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Industrial data layer for robotics training

We capture and structure real factory workflows at scale by combining first-person industrial video with SOP-level process knowledge. This enables robotics and AI labs to train on real production data, not just controlled lab environments.
Active Founders
Tanachart (James) Kujareevanich
Tanachart (James) Kujareevanich
Founder
James is the co-founder and CEO at LineWise. MBA from MIT. Former McKinsey Ops consultant.
Zhichu Ren
Zhichu Ren
Founder
Zhichu is the co-founder and CTO at LineWise. MIT PhD. Built robotics automation for materials research.
Will Wenbo Zhang
Will Wenbo Zhang
Founder
Will is the co-founder and CPO at LineWise. MSE in AI & Robotics at UPenn GRASP Lab. Former founding engineer at Greyscale AI and Bestmow.
Company Launches
Vision Lab: The Industrial Data Layer for Robotics
See original launch post

TL;DR

We capture and structure real factory workflows at scale, pairing first-person industrial video with SOP-level process knowledge, so robotics and AI labs can train models on the data that actually exists inside production environments, not just lab demos. We are already working with 2 frontier AI labs.

🎥 Our 60-second Product Launch:
https://www.youtube.com/watch?v=u2CyfEnYY5A

THE PROBLEM

The robotics industry is being trained mostly on lab demos, even though robots will ultimately need to operate in messy, high-variance real factories. The industry has less than 0.3% of the data it needs, and almost none of it comes from real factory environments.

Why?

Industrial data does not exist at scale
It cannot be scraped or passively collected. It has to be captured inside real factories, on real production lines, during real operations.

Raw footage is not enough
Unstructured industrial video is noise. Models need process context: what step is happening, in what order, with what tools, and whether it was done correctly.

Crowdsourcing cannot solve it
Understanding industrial actions requires factory expertise. Anyone can label an object; far fewer can distinguish whether a torque check, weld, inspection, or setup sequence was performed correctly.


THE SOLUTION

Vision Lab solves the industrial data problem by building:

The most diverse industrial dataset
SOP-structured production data spanning cutting-edge environments like biotech, EV manufacturing, semiconductors, and medical devices, as well as large-scale manufacturing.

Industrial access at scale
A network of 2,000+ factories across 50+ industries in 27 countries, with operators and factory owners embedded in the capture process so every sequence, tool, and technique is recorded correctly at the source.

A proprietary VLM for industrial settings
A temporal VLM trained on SOP-paired industrial footage to understand not just what is happening, but the order, timing, and correctness of real industrial processes. Our state-of-the-art VLM outperforms Gemini by 2.5x on temporal understanding in industrial settings.


PARTNER WITH US

If you believe the next decade of robotics and world models will depend on real-world industrial data, not just compute, we’d love to talk.

Vision Lab partners with robotics labs, frontier AI teams, and manufacturers to build the default industrial data layer for robotics.

Contact: founders@thevisionlab.ai
More info: www.thevisionlab.ai

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Previous Launches
AI that troubleshoots your production line
YC Photos
Vision Lab
Founded:2025
Batch:Spring 2025
Team Size:8
Status:
Active
Location:San Francisco
Primary Partner:Tom Blomfield