Govern your AI — secure, traceable and private
Clear frameworks, measurable compliance and data sovereignty. Technology, process and accountability aligned.
What we solve
- • Unclear roles and decisions → governance and ownership in place
- • Uncertain risk/compliance → measurable assurance and audit trail
- • Privacy & vendor lock-in → private architecture and data sovereignty
What you take away
- • Governance model, roles and decision flows
- • Policy guards and risk framework
- • DPIA + control plan and audit trail
- • Architecture patterns & reference models (on-prem/private)
- • Measurable criteria & protocols (SUTS)
- • Training and shared vocabulary
Capabilities & programmes
We combine governance, assurance and private AI architecture — grouped into two capabilities with concrete programmes.
Governance & assurance
We establish disciplined decision-making, risk frameworks and traceability — from gap analysis to auditable runs.
Governance Blueprint
For: organisations that need clarity, ownership and disciplined decision-making.
You get: operating model for AI governance, roles and accountability, decision flows, policy guards, risk framework, reporting.
Deliverables: governance documents, RACI, policy pack, reporting templates and metrics.
Regulatory position & gap (AI Act and related)
For: leadership and teams who want to know where they stand and what it takes.
You get: gap analysis against applicable requirements, prioritised actions, choices and dependencies.
Deliverables: gap report, action plan, board brief.
DPIA & Risk Assurance
For: initiatives requiring traceability, auditability and defined risk levels.
You get: DPIA walkthrough, risk budgets, control plan, audit trail and attestation.
Deliverables: DPIA, control framework, log/lineage schema, audit pack.
Competence & architecture
We build internal capability and private solutions that endure — without cloud lock-in.
Training & capability building
For: leadership, legal, product and data/ML teams.
You get: practical governance and ethics in day-to-day work, case exercises, shared vocabulary.
Deliverables: sessions, materials, exercises, follow-up.
Private AI architecture (Atlas Labs)
For: organisations that need private, on-prem or controlled deployments.
You get: target states and reference patterns, segmentation and safeguards, data sovereignty without cloud lock-in, auditable operations.
Deliverables: architecture design, reference implementation/POC where appropriate, handover.
Applied research & validation
For: organisations exploring self-modelling/antifragility or seeking independent validation.
You get: hypotheses, experimental design, measurable criteria (SUTS), reproducible protocols and a reference implementation where appropriate.
Deliverables: working paper, benchmark protocol, executable artefacts, executive and audit report.
How we work
Tight and measurable – without unnecessary noise.
Frequently asked questions
Do you work on-prem?
Yes, and we avoid unnecessary data sharing.
Confidentiality?
We sign NDAs and use auditable runs.
What do you need to start?
A brief inventory and access to key roles is enough.