Foundation-model robotics

Automate the tasks classical robotics can't touch

Foundation models for robots, and the full lifecycle around them. Three to six months from kickoff to canary. Built for European manufacturers and 3PLs.

01 — Diagnostic

Where classical robotics breaks

Conveyor-fed, fixed-pose, single-SKU stations work. Everything else is still done by hand. That gap is where the cost lives, and where foundation models change the math.

01

Unstructured input

Bins arrive deformed. Items stacked, leaning, occluded. Calibration jigs do not survive a returns floor.

02

Mixed SKU

Thousands of items. No two grippers tuned the same. Hand-coded heuristics break past the first SKU expansion.

03

Long-tail edges

The 5% of weird inputs blocks 100% of the automation case. Foundation models cover the tail.

02 — Capability

What foundation-model robots can do today

The frontier is moving fast and unevenly. We'll help you assess when your task is feasible.

  • C-01

    Pick-and-place · mixed bins

    0.6–1.2 picks/s
  • C-02

    Sortation · dest routing

    up to 24 lanes
  • C-03

    Light kitting · packing

    multi-step chains
  • C-04 Q3·26

    Bimanual manipulation

    bag · fold · large
  • C-05 Q4·26

    In-context SKU adapt

    < 50 demos
  • C-06 SOON

    Mobile manipulation

    wheeled · multi-cell
03 — Why us

Three reasons this actually ships

  • W-01

    Whole lifecycle, one team.

    Teleop, fine-tune, deploy, RL. Same engineers from kickoff to canary. No vendor relay.

  • W-02

    The model stays yours.

    Fine-tuned weights and your dataset, on your hardware. No server-side lock-in, no per-run fees.

  • W-03

    Forward-deployed in Europe.

    Copenhagen and Stockholm based. We come to your line: Munich, Lyon, Lisbon. Real factory work.

04 — Hardware

Hardware suited for dexterous tasks

Other arms and end-effectors are available on request - matched to your task and payload.

Enactic OpenArm v2, an open-source bimanual robot arm.
Payload
6.0 kg peak
DOF
7 per arm · bimanual
Reach
633 mm
Cameras
Wrist ×2 · scene ×1
05 — Pipeline

Teach · Deploy · Improve

Three phases. Same team. Three to six months from kickoff to canary on the first task.

Teach

Operators demonstrate.

Trained operators teleop the target task across the real SKU mix. Wrist and scene cameras record every demonstration.


Capture
wrist + scene
Deploy

Fine-tune & ship.

A foundation model, fine-tuned on the captured demos and deployed to your controller. Canary first, then full rollout.


Latency
< 50 ms
Improve

RL on production data.

Production rollouts are scored on real outcomes. Weekly refinements push success rate up the curve.


Cadence
weekly
06 — How we start

Call first. A week on your line when it fits

Many teams come with questions before they're ready to put us on the floor. The call is how we figure out whether the audit is the right next step.

  1. Day 1

    Site visit, walkthrough.

    Our engineers walk your line. Arms, grippers, WMS, throughput.

  2. Day 2–3

    Task scoping, feasibility.

    Which flows are foundation-model-ready, which need waiting, which are better classical.

  3. Day 4

    Demo capture (optional).

    20–40 demos on one candidate task. Real data in the report.

  4. Day 5

    Written report, signed off.

    Scoped pilot proposal: target flow, integration, capex, success criteria.

07 — Next

Initiate the audit

One week, on your line. The report is yours.

Feasibility audit

Tell us how we can help.

0/500
Join the team

Apply to Qualia.

0/500

“It must be confessed, moreover, that perception, and that which depends on it, are inexplicable by mechanical causes, that is, by figures and motions. And, supposing that there were a mechanism so constructed as to think, feel and have perception, we might enter it as into a mill. And this granted, we should only find on visiting it, pieces which push one against another, but never anything by which to explain a perception. This must be sought, therefore, in the simple substance, and not in the composite or in the machine.”

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