Govern AI. Before It Governs You.
- One unguarded AI decision in public administration can breach citizen trust, violate privacy law, and make tomorrow's headlines.
- Governance isn't a policy document — it's enforceable rules at every AI interaction, wherever your institution operates.
- vlinq is purpose-built for public sector: sovereign infrastructure, privacy-regulation-compliant, audit-ready from day one.
The Responsible AI Imperative
Ungoverned AI creates unique accountability obligations — driven by systemic risks reshaping public sector policy worldwide.
Monitoring Paradox
Frontier models struggle to follow internal safety instructions, creating invisible compliance gaps.
Industrial Accident Risk
AI failure shifts from predictable errors to chaotic, incoherent breakdowns with unpredictable consequences.
Regulatory Shift
Governments are moving from Ethics Principles to Mandatory Operational Playbooks.
Where It Matters
Document Intelligence
Text optimization, summarization, and transcription of official correspondence with full audit trails and FADP-compliant data handling.
Tax Administration
Explainable, rule-based AI where legal accountability is mandatory, meeting Swiss tax authority standards.
Building Permits
Specialized AI for faster processing using public data, ensuring full traceability and citizen-safe outputs.
Social Services
Privacy-laws compliant PII/PHI handling and classification, with redaction enforced at the infrastructure layer.
Three Strategic Pillars
Modeled after the Swiss Federal AI Strategy — a framework for responsible public sector AI adoption.
Build Skills
Train staff, develop internal AI literacy, and build expertise to evaluate vendor claims.
Earn Trust
Use AI responsibly, ensure legal and ethical alignment, and never skip human review for high-stakes decisions.
Increase Efficiency
Relieve staff of routine tasks and free up judgment for politically sensitive cases.
Multi-Layer Safeguards
Every workstream is protected before, during, and after model invocation — no exceptions.
Input Safeguards
Input validation, prompt injection screening, PII/PHI/secrets detection and redaction, and authentication boundary enforcement.
Runtime Safeguards
Policy-based profile routing, tool-call allowlists, rate limits, token caps, and step-level trace capture.
Output Safeguards
Safety and toxicity classification, factuality and grounding checks, structured output schema validation, and human review gates.
Every Workstream is a provider-agnostic AI container embedding compliance routing, all three safeguard layers, rate limits, accountability policies, and audit trace capture — protecting data privacy and building citizen trust.
Neuro-Symbolic Integration
We combine the reasoning power of Large Language Models (LLMs) with the absolute precision of Knowledge Graphs. Our engine injects symbolic logic into neural workflows to guarantee compliant outcomes.
Includes best practices for Safe and Responsible AI
Built for Public Administration
Purpose-built for the governance, accountability, and compliance requirements of public institutions worldwide.
Public Administration
For government bodies, municipalities, national departments, and public institutions seeking sovereign AI governance aligned with local law and data residency requirements.
- Sovereign deployment — data processed and stored in your jurisdiction
- Aligned with local data protection regulations
- Explainable AI decisions with full audit trails
Ready to get started?
Reach out to discuss how vlinq can be tailored to your institution's specific requirements.
Request a DemoSingle-Box Docker
Deploy in minutes on your infrastructure. Zero-dependency runtime.
Enterprise-Grade Security
Engineered with precision and privacy-first principles.
Cloud-Agnostic
No lock-in. Works across AWS, Azure, GCP, or on-premise air-gapped systems.
Open Source at Heart
We believe the best software is built in the open. Open source is not a strategy — it is how we work.
Built on Open Source
vlinq is built on a foundation of world-class open source projects. From our runtime to our security primitives, we rely on the collective intelligence of the open source community to deliver a product that is robust, auditable, and freely inspectable. We are transparent about our dependencies and vet every library we adopt.
- Core runtime built on open source components
- All dependencies publicly disclosed
- Reproducible builds for full supply-chain auditability
Giving Back
We actively contribute upstream to the projects we depend on. Bug fixes, documentation improvements, security patches — if we find something that benefits the community, we send it back. Our engineers are encouraged to participate in open source maintenance as part of their regular work.
- Regular upstream bug fixes and patches
- Security disclosures follow responsible processes
- Engineers contribute on company time
Publishing Our Own Work
Where it makes sense, we release our own tools and libraries as open source. We believe that tooling around AI governance, observability, and safety should be a public good. Releasing our work allows the wider community to audit, extend, and build upon what we create.
- AI governance tooling released publicly
- Community-driven roadmap for open components
- Permissive licences where possible