Why we built a company to
capture factory data
The gap between robotics research and real manufacturing deployments isn't closing on its own. We built TalosHub to close it.
Why robots fail when they leave the lab
Robotics teams were failing in factory deployments — not because of model limitations, but because of training data that never reflected real manufacturing conditions. The gap wasn't compute or architecture. It was ground truth.
In a lab, parts are uniform, fixtures are ideal, and every demonstration is a successful one. On a real shop floor, tray positions shift, parts have burrs and chips, machines throw alarms, and operators have developed years of tacit workarounds. None of that exists in lab data.
TalosHub was built to close that gap. We go directly to manufacturing facilities, capture real operator workflows with real machines, and structure everything into training-ready datasets that reflect conditions your robots will actually encounter.
What we exist to do
TalosHub exists to make real manufacturing data accessible to robotics teams. Not lab demos. Not simulation. The actual data that makes industrial robots work in the real world.
How we think about this work
Everything we build starts from real factory conditions — machines, operators, variance, and exceptions included. Lab conditions aren't a starting point.
One workflow, done right. We don't try to cover everything at once. Each task pack is scoped precisely and executed completely before moving on.
Schemas, documentation, and capture methodology are always open to clients. You know exactly what you're getting and exactly how it was captured.
We talk to engineers like engineers. No vague claims about "high-quality data" — we give you episode schemas, labeling taxonomy, and QA methodology upfront.
Facility relationships, capture methodology, client engagements
We maintain direct relationships with manufacturing facilities across multiple machine families and regions. Each partner facility gives us access to production cells during active operation — not after-hours demonstrations, but real shifts with real operators running real parts.
Every capture session is designed before we arrive — camera plan, machine-state integration points, exception taxonomy, and consent protocols. We synchronize multi-view video with live machine controller signals to build a complete picture of each manipulation episode, including nominal cycles and recoveries.
Engagements are scoped, not open-ended. We align on the workflow, delivery format, and timeline before capture begins. Starter packs deliver in 4 weeks. Growth packs expand coverage. All data is white-labeled, tenant-isolated, and delivered with schema documentation your team can act on immediately.
Ready to build with
real factory data?
Tell us the workflow. We'll scope a task pack and get back to you within 24 hours.
Get in Touch