We start from a reusable technology core and configure it according to each organization's domain, AI maturity, existing systems, criticality level and governance requirements.
We don't tell the same story to a public administration, a corporation running multiple AI platforms and an SME that needs to launch a first useful use case.
Cross-cutting scalability, reuse of public knowledge, sovereignty, traceability and support for both citizens and case-handling staff.
Connect an existing AI ecosystem, reduce silos and lock-in, keep control of the cognitive asset and expand domain by domain.
Adopt AI in an orderly way without oversizing the architecture, leaving reusable knowledge for future use cases.
Solutions are configured by combining a shared knowledge foundation with context, operations and governance capabilities, as each case requires.
Capture, structure, reconcile and govern knowledge, relationships, rules and evidence so they can be reused consistently.
Provide every query, agent or workflow with the relevant, authorized and traceable context its task requires.
Enable assistants, AI Specialists, agents and vertical solutions with evidence, permissions, traceability and human oversight.
Keep knowledge up to date, validated, versioned and auditable as the organization and its use cases evolve.
Each page covers its own challenges, adoption patterns and use cases.
Scale AI with a reusable, governed knowledge infrastructure.
Govern and connect copilots, agents, platforms and knowledge on a shared foundation.
Better-structured AI from the start, without building a complex stack.
Not every project needs all of GenInContext. The assistant can help you identify which foundation, specialists and integrations would be relevant.
The architecture is modular: we can adapt the entry point to your actual domain, maturity, systems and criticality.
