Every significant technology transition has an infrastructure problem that looks unsolvable until someone decides it isn't. The internet needed fiber. Mobile needed towers. Cloud computing needed data centers. Physical AI needs a data supply chain — and right now, that supply chain barely exists.
FieldMesh Data was built to be that infrastructure. Today we're opening pilot scoping for physical AI and robotics teams that need something the existing data market cannot provide: egocentric video from real US operating environments, collected from real employed workers, under buyer-defined protocols, with consent chains that hold up.
Why We Built This
The physical AI industry is at a remarkable inflection point. Humanoid robots that would have looked like science fiction five years ago are now shipping into commercial environments. Autonomous material handling systems are operating in live distribution centers. Manipulation arms that can generalize across object types are moving out of research labs. The hardware has largely caught up to the ambition.
The data hasn't.
Every physical AI team we've talked to has the same problem beneath the surface: they don't have enough real-world training data. They have synthetic data that doesn't generalize. They have staged footage that produces models that perform in the staged environment. They have a handful of research datasets that have been used by everyone, which means they can't build a differentiated model on them.
"The physical AI teams that win the next five years won't be the ones with the best architecture. They'll be the ones that solved their data pipeline first."
We built FieldMesh to solve that pipeline.
How FieldMesh Works
The model is straightforward, even if the execution is not.
On one side: physical AI buyers — robotics teams, autonomous system developers, AI labs. They need egocentric video data from specific environment types. They have protocols: camera specifications, task types, annotation requirements, volume targets, delivery timelines. They need rights-cleared data they can actually train on.
On the other side: US operating businesses — warehouses, manufacturing facilities, food production operations, skilled trades businesses, healthcare environments, retail operations. These businesses have something valuable that most of them don't know is valuable: their workers' daily operational behavior, captured from the first-person perspective, is training data for the physical AI systems that will define the next decade of industry.
FieldMesh sits between them. We equip business partners with the hardware and protocols specified by each buyer. Workers participate voluntarily, with informed consent and direct compensation. Data flows from the collection environment to the buyer under a rights agreement that clearly defines usage scope. The business earns additional revenue. The workers earn additional income. The buyer gets data that actually generalizes.
What Makes This Different
We're not a data broker. We don't have a catalog of footage someone shot two years ago in a warehouse in Ohio. We're infrastructure — we build the collection relationship, deploy the protocols, ensure the consent chain, and deliver data to spec.
The key differentiators matter if you're evaluating physical AI data supply options:
- Employed workers, not gig contractors. Our data reflects how real workers actually perform their jobs — speed, decision-making, motion efficiency, situational awareness. Not a performance of those things.
- Operational environments, not staged ones. Collection happens during actual operations. The environment responds the way it actually responds, not the way it responds when an outsider is present for a weekend session.
- Layered consent, not checkbox consent. Business owner agreement, individual worker voluntary consent, usage-scoped data rights. Documented and auditable.
- Environment diversity by design. We've built across warehousing, manufacturing, food production, skilled trades, retail, healthcare, facility services, construction, and agriculture. The diversity is the product.
What's Available Now
Pilot scoping is open. We work with physical AI and robotics teams to define collection parameters — environment types, task focus, camera protocols, volume targets, annotation requirements — and scope a pilot engagement before moving to production-scale collection.
If you're a US business in any commercial environment and you're wondering whether your operation could be a data collection partner, that answer is almost certainly yes, and the process starts with a profile submission.
The physical AI industry is moving fast. The data infrastructure to support it has been moving too slowly. FieldMesh is here to change that ratio.
Let's scope your pilot.
Tell us your environment requirements. We'll tell you what's possible and what it takes to get there.