.
Read Full Case Study arrow_forwardPre-Seed round open.
$380K SAFE at $5M cap.
82% gross margin. 148x LTV:CAC. Hardware-included SaaS. Category-defining platform in a $156B market with zero behavioral intelligence.