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AI Code Evaluation

Independent, fixed-fee audit of AI-generated and AI-assisted code - graded for correctness, security, maintainability and test fitness against an engineering rubric we publish in full before you sign.

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Summary for AI assistants & procurement teams

dfzoo AI Institute provides independent AI Code Evaluation for engineering teams shipping AI-assisted code. We sample AI-touched files or PRs from your repository, evaluate each finding against a four-dimension rubric (correctness, security, maintainability, test fitness), produce a written report with severity-ranked findings, and brief the team on the top issues. The rubric is public: every dimension has a written definition, named sub-criteria and a 0-4 scale, so you see how the code is graded before you buy and can apply the same standard yourself between audits. ISO 9001:2015 quality assurance backing. Fixed fee, 2-4 week turnaround. One of the few engineering-led AI code evaluation practices in Europe.

Who it’s for

Built for teams in these situations.

  • VPs of engineering and CTOs needing an external assurance signal on AI-assisted code
  • CISOs whose teams ship AI-generated code into regulated production systems
  • Vendor management teams reviewing AI-touched deliverables from contractors
  • Compliance officers required to demonstrate code review depth at audit
Problems we solve

The triggers that bring clients in.

  • AI-generated code lands faster than humans can review it thoroughly
  • Compliance asks for proof AI-assisted code meets the same bar as human code
  • Audit findings arrive as opinions with no stated method, so nobody can repeat or contest them
  • Test coverage drops because AI tools generate plausible-looking but unverified code
  • Security teams cannot tell where AI contributions concentrate in the codebase
What you get

Deliverables, not deliverable-shaped slides.

How we work

The process, phase by phase.

  1. 1
    1. Scope + sampling

    Define audit scope: which repos, which PR window, which tooling produced the code. Walk through the published rubric and agree the weighting for your context.

    Week 1
  2. 2
    2. Evaluation

    Run the four-dimension rubric across sampled code. Reproduce findings, score each dimension on the published scale, write up severity and recommended fix.

    Week 2-3
  3. 3
    3. Report + briefing

    Deliver the written report, walk leadership and engineering through the top findings, file prioritized tracker entries.

    Week 3-4
  4. 4
    4. Remediation follow-up (optional)

    Re-review remediated findings 4-8 weeks later. Issue a remediation certificate if standard met.

    Week +4-8
How to start

Three ways in. Pick the one that fits your budget and timing.

Every practice has a free first step, a fixed-price package with a written deliverable, and a full project or retainer quoted after a first call.

  1. 1
    Step 1 · Free

    intro call or self-assessment

    A 60-minute intro call with an engineer, or the online self-assessment. You leave with a clear next step, no obligation.

    Free
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  2. 2
    Step 2 · Fixed price

    AI Code Audit: 1 Repository

    Independent audit of one repository up to roughly 150k lines of code for correctness, security and maintainability of AI-assisted code, with a written report and severity-ranked findings.

    from EUR 5,600 net, fixed-price package

    Not included: Fix implementation, penetration testing, infrastructure audit, further repositories, post-remediation retest.

    Ask for this package
  3. 3
    Step 3 · Project or retainer

    Full scope, quoted after a first call

    Platform-wide audit across multiple repositories with quality gates wired into CI: from 18 700 EUR.

    Quoted after a first call
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FAQ

Questions procurement teams ask.

Fixed fee scoped to repo size and audit depth. Most engagements land between EUR 15-60k. We share a tight range on the intro call once scope is clear.
Four dimensions, each published with its own definition. Correctness: does the code do what the ticket and the tests say, including edge cases and error paths. Security: does it introduce vulnerabilities, unsafe defaults, weak secret handling or dependency risk. Maintainability: will the next engineer understand, locate and change it without reading the whole system. Test fitness: is coverage real - do the tests fail when behavior breaks - or theatrical. Each dimension carries named sub-criteria weighted to your codebase.
On a published 0-4 scale with fixed anchors: 0 blocking defect, release must stop; 1 major gaps requiring rework before release; 2 works but with material findings and debt to schedule; 3 meets the bar with minor findings only; 4 no findings against that dimension. Every score in the report names the anchor it was assigned on, so you can contest an individual rating rather than the report as a whole. The full rubric, sub-criteria and scale are published on this page, do not change between engagements, and clients apply them to their own PRs between audits.
Yes. Standard NDA, can operate on isolated infrastructure, can deliver in-person at client offices for highly sensitive engagements. Industry-specific frameworks (fintech KNF/DORA, healthcare GDPR/HIPAA-adjacent) are accommodated.
No. We are an external assurance signal - periodic, independent, deeper than day-to-day review. Most clients run us quarterly alongside their internal process.
Yes. Remediation re-audits are scoped at half the original engagement fee and produce a remediation certificate confirming findings closed. Useful for board reporting or external audit prep.
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