Menlo Platform
The Menlo Platform is our core product infrastructure: an integrated stack for building, training, validating, and deploying agentic behavior into humanoids.
Components
The Menlo Stack integrates four key components:
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Agent Platform — The deployment layer for packaging, permissioning, and deploying AI agents to humanoid robots. Agents are packaged as deployable payloads, constrained by safety envelopes, and observable through operational telemetry.
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Uranus — Our world simulator and digital twin engine. Produces high-fidelity scenarios for stress-testing agents, enables pre-deployment validation, and supports hardware-in-the-loop testing.
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Cyclotron — Our motor-control and locomotion training pipeline. Trains robust full-body behaviors through domain randomization, bridging the reality gap between simulation and hardware.
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Data Engine — Our telemetry and continuous improvement system. Captures operational evidence and feeds real-world data back into Uranus and Cyclotron for closed-loop improvement.
The Deployment Loop
The Menlo Platform enables rapid iteration:
- Define an agent in a standard framework
- Validate against scenarios in Uranus
- Refine motor skills via Cyclotron if needed
- Deploy to Asimov via Agent Platform
- Capture telemetry in the Data Engine
- Iterate and redeploy
A platform wins even if hardware commoditizes. We focus on the cost-collapse levers that enable humanoid robotics to be deployed as an economically viable labor force, not a novelty demo.