AI Governance
Pass the AI risk review.
Close the enterprise deal.
We run engineer-led technical audits, model risk assessments and compliance mapping for your AI systems, then hand you audit-ready documentation that clears enterprise procurement.
Aligned with ISO/IEC 42001, NIST AI RMF, the EU AI Act and SOC 2.
Engineer-led audits. No code changes required.
The pinch point
Procurement is stalling
your AI revenue.
The buyer is sold on the product. The deal still waits on an AI risk review nobody on your side is ready to answer.
The questionnaire wall
The questionnaire wall
Your champion is convinced, then the CISO and legal counsel drop a long AI risk assessment into the thread. The deal pauses on answers you do not have ready.
High-risk regulatory doubt
High-risk regulatory doubt
Buyers want proof of EU AI Act alignment, data boundary isolation and guardrails against hallucination before they will sign.
Engineering pulled off product
Engineering pulled off product
Your engineers lose days writing model cards, tracing data lineage and answering GRC questionnaires instead of shipping.
What you can run
Production-grade governance,
without the overhead.
Fixed-scope sprints, built for fast turnaround and audit clearance.
Enterprise deal-closer sprint
For AI startups stuck in mid to late-stage enterprise procurement.
What we audit
- LLM and RAG data flows, prompt logging, telemetry and vector store isolation.
- Third-party dependencies: API endpoints, training-data usage and retention.
What you receive
- Enterprise trust dossier: technical responses to AI security questionnaires.
- System model card: architecture, foundation models, latency and fallback policy.
- Data boundary policy: proof that client data never trains external models.
Framework readiness sprint
For scale-ups that need formal ISO 42001, EU AI Act or NIST AI RMF readiness.
What we audit
- System classification and EU AI Act risk tiering.
- Bias, fairness and drift monitoring, and prompt injection resilience.
What you receive
- Gap analysis and remediation roadmap, with precise engineering steps.
- AI risk register and controls matrix, mapped to ISO 42001 and NIST AI RMF.
- Conformity and verification pack, ready for a third-party certifier.
Red teaming and safety assessment
For engineering teams hardening a system before an enterprise launch.
What we audit
- Adversarial prompt injection, data extraction and jailbreak testing.
- Guardrail tuning benchmarks across your live configuration.
What you receive
- Vulnerability report with reproducible cases and severity.
- Guardrail tuning benchmarks and mitigation recommendations.
The artifacts
Everything you hand
to a buyer.
Every sprint ends in documents written by engineers, ready to forward to your prospect's security and legal teams.
Enterprise trust dossier
Technical answers to AI security questionnaires.
System model card
Architecture, foundation models, latency and fallback.
Data boundary policy
Proof that client data never trains external models.
AI risk register
Risks and controls mapped to ISO 42001 and NIST AI RMF.
Conformity pack
Audit-ready evidence for a third-party certifier.
Red-team report
Reproducible vulnerability findings and mitigations.
How it works
A process that respects
your engineering time.
Three steps, scoped to pull as little from your team as the work allows.
45-minute pipeline review
We review your architecture, data pipeline, model configuration and your buyer's requirements, under NDA.
Independent technical audit
Our engineers map data flows, run adversarial tests, check retention boundaries and verify guardrail performance.
Enterprise-ready dossier
You receive client-facing compliance collateral, complete model cards and direct answers to your buyer's questionnaire.
Proof of work
See what enterprise-grade
AI transparency looks like.
A sanitized enterprise trust dossier and model card, from a healthcare and fintech RAG architecture. See the depth, and reuse the structure with your own prospects.
Request the sample dossierEnterprise trust dossier and model card
Healthcare and fintech RAG architecture, anonymized
1. System classification and EU AI Act risk tier
2. Foundation models, versions and fallback policy
3. Data boundary and retention controls
4. Guardrails, evaluation and red-team results
5. Control mapping: ISO 42001 and NIST AI RMF
Frameworks we cover
We speak your
legal team's language.
Bring any regulation or contract and we map it to controls your auditor recognises.
EU AI Act
Prohibited and high-risk conformity assessments, and GPAI transparency.
ISO/IEC 42001
AI management system readiness, and support through certification.
NIST AI RMF 1.0
Govern, Map, Measure and Manage controls, mapped to your systems.
US state AI laws
Colorado AI Act, SB 205, and California automated decision rules.
Privacy integration
GDPR, CCPA and DPDPA cross-compliance for the data behind your AI.
SOC 2 AI addendums
AI-specific control responses that extend your existing SOC 2 scope.
Why Kensara
Depth where others stay shallow.
Questions
Questions enterprise buyers raise.
Do you need our source code or customer data?
No. We review data-flow architecture, API endpoints, telemetry logs and configuration under a mutual NDA. We never touch raw client data.
Can you answer our buyer's specific questionnaire?
Yes. Send us the document your prospect provided, and we formulate the technical responses, backed by architectural evidence.
Does this help if we pursue SOC 2 or ISO 42001 later?
Yes. Every artifact maps to standard control libraries, so your auditor gets structured documentation when you move to certify.
Who runs the audit?
Engineers, not account managers. The same people who map your pipeline write the responses your buyer reads.
Ready when your deal is
Have a deal waiting on
AI risk clearance?
Do not let the pipeline freeze. Our engineers build your compliance dossier while the deal is still warm.