RoboDAQC · Technology
The architecture behind datasheet in, verified integration out.
Frontier AI is the intelligence layer. RoboDAQC provides the controlled hardware access, execution, safety and observation environment it works through.
The loop, step by step
What the agent does at each stage.
- 1
Understand
Read the datasheet, SDK, protocol description, pinout or existing code.
- 2
Act
Configure buses, probe devices, read registers, send commands, execute integration code.
- 3
Observe
Inspect device state, bus traffic, decoded frames and, where needed, electrical behaviour.
- 4
Correct
Compare expectation with reality and diagnose mismatches.
- 5
Verify
Test again until the behaviour matches the objective.
- 6
Reuse
Save a driver, ROS 2 node, library, configuration and verification record.
Platform
Five parts underneath the loop.
- 01
Multi-protocol hardware node
Compact node with CAN FD, RS-485, I²C, SPI, UART, GPIO, USB and Ethernet.
- 02
Abstraction & safety layer
Bounded, controlled access so an agent can act on real hardware without unchecked control.
- 03
Instrumentation
Physical observability: the electrical evidence needed for deeper debugging and qualification.
- 04
MCP interface
Hardware capabilities exposed to any MCP-capable AI agent. As models improve, the physical interface doesn't have to be rebuilt.
- 05
Developer workbench
Work from VS Code: inspect buses and device state, direct the agent, review what it changed, trace integrations and keep the resulting drivers and device definitions.
Hardware direction
Small enough for the bench. Designed to go where the engineering happens.
The current hardware direction is a compact CM5-class system built around a vertically integrated carrier and instrumentation architecture.
- Developer workbench & core hardware-access stackBuilt · hardening
- Compact carrier & instrumentation hardwareIn development
Bring us a difficult device.
We're looking for engineers and teams with real hardware integrations to test against.