A sovereign RAG + Agents platform with governance built in
A self-hostable enterprise AI platform that unifies retrieval-augmented generation, autonomous agents and AI governance — so organizations can adopt generative AI on their own infrastructure without surrendering their data.
The problem
Enterprises in regulated sectors want the productivity of generative AI, but cannot send confidential data to third-party APIs, and have no unified way to govern how models are used. The result is shadow AI, fragmented tooling and unmanaged risk.
Approach
Rather than another chat wrapper, the platform treats generative AI as production infrastructure. It combines three layers — a retrieval layer grounded in the organization's own knowledge, an agent layer for multi-step tasks, and a governance layer that makes usage observable and controllable — all deployable on the client's own cloud.
- RAG grounding over private, sovereign knowledge bases
- Agent orchestration for multi-step, tool-using workflows
- Governance and LLMOps for observability and control
Architecture
A decoupled architecture separates the Next.js experience layer from a FastAPI service layer, with model access, retrieval and agent orchestration behind well-defined APIs. Everything is containerized and orchestrated on Kubernetes so it scales horizontally and runs identically from a laptop to a production cluster.
- Next.js front end · FastAPI back end
- Containerized services orchestrated with Kubernetes
- Automated CI/CD for reproducible releases
- LLMOps/MLOps hooks for monitoring and evaluation
Deployment
The platform ships as containers with CI/CD pipelines, so it can be deployed into a client's own environment and updated safely. Sovereignty is the design constraint: data and models stay where the organization controls them.
Business value
The platform gives regulated organizations a single, governed path to adopt generative AI — grounded in their own data, orchestrated for real workflows, and operable by their own teams. It collapses what is usually a multi-vendor integration effort into one coherent, self-hosted system.
Lessons learned
Governance cannot be an afterthought — observability and control belong in the architecture from day one.
Sovereignty (self-hosting) is often the deciding factor for regulated buyers, ahead of raw model quality.
Separating the experience layer from the model/agent layer keeps the system adaptable as models change.