01 / 03Security & Governance
AI Risk Assessment
Every AI system mapped against the risks it actually introduces, before regulators or customers find them for you.
Risk scoringBias testingExecutive readout
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AI you can actually govern.
Risk assessments, security audits, and compliance frameworks for every model you ship.
What's included
Three ways we keep AI accountable.
02 / 03Security & Governance
Model Security Auditing
Red-team your models the way you'd pen-test an app, prompt injection, data leakage, and jailbreaks, all covered.
Prompt injectionData leakageAdversarial testing
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03 / 03Security & Governance
Responsible AI Compliance
Documentation and controls mapped to the frameworks that matter, so audits are a formality, not a fire drill.
Policy & docsFramework mappingAudit-ready
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The process
How a governance engagement runs.
Step 01
Discovery & risk mapping
One call, a shared doc, every AI system in scope mapped against its actual risk profile.
Step 02
Framework selection
We match your systems against the right standards (NIST AI RMF, ISO 42001, EU AI Act) instead of every standard at once.
Step 03
Assessment & testing
Red-team testing, bias checks, and control gap analysis, run against your actual deployed systems.
Step 04
Remediation plan
A prioritized fix list, ranked by risk and effort, not a 200-page report nobody reads.
Step 05
Ongoing monitoring
Scheduled re-assessments and drift monitoring so today's clean bill of health doesn't expire quietly.
Built on
The tools we use to assess, monitor, and govern AI systems.
OpenAIAnthropic ClaudePythonHugging FaceLangChainWeights & Biasesscikit-learnDatadog
Why us for this
Governance done the way it should be.
We test for how models actually fail, not a compliance checkbox.
Every finding comes with a fix, not just a flag.
You own every report, policy, and control document.
One fixed quote, no meter running on scope creep.
Often paired with
Round out the program.
The services teams usually add before or after a governance engagement.
Questions
AI Security and Governance, answered.
Yes. We audit third-party and vendor models the same way, you don't need to have built it in-house for us to assess it.
Whichever apply to you, NIST AI RMF, ISO/IEC 42001, the EU AI Act, or an internal policy you're building from scratch. We'll tell you which actually matters for your risk profile.
A risk assessment in 2–4 weeks, a full security audit in 3–5, and a compliance program from 2–3 weeks for policy documentation up to 6–8 for a full governance program.
Both. Every engagement ends with a prioritized remediation plan, and we can implement the fixes ourselves if you want.
No. Any AI system handling customer data, money, or decisions benefits from this, regulation just makes it mandatory sooner for some industries.
A clear, proven process
Model risk.
Under control.
Audits, red-team, policy. Fixed quote in 48 hours, then evidence pack the same sprint.
The processbrief → first staging build in ~2 weeks
01Send the briefWhat you’re building, in a paragraph.5 min
02Get a fixed quoteScope, price, and date, locked.48 hrs
03Watch it take shapeA new build to staging every week.weekly
04Ship to productionLive, handed over, and supported.live
team onlineavg reply 1h 47m