Align
Scope · 30 minutesWe map stack, AI tools in use, risk windows, and which repos or PRs matter most.
- Tools and teams generating code
- Repos, PRs, and risk windows
- Diligence or production trigger
You get: agreed review boundaries
AI-generated code review
Independent review of Cursor, Copilot, and Claude Code output — security, architecture, data handling, and ship-readiness — before production users, enterprise buyers, or investors dig in.
AI coding tools accelerate delivery. They also produce confident-looking code that can miss auth boundaries, leak secrets, invent architecture, or skip error handling. Maxiom's AI-generated code review puts a senior engineer on the diff — not a linter report — so you know what is safe to ship, what must be fixed, and what needs an owner before the stakes rise.
The problem
AI tools generate plausible implementations that can still miss authorization checks, mishandle secrets, or encode the wrong business rule.
When every engineer ships with AI assistance, review capacity becomes the bottleneck — and silent risk accumulates in the main branch.
Enterprise security review, investor diligence, or a production incident forces a hard look at code nobody fully owned.
What we review
We inspect the code that matters for risk — not every cosmetic change — and score what must change before you ship with confidence.
AuthZ gaps, injection surfaces, credential leakage, insecure defaults, and dependency risk in AI-assisted changes.
Whether generated features fit the system, create coupling debt, or break boundaries that will hurt at the next scale step.
Error handling, idempotency, logging, retries, and failure modes that demos never exercise.
Whether a human team can understand, test, and extend this code without reverse-engineering the prompt history.
Velocity is up. Review bandwidth is not. You need a senior pass on AI-heavy PRs before they become production debt.
The MVP was built fast with Copilot and Claude. Real users and real data are next. You need to know what breaks first.
Investors or enterprise buyers will ask how AI-assisted code is governed. You need findings and a remediation story — not a shrug.
Kickoff
We map stack, AI tools in use, risk windows, and which repos or PRs matter most.
You get: agreed review boundaries
NDA signed, least-privilege repository access, review boundaries confirmed.
You get: a bounded review, not a full rewrite
Engineers inspect AI-assisted code paths, document severity-rated findings, and map fix priority.
You get: findings with a remediation story
Written findings, remediation roadmap, and a live walkthrough — with optional Maxiom fix engagement.
You get: a packet for diligence or the next release
Written findings and remediation roadmap. Best when your team can close issues internally.
Maxiom closes critical findings after the review. Best when velocity matters and senior fix capacity is thin.
A senior engineer review of code produced or heavily assisted by tools like Cursor, GitHub Copilot, and Claude Code. We evaluate security, architecture, reliability, data handling, and maintainability — then deliver severity-rated findings and a remediation plan.
AI Code Audit is a formal point-in-time findings package for broader AI-assisted codebases, often tied to enterprise sale or compliance deadlines. AI-generated code review is the sharper commercial engagement for teams that want a senior pass on recent AI-written work before merge, launch, or fundraise.
Vibe Coding Governance assesses products built primarily through prompting with limited engineering process. AI-generated code review fits established or emerging teams that already use AI tools inside a repo and need senior judgment on specific output before it ships.
Cursor, GitHub Copilot, Claude Code, ChatGPT-assisted PRs, and similar AI coding workflows. The review targets the resulting code and architecture — not the vendor brand.
A written findings report with severity ratings, concrete examples from your repo, prioritized fixes, and a live debrief with a senior engineer. Optional remediation can follow.
No. Review uses read-only repository access and direct senior engineer inspection. Proprietary source is not processed through third-party AI tools.
Before a production launch with real user data, before a security questionnaire or enterprise sale, before Series A diligence, after a large AI-assisted feature lands, or whenever an incoming engineer will inherit AI-heavy code.
Yes. Engage for review only, or review plus remediation where Maxiom closes critical findings so your team can keep shipping.
Most reviews complete in days to a couple of weeks after scoping and repository access, depending on PR volume, stack complexity, and whether remediation is included.
Scoping
Response within 1 business day