What this service solves
We design your company's AI governance framework: policies, controls, an internal committee and metrics aligned with the NIST AI Risk Management Framework, ISO/IEC 42001 and the European AI Act. We turn regulatory principles into operational practices that protect the brand, data and business as AI adoption scales.
Problems we solve
- Uncontrolled AI use by employees.
- Sensitive data exposed in public tools.
- A lack of criteria for approving new use cases.
- Emerging legal and reputational risks.
- The inability to audit decisions made by AI.
What's included
- A current risk diagnostic by area.
- Designing an acceptable-use policy.
- A governance committee and approval process.
- Technical and access controls.
- Audit logs and traceability.
- An internal training plan.
How we work
- An executive diagnostic of the current state.
- Designing the governance framework.
- Supporting the creation of the committee.
- Implementing technical controls.
- Training and periodic reviews.
How we work: service methodology
- Phase 1 · Shadow AI Audit and Risk Mapping (Week 1) — Diagnosing which AI tools employees are currently using and in which departments data-leak risks exist.
- Phase 2 · Drafting the Corporate AI Policy Manual (Weeks 1-2) — Creating the legal and operational document with permitted-use guidelines, strict prohibitions and anonymization protocols.
- Phase 3 · Implementing Technical Controls and Firewalls (Weeks 2-3) — Configuring network firewalls, secure API gateways and blocking vulnerable public tools; includes server hardening (UFW/Fail2Ban, SSH via Ed25519 keys with 2FA), Zero-Trust private VPN networks (WireGuard/Tailscale) and anti-prompt-injection guardrails (Llama Guard/NeMo Guardrails) for AI agents.
- Phase 4 · Training and Employee Agreement Signing (Week 3) — Awareness workshops on AI risks and formalizing confidentiality commitments with staff.
- Phase 5 · Delivering the Governance Framework, Pentesting and Continuous Monitoring Matrix (Week 4) — Delivering the compliance dossier, naming the Internal AI Ethics Committee, penetration testing, and a quarterly audit plan.
What we need from your team
- The company's current information-security and data-privacy policies.
- An inventory of software and digital tools used across departments.
- An inventory of servers, domains and active applications.
- A list of employees authorized for VPN access.
- No access to confidential production databases is required for the governance component; the infrastructure component does require temporary root access to servers for hardening.
Deliverables
- An approved AI policy.
- A documented governance framework.
- A committee and operating SOPs.
- Implemented technical controls.
- An audit log.
Who it's for
- Regulated companies or those aiming to operate in regulated markets.
- Organizations with sensitive customer data.
- Legal and compliance teams.
- Executives who need to safeguard AI adoption.
Signs you need it
- Employees are already using AI tools on their own, with no clear policy on what can be uploaded or queried.
- The company has no way of knowing which AI tools are circulating internally or what data has passed through them.
- There's no defined criteria for approving or rejecting a new AI use case before a team implements it.
- The board or legal team is worried a data leak could lead to regulatory penalties or reputational damage.
Measurable KPIs
- Approved and monitored use cases.
- Incidents avoided.
- Approval time for new use cases.
- Internal training coverage.
Expected outcome
The company adopts AI quickly but within a framework that protects the business: clear policies, an executive committee, technical controls and audit logs aligned with the most recognized international standards.
Technology stack
- NIST AI RMF
- ISO/IEC 42001
- EU AI Act
- Microsoft Purview
- Datadog
- Notion
- Confluence