AI Safety & Compliance Layer
Your team adopted Cursor and Copilot. Great. But who's validating the AI-generated infrastructure code before it hits production? Nobody. That's the blind spot.
What It's Costing You
AI-assisted developers ship plausible-but-wrong code faster than any reviewer can catch it. The risks compound silently until an auditor or incident surfaces them.
- Security risk: AI-generated code with subtle vulnerabilities, hardcoded secrets, permissive IAM defaults
- Compliance risk: auditors asking "How do you validate AI-generated code quality?" — and nobody has an answer
- Operational risk: inference pipelines deployed without cost controls or rollback plans
- Supply chain risk: AI-suggested dependencies pulled in without provenance review
Three Ways In. One Safety Net.
Start with a one-week audit that maps your real AI code exposure. Scale into a validation pipeline that gates every PR. Evolve into governance that grows with your stack.
AI Code Safety Audit
One-week inventory. Find the real risks before the auditor does.
- AI Code Inventory
- Code Quality Scan
- IaC Validation Assessment
- Compliance Risk Mapping
- Supply Chain Security Review
- Policy-as-Code Readiness Score
- Critical Finding Summary
AI Validation Pipeline
Ship a pre-production gate that validates every AI-touched artifact.
- Pre-production review pipeline
- Policy-as-code for IaC (OPA, Conftest, tfsec)
- Drift detection & auto-rollback
- Inference validation harness
- Compliance dashboard
- Secret-scan integration & SBOM
AI Governance Operations
Governance that keeps up with your AI adoption curve.
- Ongoing monitoring of AI-touched code
- Compliance dashboards & audit prep
- Policy evolution as tools change
- Incident response for AI-linked failures
- Developer training & guardrails
- Quarterly board-ready risk reports
The 5-Day Assessment Process
A structured week: inventory, scan, risk mapping, and a concrete critical-findings readout you can hand to your CISO.
Connect read-only tooling. Catalog where AI is touching code (PR stats, extension usage, IaC repos).
Run static analysis, secret scans, SAST across AI-authored commits.
Terraform / K8s manifest assessment, policy-as-code readiness, drift exposure.
Map findings to SOC 2 / ISO 27001 / internal controls. Prioritize by blast radius.
Readout, critical-findings report, policy-as-code roadmap, Build proposal if fit.
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Platform Engineering Rescue
AI code gates land best when the platform already has policy-as-code wired in. Fix the platform, the safety layer lands naturally.
Explore Platform Engineering Rescue →Unified Delivery Pipeline
When AI ships both code and models, you need one pipeline that validates both. Same gates, different artifacts.
Explore Unified Delivery Pipeline →