Operational AI
AI applied to real processes: copilots, internal assistants, and intelligent automation wired into your systems — not empty demos.
Operational AI in depth
What we do with generative AI, ML, assistants, and copilots
Operational AI requires context: private data, permissions, business rules, reports, and processes. That is why we design assistants and copilots connected to real systems.
LLMs, corporate RAG, permissions, and traceability
Generative AI solutions wired into private data with RAG, access controls, and traceability. No chatbots floating outside the client's context.
- LLMs
- Corporate RAG
- Citations
- Permissions
- Continuous eval
- LLMs grounded on private data with corporate RAG.
- Answers with citations and traceability to the source.
- Access controls per role and per domain.
- Deployment in private cloud or dedicated VPC.
- Continuous evaluation of responses.
When it applies
Useful AI, not empty demos
AI only delivers value when it connects to real processes, private data, and explicit business rules.
- Assistants connected to corporate data, not the open internet.
- Measurable use cases — not infinite labs without a deliverable.
- Human-in-the-loop before any sensitive action.
- User permissions respected by the AI layer.
- Traceability of every answer back to the source data.
- Operational MLOps with model monitoring and controlled deployment.
What we deliver
What we deliver
Each commitment is documented as a deliverable that can be reviewed, audited, and operated.
- Use cases prioritized by operational impact.
- Assistants and copilots over private data.
- Corporate RAG with access controls.
- Productive ML models with monitoring.
- Evolution plan and new use cases roadmap.
Next step
Want to build software, integrate SAP, or pilot an Enterprise Copilot?
We help diagnose the case, define a focused scope, and assemble the right team. Clear communication, without vague promises.