AI Implementation
Build the system.
Inspection workflows, work-order document AI, operational assistants and agents, delivered with acceptance testing, monitoring and rollback.
AI data, evaluation and implementation under one accountable delivery model.
Contact us Become a ContributorIndustrial & Energy
Inspection, work-order intelligence, operational assistants and agents, built into production and trained on data captured in your own plant.
Why industrial AI stalls
The failure that costs you is the one nobody saw. A model watching your line has to know your failures, and be proven before it touches operations.
Generic datasets are full of good parts. Your cost lives in the rare weld defect and the sensor that drifts before it fails. Data never captured on your line cannot teach a model your failures.
On a live line a wrong action is worse than a wrong answer. Assistants and agents run inside approval gates, hand off to your people and stop at the safety boundary.
An evaluation set that represents your line, acceptance against agreed criteria, regression on every change, rollback after release. Nothing ships on impression.
What you can buy
System Data
AI Implementation
Inspection workflows, work-order document AI, operational assistants and agents, delivered with acceptance testing, monitoring and rollback.
Data Collection
Sensor streams, industrial audio, camera video, rare events and robot episodes, collected in your environments with consent and provenance on every file.
Operated from Norway, with EEA processing where required.
One inspection · frame to verdict to record
A model trained on frames from your line lands a flag. A reviewer rules on it. The verdict is logged with its lineage. Green appears only where a person has ruled.
Trained on your defect classes and rare events, calibrated before production.
Captured on your line, by the cameras you run, under your light. Your parts, not a catalogue's.
Every routed flag gets a human ruling, logged with its frame, model version and reviewer stage.
Before a vision model is allowed to flag on your line it passes a calibration gate: video annotation behind HOTA 0.65+ / IDF1 0.75+, and five-stage consensus QA with Cohen and Fleiss Kappa inter-rater scoring on the data it learned from.
Screen contents are illustrative. Defect taxonomy, severity scale and acceptance thresholds are set per line in the project specification.
Where it applies
Four systems we build most often, opened. Each runs on different data, captured inside the plant's own rules, and each stops where your people rule.
A model that flags what your cameras see, and a reviewer who rules on the flag.
Maintenance paperwork turned into a controlled workflow, with review where it belongs.
Assistants that answer from approved procedures and manuals, and escalate by your rules.
Machine and robot data made trainable, and agents that act only inside approval gates.
Connected Delivery
Observe the miss A flag the reviewer rejected, or a defect the model waved through.
Isolate the gap Which defect class, shift, camera or sensor the training set never saw.
Capture the data Collected on your line, to quota, with provenance on every file.
Improve the system Retrained, re-gated and re-integrated behind the same approvals.
Rerun the evaluation The same evaluation set, plus the miss, before anything ships.
Release Into operations with monitoring and rollback. Then the next miss.
A defect class the cameras never captured, a sensor that drifted, an evaluation set that does not represent the line. No hand-off between an integrator, a model vendor and a collection company. Each line remains independently purchasable.
Where the data lives
A Norwegian company under GDPR. Your project data is stored in Europe by default and processed in the EEA where required, with the paperwork to prove both.
Scope a project
We scope against your workflow, write the specification with you and prove the loop on a pilot batch before anything touches operations.
A bounded pilot carries its own acceptance criteria. You judge the output against your line, not against a slide.
Briefs are treated as confidential. We are used to plants that photograph badly and fail rarely.
The brief Tell us the line, the failure modes that cost you, and the data or system you need. We reply with a feasibility read.