AI code oversight
AI does not review its own work. We do.
Independent code oversight for engineering teams shipping with Copilot, Cursor, and AI-assisted development. Senior engineers. No automated scanners.
Independent AI code review for regulated and high-stakes software teams
Engineering leaders adopt AI coding tools to move faster — but velocity without oversight creates security, compliance, and architectural debt. Maxiom's AI code oversight service delivers structured human review by senior engineers who have shipped production systems in healthcare IT, federal, fintech, and enterprise environments. We evaluate AI-generated and AI-assisted code for OWASP risks, licensing exposure, maintainability, and regulatory alignment before your next audit, fundraise, or enterprise sale.
- 2002
- Founded
- $100M+
- Delivered
- 98%
- Satisfaction
The problem
Security gaps the AI did not flag
AI tools produce syntactically correct, functionally plausible code that can still contain injection vulnerabilities, insecure deserialization patterns, and improperly scoped authentication logic.
Architectural decisions that compound
AI tools optimize for the immediate task. They do not optimize for your system's existing architecture or the next 18 months of feature development.
Compliance gaps in regulated industries
HIPAA, SOC 2, FedRAMP: compliance requirements are context-dependent in ways AI tools cannot fully reason about.
What an AI code oversight engagement looks like
Senior engineers. Not scanners.
Every audit is conducted by engineers with 10-plus years of production experience. The scope covers security, architecture, compliance, dependencies, and test coverage quality, not just coverage percentage.
Security analysis
OWASP Top 10 plus AI-specific patterns including prompt injection in LLM-integrated code
Architecture review
Against your stated system design and roadmap
Compliance gap analysis
HIPAA/FHIR for healthcare, SOC 2 for SaaS, FedRAMP for federal
Dependency and licensing review
GPL contamination, unvetted OSS packages
Test coverage assessment
Coverage quality, not just coverage percentage
Readability and maintainability scoring
Structured scoring for long-term team velocity
The AI Code Risk Checklist
Security
- ·Injection vulnerabilities in AI-generated query construction
- ·Authentication and authorization logic gaps
- ·Hardcoded or improperly handled secrets
- ·Insecure dependencies introduced without review
- ·Prompt injection exposure in LLM-integrated features
Architecture
- ·Unintended coupling between modules
- ·Data model assumptions conflicting with existing schema
- ·Performance anti-patterns (N+1 queries, unbounded pagination)
- ·Missing error handling and edge case coverage
Compliance
- ·PHI handling that does not meet minimum necessary standards
- ·Audit logging gaps for covered transactions
- ·Data residency and encryption-at-rest assumptions
- ·Third-party integrations without compliant data agreements
Code quality
- ·Test coverage on security-critical paths
- ·Dead code and duplicate logic from AI regeneration
- ·Documentation accuracy vs. actual behavior
Download the full AI Code Risk Checklist
Is this right for you?
The accelerating team
Your team adopted AI coding tools and delivery velocity increased. You are not sure whether your review quality kept pace with your review speed.
The compliance moment
You are in healthcare, fintech, or federal contracting. A compliance review or customer security questionnaire has surfaced questions about AI-generated code in your stack.
The high-stakes inflection point
You are approaching a fundraise, an enterprise sales cycle, or an acquisition. Someone is going to look at your code.
How our AI code oversight engagement works
- NDA signed before access
- Read-only repository only
- Senior engineers every time
- Report in 10 business days
Frequently asked questions
What is AI code oversight?
AI code oversight is independent technical review of code produced or heavily assisted by AI tools such as GitHub Copilot and Cursor. Senior engineers evaluate security, architecture, compliance, dependencies, and test quality — not just syntax or lint results.
Who needs an AI code audit?
Teams in healthcare, fintech, federal contracting, and enterprise SaaS who use AI coding tools and face customer security questionnaires, compliance reviews, due diligence, or production incidents tied to unreviewed AI output.
How long does an AI code review take?
Standard engagements share initial findings within five business days after read-only repository access and scoping. Timeline depends on repository size, stack complexity, and regulatory scope.
Does Maxiom run client code through third-party AI tools during the review?
No. Client code stays in client environments. Reviews use direct inspection by senior engineers — not automated scanners or third-party AI processing of proprietary source.
What does an AI code oversight deliverable include?
A written findings report with severity-ranked issues across security, architecture, compliance, dependencies, and test quality — plus a live debrief and prioritized remediation guidance from a named senior engineer.
Which AI coding tools do you review for?
Engagements commonly cover GitHub Copilot, Cursor, Claude-assisted workflows, and similar AI coding assistants. Scope is based on how your team actually generates and merges code, not a single vendor list.
Can AI code oversight cover HIPAA, SOC 2, or FedRAMP concerns?
Yes. Reviews can include compliance gap analysis mapped to your framework — HIPAA/FHIR for healthcare, SOC 2 for SaaS, and FedRAMP/NIST alignment for federal environments.
How is access handled for an AI code audit?
NDA first, then read-only repository access by default. Least-privilege permissions are scoped to the engagement; build access is only added when remediation work requires it.
Is AI code oversight different from vibe coding governance?
Yes. AI code oversight focuses on teams already shipping with AI tools who need ongoing or point-in-time senior review. Vibe coding governance assesses products built primarily through AI prompting for production readiness before fundraise, launch, or team inheritance.
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