INDUSTRIAL AI · PHYSICAL AI

Physical AI and engineering for industrial systems

From recognising a part to talking with a visitor. We build the intelligence and software that connect perception, information and action.

Front view of TXISTU with sensors above its head and its face illuminated in blue.
TXISTU during a project test, developed with NASERTIC on a Unitree G1 platform. Explore the TXISTU project →

Solutions

Industrial Computer Vision

We develop models that detect objects and estimate their position. We connect those observations to the robot or industrial process and evaluate performance using images from the actual environment.

  • Detection
  • Localisation
  • Spatial estimation
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Human-Robot Interaction

We connect speech recognition, language models and information sources so a system can answer questions in context. We also define when it should request assistance or stop an action.

  • Voice and conversation
  • Context-aware interfaces
  • RAG integration
TXISTU →

Industrial AI & Edge

We choose where to run models based on latency, connectivity and data control requirements. We integrate the solution with existing systems and plan how it will be maintained.

  • Applied AI
  • Edge / cloud
  • Industrial integration
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ENGINEERING FOUNDATIONS

The engineering that makes it possible

A model needs data, interfaces and software to work within a system. We build that foundation, from connecting an ERP to deploying an API or setting up the infrastructure it runs on.

How we work

We start with the task you need to solve and the conditions it must work in. Then we agree the scope, build the system and test it against clear criteria.

  1. Discovery

    We review the process, equipment, available data and operating constraints.

  2. Design

    We agree what the system must achieve, how it will integrate and which tests will demonstrate the result.

  3. Development & integration

    Build the intelligence layer and connect it to existing systems.

  4. Validation

    Check behaviour against agreed criteria and document its limits.

  5. Evolution

    We refine the system based on test results and plan maintenance and further improvements.

What does your system need to do?