Design partner programme — six places
A new layer of security for the AI era.
Secure Shield Labs builds regulAIt — the platform where security and AI teams authorize, govern and evidence every model, agent and access path in production.
| Control | Name | Framework | Status |
|---|---|---|---|
| AC-2.3 | Session termination | SOC 2 | Failing |
| IA-5.1 | Credential rotation | ISO 27001 | At risk |
| CM-8.2 | Model inventory | EU AI Act | Passing |
| AU-12 | Agent action logging | ISO 42001 | Passing |
- SOC 2
- ISO 27001
- ISO 42001
- EU AI Act
- NIST AI RMF
- DORA
- HIPAA
The gap
AI is shipping faster than governance can follow
Three problems show up in every enterprise putting models into production. None of them are solved by another spreadsheet.
- 01
Models reach production before anyone owns them
A model goes live in a business unit, and the security team learns about it during the audit. Inventory is the first control and almost nobody has one.
- 02
Evidence is gathered by hand, then goes stale
Screenshots, exports and a shared drive. It survives one audit cycle and is wrong again by the next quarter.
- 03
Controls were written for software, not agents
Access frameworks assume a human behind every session. Agents hold credentials, take actions and change behaviour between reviews.
The layer
One layer between your stack and your auditors
regulAIt sits above the systems you already run. Nothing gets rebuilt, nothing gets replaced, and everything above the layer finally has one source of truth.
- Your board
- Your auditors
- Your regulators
- Identity providers
- Cloud & data platforms
- Model providers & gateways
- Agent runtimes
The suite
Six modules, one control plane
Buy one module or the suite. Each runs as its own system — what they share is one compliance vocabulary and one evidence format across every module, so a mapping made in one is legible to the others, and to your auditor.
regulAIt-Authorized
Access reviews, entitlement drift and identity compliance across every system of record — humans and agents alike.
Access & identityregulAIt-LLM
Build, evaluate and guardrail your own models and agents on your own data, with the evaluation record kept as evidence.
Build your ownregulAIt-Governed
Policies mapped to controls, controls mapped to evidence, monitored continuously rather than at audit time.
Policy & controlsregulAIt-Migrate
Move between frameworks and versions with mappings and evidence carried forward instead of rebuilt.
Join the waitlistregulAIt-Attested
Continuous audit evidence and attestation packs an auditor can accept without a working session.
Join the waitlistregulAIt-Observed
Runtime oversight for live models and agents — drift, abuse, cost and behaviour, watched continuously.
Join the waitlistDesign partners
Six places. Twelve weeks. A direct line to the team.
Secure Shield Labs was founded in 2026 and is choosing its first six design partners now. You get the platform at launch pricing held for two years, weekly access to the people building it, and real influence over the roadmap. We get to build against your frameworks instead of a guess.
Who the programme suits
Regulated enterprise deploying AI
Financial services, health, public sector — anywhere a model decision has to be defensible.
Platform team under audit pressure
You own the controls and the evidence, and the AI teams keep shipping past you.
AI team without a governance owner
Models in production, no one accountable for the paperwork, and a deadline arriving.
See it against your own frameworks
Thirty minutes, your control set, no sales sequence afterwards.