Physical AI & Robotics

Your robots learn from the world. We bring the world to them.

Real-world data is the hardest part of building physical AI. We plan, capture and label the multi-sensor data your models need, and help you run those models well on the hardware you ship.

Robot arm or mobile robot in a lab, with a calibrated multi-sensor capture rig nearby
01 · What you can count on

Built for production programmes.

Data operations on three continentsField teams and pipelines wherever your robots need to work
Thousands of participants recordedConsented, diverse and well documented
Years inside production programmesBuilt for the standards of global automotive brands
02 · We get it

The data problem is the real problem.

Your model is only ever as good as what it has seen. And the real world rarely shows up on schedule.

“

Your model is starved of real-world data.

Simulation takes you a long way, but your robot still meets the real world for the first time in the field.

“

The rare moments matter most.

The situations that break your system are exactly the ones you cannot stage on demand.

“

Your data fights your pipeline.

Sensors out of sync, labels that disagree, and formats that do not fit the way you train.

03 · How we help

Everything between your model and the real world.

Field crew operating a calibrated camera and LiDAR rig
CameraLiDARRadarIMU
01 · Data campaigns

Tailored multi-sensor data campaigns

We plan the campaign around your tasks, environments and edge cases. Then we capture camera, LiDAR, radar and motion data together, calibrated and in sync, wherever you need it.

  • +You get the data your model is missing, not more of what it already has.
02 · AXIRA

AXIRA edge data platform

Our multisensor fusion platform makes sense of data in the field. What comes back is usable data, rather than raw terabytes waiting weeks to be processed.

  • +You get fewer collection runs, and a shorter path from capture to training.
Edge compute unit in a vehicle or robot, with live fused sensor view on screen
Edge fusionIn-field processing

Labelling you can trust

2D and 3D annotation with quality checks at every layer, built to your guidelines and delivered in the format your pipeline expects.

You get. labels your engineers stop second-guessing.

Model benchmarking and optimisation

We benchmark your models on the silicon you plan to ship. Then we make them run fast, without giving up the accuracy you worked for.

You get. real numbers on real hardware, and models that fit your power and cost budget.

04 · How a campaign works

From brief to training-ready, in four steps.

01

Scope

We agree the tasks, environments, edge cases and volumes your model needs.

02

Capture

Calibrated, synchronised rigs and trained crews collect in the places you choose.

03

Label and verify

Annotation in 2D and 3D, checked in layers before anything reaches you.

04

Deliver and refresh

Data in your format, live or in batches, with new rounds as your model grows.

Data operations team at work, reviewing labelled 3D point clouds
Engagement models

Work with us your way.

A dedicated, client-only data centre. A managed team that scales with your programme. Or simply pay per delivery.

05 · Proof

Data programmes that ran for years, not weeks.

Annotated street scene with 3D bounding boxes
Autonomy · Leading car marque

Training data they could count on, year after year

A long-running programme of image, video and 3D labelling under strict quality checks, sustained across multiple projects.

Result. consistent, production-grade data, project after project.

Dense, unstructured Indian traffic scene from a dashcam
Research · IIIT and University of Maryland

One of the world's largest open driving datasets

We collected and labelled more than 100GB of real, unstructured driving behaviour and released it openly.

Result. METEOR, used by researchers around the world.

Trusted by teams at

  • Mercedes-Benz
  • Intel
  • Honeywell
  • Mastercard
  • MTN
  • SiMa.ai
  • Hubilo
  • Flytxt
  • ProcessMAP
  • DigitalTrust
  • CardByte
  • Susman Godfrey
  • Pixofix
  • BoxFit
06 · Questions

What teams usually ask us.

How do I source real-world training data for robotics or physical AI?

You can collect it yourself, license existing datasets, generate it in simulation, or work with a specialist partner who combines all three. For multi-sensor, real-world data, a tailored campaign usually gets you the edge cases you need far faster than building a collection operation from scratch. That is what we run.

Can you collect data in our own environment or facility?

Yes. We bring calibrated sensor rigs and trained crews to your sites, or capture in public environments that match where your robots will work.

Which sensors and formats do you support?

Camera, LiDAR, radar, thermal, IMU and GNSS, captured together and in sync. We deliver in the formats your training pipeline already uses.

How do you handle privacy and consent?

Participants give informed consent, and personal data is handled under access and anonymisation controls that we agree with you before collection starts.

How do engagements work?

As a dedicated, client-only data centre, a managed team that scales with you, or per delivery. Most clients start with a scoped pilot campaign.

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Last updated: 19 October 2026

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Email: info@navajna.com