We build the intelligence and operations layer for physical automation: 3D perception and pose estimation, motion and task planning, fleet orchestration, and the operator consoles your team lives in. From cobot cells and bin picking to AMR fleets and humanoid pilots, we take robots from a promising demo to supervised production work.
Hardware vendors ship capable platforms. What decides whether a cell holds cycle time, or an idle arm gathers dust, is perception tuned to your parts, planning that respects your constraints, and tooling your operators can actually use.
We build that layer for industrial arms, autonomous mobile fleets, and humanoid pilots: 3D vision, motion and task planning, fleet orchestration, and the consoles and telemetry that turn a promising demo into supervised production work.
Sim-first
Behavior validated in simulation before hardware time
Edge-native
Onboard inference on Jetson-class compute
ROS 2
Standards-based integration, not one-off scripts
Safety-aware
Built to support your ISO 10218 / TS 15066 review
Perception, autonomy, and operations software for industrial arms, mobile fleets, and humanoid platforms.
Three form factors, one software discipline. Most clients start with a single cell or route and expand once the numbers hold.
Supervised pilots, teleoperation rigs, and learned manipulation on general-purpose bodies.
Bin picking, 3D-guided placement, and cell integration with your PLC and MES.
Navigation, traffic control, charging, and mission scheduling across a site.
Six-axis arms doing real work: bin picking from unstructured totes, 3D-guided placement, and handoffs that survive part variation and shift changes.
Structured pilots for general-purpose platforms: data collection rigs, learned manipulation policies, and task orchestration with a human in the loop.
AMRs and AGVs coordinated as a fleet rather than a crowd, with traffic control, mission scheduling, and charging that hold up during peak.
Defect detection at line speed with operator review built in, so quality decisions are traceable and models improve from real rejects.
Virtual cells and routes where policies, layouts, and edge cases get tested cheaply, so hardware time confirms behavior instead of discovering it.
The day-two layer: telemetry, alerting, safe over-the-air updates, and remote diagnostics so a stuck robot does not require a site visit.
Robotics punishes optimism, so each stage is designed to surface bad news early and cheaply.
1–2 weeks
We measure the real environment: parts, tolerances, cycle times, layout, and safety constraints, then confirm whether the task is a software problem, a hardware problem, or both.
3–5 weeks
Environments, synthetic data, and planning or learned policies validated in simulation, including the edge cases nobody wants to stage on a live line.
4–8 weeks
Calibration, real-time tuning, PLC and fleet integration, and failure-mode drills on your floor with your operators in the loop from day one.
Ongoing
Staged handover with telemetry, safe update paths, and a concrete plan for going from one cell or robot to a multi-site fleet.
Robots that hold cycle time outside demo conditions
Operators who can diagnose and recover without calling engineering
Fewer hardware surprises, because behavior is proven in simulation first
A documented, testable software stack you own end to end
The tools we reach for on Robotics work, picked for the problem in front of us and for the team who inherits the code.
Real-time control and messaging
Making sense of a cluttered world
A million runs before a single one on hardware
Operating machines you cannot reach by hand
That is a common pattern and usually an integration and software gap: brittle scripts, perception that cannot handle real part variation, or no tooling for operators. We start with a short cell study to find where the process actually breaks, then rebuild the weak layer instead of replacing your hardware.