AI in production, under full control.
AI agents, private language models, computer vision and GeoAI taken from pilot to production, on premises or in the cloud.
01 Use cases
AI that does real work.
Each use case starts from a concrete problem and ends in a working result, all on the same private foundation, so one deployment serves many.
02 Reference architecture
Private AI, end to end.
Documents, data and imagery stay inside the controlled environment. Models run on dedicated hardware, on premises or in the cloud, answers cite internal sources and the model itself can be swapped without rebuilding the system.
Client perimeter · nothing leaves
Evaluation and monitoring run across the whole pipeline, against criteria agreed up front.
External AI services Not required
03 Pilot to production
Gates, not guesswork.
Most AI pilots stall between demo and production. Every stage here closes on an explicit gate, so a pilot either earns its way into production or stops early and cheaply.
-
Use case
Gate · Agreed scope
-
Evaluation set
Gate · Criteria signed off
-
Pilot
Gate · Criteria met
-
Hardening
Gate · Security review
-
Production
Gate · Go-live approval
-
Monitoring
Ongoing
04 Model registry
Models change. The system stays.
Open-weight models run locally by default; commercial models are added only where policy allows.
Ready to put AI to work?
Start from one real process and the data behind it. A pilot can be scoped from there, on infrastructure under full control.
Discuss an AI use case