Built to be trusted: every answer traces to a published rule.
Folaint is auditable, EU-sovereign and interoperable by design. It runs on your own infrastructure, your data never leaves your environment, and the open foundation underneath means no lock-in.
Trust is a property of the architecture, not a promise.
Runs on your infrastructure
On-premise by default. Open-source models only: your prompts never reach a US cloud AI provider.
EU-sovereign by default
Hosted in Europe, GDPR-respecting, built to align with the EU AI Act.
Every answer is traceable
Full provenance to the source document or system, auditable when it counts.
Open standards, no lock-in
RDF / OWL / SHACL. You can export and keep your foundation.
For your most sensitive workloads.
On-premise and EU-sovereign cloud are the baseline. When a workload demands more, two options go further.
Air-gapped
Runs with no path to any outside network — the whole system stays inside your perimeter.
- No external network paths
- Offline, signed updates
- Strict audit trails
Confidential compute
Data stays encrypted even while in use — processed inside hardware-isolated enclaves.
- TEE-protected workloads
- Encrypted memory & attestation
- Secure ML inference
What’s in place today, and what is still on the way.
These reflect our current wireframe roadmap, the posture we are building toward, stated plainly rather than overclaimed.
Principles you can hold us to.
Defaults that hold up under scrutiny, in place from the start rather than bolted on after the fact.
Data minimization
We hold only what an answer needs, for only as long as it needs it.
Encryption in transit and at rest
Standard, everywhere, not a premium tier.
Role-based access control
People see what their role permits, and nothing beyond it.
Full audit logs
Who asked, what was answered, and which sources it drew on, all recorded.
Your experts approve what becomes truth
Nothing enters the graph as fact until a named person signs off.
The model is never in the deterministic path
Rules and provenance decide the answer; the model helps phrase it, not judge it.
Open-source models, on premise
We run only open-source language models on your own infrastructure. Your prompts never touch OpenAI, Azure AI, Google Vertex, or any US cloud provider, because the architecture leaves them no way there.
The same conviction runs through everything we build.
Security here isn’t a checklist we run at the end; it follows from how the system is made. If that matters to you, let’s talk about it directly.