Labor is the bottleneck
of logistics.
We're building the robots that remove it.
Oli Robotics develops bimanual AI robots for 3PL warehouses — sorting parcels, picking orders, processing returns. Trained on proprietary teleoperation data. Deployed as a service.
$1.5 trillion moves through 3PL every year.
70% of the cost is human hands.
Third-party logistics is the backbone of global commerce — and its margins are being crushed by labor it can't hire fast enough.
The industry doesn't need another conveyor belt. It needs hands that think.
Bimanual robots, built for the messy 80% of warehouse work.
The hardware stack.
Built for the messy 80% of warehouse work — mixed SKUs, poly bags, returns, irregular shapes — that conveyor automation can't touch.
Every shift makes the fleet better.
Traditional robots ship with fixed capabilities. Ours ship with a learning loop — and the moat compounds with every grasp.
Teleoperate
Human operators handle edge cases through force-feedback gloves. Every motion becomes labeled training data — joint trajectories, contact forces, intent.
Train
Autonomize
Pay for output, not hardware.
No capex. No integration teams. No six-month deployments. You staff your warehouse the way you'd scale a SaaS license.
Three curves just crossed.
The window to build the category leader is open. It won't stay open long.
Foundation models for robotics work.
VLA architectures (π0, GR00T, RT-2) cleared the generalization barrier in 2024–2025. Robots can finally learn tasks instead of being programmed for them.
Compute fits on the robot.
Jetson Thor delivers data-center-class inference at the edge. No cloud round-trip, no latency tax — sub-50ms decisions on-device.
Labor economics broke.
3PLs are paying signing bonuses for warehouse pickers. The unit economics of RaaS now beat human labor in most US metros — for the first time ever.
We've shipped robots that worked in the wild.
Before Oli, our team built and deployed an autonomous robotic café in San Francisco — a fully bimanual system serving real customers, viewed by 4M+ people on social media.
We learned what physical-AI startups usually learn the hard way:
- L·01Hardware reliability is the product.
- L·02Data quality beats data quantity.
- L·03The last 5% of autonomy takes 95% of the work.
We're applying those lessons to a market a thousand times bigger.