Industries
AI on the factory floor, and behind it.
From the test bench to the warehouse, we build AI that helps manufacturers troubleshoot faster, validate in the field, and see their inventory clearly. Practical work for complex production environments.
Book a consultationWhat we do
Where production work gets hard.
Manufacturing rewards AI in the places the work is knowledge-intensive and high-stakes: diagnosing faults, validating builds, and tracking what you actually have.
RAG troubleshooting pipelines
Instant access to device and product knowledge for test engineers, with sourced answers drawn from your own documentation instead of a manual search.
Test-debugging AI agents
Assisting validation and debugging in the field, surfacing likely causes and next steps so engineers resolve problems faster and with less downtime.
Engineering knowledge assistants
Putting institutional know-how at your teams’ fingertips, so expertise that lives in a few people’s heads reaches the whole operation.
Computer vision
Inventory optimization and warehouse stock management, with vision models that count, locate, and track stock automatically.
Data foundations
The trusted data layer manufacturing AI depends on. Clean, governed pipelines that make retrieval systems, agents, and vision models work in production.
Delivery and modernization
The engineering to get it built and running inside your environment, at your scale, under real load.
How we work
Assess. Brainstorm. Coach. Deliver.
Manufacturing work tends to fail on the unglamorous parts: documentation nobody trusts, data that never left the machine, expertise that lives in three people. We start there.
Assess
An honest read on where you actually stand, before anyone writes a roadmap.
Brainstorm
Options on the table with your people in the room, not a deck delivered to them.
Coach
We build the capability as we go, so the work does not leave when we do.
Deliver
Into your operating reality, running, owned by your team.
Common questions
Questions we hear often.
How is AI used in manufacturing?
In engineering and operations especially: helping test engineers troubleshoot faster, assisting field validation, putting institutional knowledge at teams’ fingertips, and applying computer vision to inventory and stock management.
What is a RAG troubleshooting pipeline?
Retrieval-augmented generation grounded in your own device and product documentation. Instead of an engineer searching manuals, they ask a question and get a sourced answer drawn from material you control.
What does a test-debugging agent do?
It assists a human engineer during field validation, proposing likely causes and next steps from prior cases and documentation. The engineer stays accountable for the call.
Where does computer vision pay off?
Usually in the warehouse before the line. Counting, locating, and tracking stock automatically tends to return value faster and with less risk than vision on the production process itself.
Next step
Bring it to your operations.
Book a consultation and we will find where this saves time and cost in your production environment.
Book a consultation