AI with judgement. Not with haste.
Average across projects run in our internal lab · limited sample · each case varies
Before production, the test bench.
Every use case goes through our internal lab: the client's own dataset, measurable evaluation, metrics that matter to the business — before touching production. No polished demo; just an ugly KPI that goes up.
Illustrative case based on an internal lab project, 2025. Actual values vary depending on dataset and production configuration.
Six ways to apply it.
None of these services are sold off the shelf. All begin with a measurable 6–8 week pilot. If the agreed KPI does not improve, it does not go to production.
Back-office agents
Multi-step task automation: invoices, returns, quotes, order handling.
Internal search (RAG)
Company knowledge, accessible via chat.
Voice & transcription
Calls, meetings, training. Transcription + analytics.
Computer vision
Inspection, counting, OCR for unstructured documents.
Forecast & planning
Demand, stock, capacity. Classic models + ML.
AI governance
AI Act compliance, traceability, audit.
Models that work.
No demos: production. These are the sectors where we have live models, measured and maintaining the agreed KPI.
What we deliver.
A sample. The details, metrics and before/after are on the case studies page.
View all case studies→Autonomous returns
High autonomy: most cases resolved without human intervention. Dramatic reduction in cost per case.
Read the case study →RAG · 14,200 documents
High accuracy with every answer cited to source. Substantial reduction in onboarding time.
Read the case study →Vision · welding defects
Very high recall on critical defects. Substantial improvement in line throughput.
Read the case study →“They told us that a particular case wasn’t solved by AI, but by a process change. That honesty is the reason we keep working with them.”
Intelligence is not bought: it is applied with judgement.