Sovereign AI Platform

Data-sovereign AI platform. Auditability that meets the AI Act.

Verisa is a sovereign on-premise AI platform with graph-native reasoning — every conclusion traces back to a concrete reference. Aligned with EU regulation, built by Entel — a 36-year-old independent Hungarian deeptech vendor.

Two products on one sovereign infrastructure.

Verisa AI is the agent platform. Verisa Flow is the knowledge-management and AI orchestration tool.

Verisa AI

Sovereign AI with graph-native reasoning
  • On-premise. Air-gapped if you need it. Your data never leaves your infrastructure.
  • Frontier-grade retrieval — Verisa's ARTIS module reaches 94.7% Hits@10 on the public MultiHop-RAG benchmark, the best published result to date.
  • EU AI Act–ready auditability, hardware-key licensing, source code escrow.
Verisa AI

Verisa Flow

Knowledge management and AI orchestration tool
  • Five domains, one engine — code, documentation, research, legal, process.
  • Multi-model consensus and graph-backed structural verification.
  • Legal AI support — graph-native legal reasoning, where every answer traces to a specific law, paragraph, or precedent.
Verisa Flow

Built for regulated work

Sovereign
By configuration
Cloud, on-prem, gov network, air-gapped
Zero
Egress
Air-gapped deployment supported
5
Workflow domains
Code, Docs, Research, Legal, Process
EU
AI Act ready
Audit trail, conformity scaffolding

Why Verisa?

Direct answers to the questions regulated buyers actually ask.

Your data stays in your infrastructure.

Fully on-premise or air-gapped. Vendor-bound automatic data transmission and telemetry (phone-home) is blocked entirely, and a user-side data loss prevention (DLP) integration is in place. The isolated operating and deployment mode is enforced in code, not promised in a sales slide.

Explainable AI (X-AI) and auditability.

Every answer's reasoning path is traceable, the inference is auditable, and the use of training data is recoverable through the graph-native representation.

Multiple AI models check each other.

Multi-model consensus with structured disagreement handling, human decisions in the loop, fully logged.

Built in the EU, regulation-aligned.

Multi-language UI and speech recognition. eIDAS-based identity, with national identity integrations on request. EU AI Act conformity. EU-sovereign foundation models when you need them.

Cryptographic audit trail.

TLS 1.3, mTLS between services, SHA-3-256 hash-chained audit log, hardware-rooted licensing, source code escrow.

Five domains, one orchestration engine.

Code, documentation, research, legal, process — the same knowledge-management methodology, used intuitively and securely on a single workspace, native desktop app, with a Microsoft Word add-in and further auxiliary tools.

How it works

From a complex requirement to a verified, delivered artefact.

01

Define

Pick the workflow mode. Verisa decomposes the work into sequenced tasks against an explicit spec when coding, or runs built-in pipelines and macros for knowledge-management tasks.

02

Generate

Each task goes to the right model — fast or capable, cloud or local, as your settings dictate. Multiple models run in parallel.

03

Verify

Cross-model consensus plus graph-backed structural verification. Tests, compliance checks, style standards. The system does not blend model disagreements into a single averaged answer: every divergence is flagged explicitly and routed to human decision.

04

Deliver

Verified artefacts move into your delivery pipeline — CI/CD, document publishing, approval workflows, compliance registries — with the audit trail attached.

Five domains, one engine

The same methodology, configured per domain. Tabs for parallel work, native desktop app, multi-platform messaging gateway for remote control.

Code

Spec-driven AI coding. Multi-model consensus, automated tests, CI/CD. Pre-commit checking rejects the commit if the AI modified files outside the active task's scope.

  • Architect / Developer / Reviewer / QA agent roles
  • Auto-generated unit tests
  • Cryptographic audit log of every AI-generated change

Example

"A small team ships a full-stack API with architectural guidance, automated review, and deployment automation — without a senior engineer on every keystroke."

See it in action

Methodology-driven orchestration with multi-model consensus and graph-backed verification.

terminal
$ verisa-flow start --mode code --project my-api
[Architect] Decomposing task into 4 subtasks...
[Developer] Generating auth module...
[Reviewer] Consensus review (cross-model)...
[QA] Running 12 unit tests... All passed.
[Pipeline] Pushing to staging via GitHub Actions...
output
Consensus: 3/3 agents agree (high confidence)
Validation: 12/12 tests passing
Pipeline: deployed to staging
Design sync: HLD updated (DESIGN-017)
Ready for production deployment.

Talk to us about your AI infrastructure.

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