AI code audit in Germany: get repo, security, CVEs and infrastructure reviewed
An AI code audit checks not only whether AI-built code runs, but whether it is production ready. I do this from Germany with a named point of contact: repo, security, CVEs and infrastructure are reviewed and then kept under ongoing technical oversight, instead of stopping at a one-off report.
- Baseline from 790 €
- German point of contact
- Repo + CVE + infrastructure
- Ongoing oversight, not a one-off audit
Direct point of contact
Timo Wevelsiep
Software engineer, cloud architect, founder & managing director
I review code, security and infrastructure and surface what is technically risky before launch, customer use or due diligence.
I have delivered production software, infrastructure and cloud systems for clients worldwide, including Europe, the UAE, Asia, Australia and the Americas: from automated multi-location platforms and cloud migrations to remote access systems for industrial plants.
For questions like:
- Is this release production-ready?
- Which CVEs are really critical?
- Are auth, data access and tenant isolation clean?
What an AI code audit covers
An AI code audit is more than a linter run. As an AI code audit Germany engagement, we look at the points that decide production readiness and rank every finding by severity. We review:
- Repo and architecture: structure, dependencies, obvious weak spots
- Security and access control: auth, roles, exposed secrets
- CVEs and dependencies: known vulnerabilities in the packages you use
- Database and RLS: tenant isolation, policies, access protection
- Infrastructure, deployment, backups and monitoring
- Production readiness: what is still missing before real users
Why AI code needs different review patterns
AI tools produce working code fast, but they rarely make the security and operations decisions that real production needs. An AI code audit therefore has to watch for different patterns than a classic code review:
- Plausible-looking code that ignores real edge cases and error paths
- Authentication without a well thought out roles and permissions model
- Supabase RLS not enabled or incomplete across several tables
- Secrets and API keys in the frontend or accidentally in the repository
- Unchecked dependencies pulled in by prompt, with known CVEs
- Copied patterns with no rate limiting, input validation or logging
- Architecture that shifts with every prompt and gets hard to follow
German point of contact and confidential access
An AI code audit touches sensitive code. That is why at Veriploy you have a named point of contact in Germany: Timo handles the review personally, you talk to a person who knows your stack, not an anonymous ticket system.
We work with read-only access to the repository by default. Read access is fully enough for the review, we do not need write access because we do not commit the fixes ourselves. On request we agree confidentiality up front via an NDA.
Communication runs in German or English, async and traceable. Every finding is documented, prioritised and explained so your team can implement it without assuming prior security knowledge.
The Baseline as your entry point
You start with a one-off review and then decide whether ongoing oversight makes sense. Prices are fixed and transparent.
| Baseline 790 € | |
|---|---|
| Scope | Deep initial baseline: repo, architecture, dependencies, config |
| Result | Risk dashboard, CVE baseline, secrets check, plan recommendation |
| CVEs and dependencies | Full baseline as a reference point |
| Support | One-off, with a recommendation for the right plan |
| Best for | Clean starting point before any ongoing oversight |
Oversight, Guard and Launch as ongoing oversight
AI-built code drifts fast: new dependencies, new CVEs, shifting architecture. Yesterday's audit does not cover that. So after the entry point Veriploy offers ongoing oversight in fixed monthly plans:
| Oversight 990 €/mo | Guard 1.950 €/mo | Launch 3.900 €/mo | |
|---|---|---|---|
| Focus | CVE and dependency monitoring with heads-ups | Reviews of important changes plus async sparring | Close support before and during larger releases |
| Reviews | Recurring report with a risk dashboard | Reviews of risky pull requests, prioritised | More frequent reviews and a release-readiness check |
| Sparring | Heads-up on critical findings | Direct channel for questions | Close exchange and human prioritisation |
| Best for | Stable apps that rarely change | Products in active development | Teams just before or after go-live |
How it differs from pure AI code review tools
Automated AI code review tools are useful: they run on every commit, catch many standard issues and are cheap. But they do not replace an AI code audit with human judgement. A tool hands you a score, it does not prioritise and it does not understand your business context.
Veriploy uses automation as the base and puts human review on top. We decide which findings are truly critical, which can wait and which are harmless in the context of your app. Instead of a long list you get a prioritised assessment.
Before larger releases you get a human judgement instead of an automated score. Exactly this combination, tools for breadth and a human for depth, sets the audit apart from a pure review bot.
How the AI code audit works
- 01
01 Fit check
A free short exchange about stack, tool and goal. I clarify what scope the Baseline needs and name the effort up front.
- 02
02 Scope and access
Define which repository gets reviewed and where the focus sits. Read-only access is set up, on request agreed up front via an NDA.
- 03
03 Technical analysis
Automated scan plus manual review of repo and architecture, security and access control, CVEs in the packages in use, and infrastructure, deployment and backups.
- 04
04 Report and recommendations
Findings sorted by severity, with a risk dashboard and concrete recommendations. Every point is explained so the team can act on it without prior security knowledge.
- 05
05 Next step
A joint assessment of what to address now, before launch and later. On request, a recommendation for ongoing oversight with Oversight, Guard or Launch.
Many projects start with a Baseline review. If the product keeps being built with AI afterwards, Veriploy can support it on an ongoing basis.
What I need for the review
- read-only access to the repository
- a short description of stack, tool and goal
- details on hosting and deployment
- database and auth context
- notes on sensitive data or user roles
- open questions or specific concerns
What the review delivers
- an understandable risk dashboard
- top risks at a glance
- prioritised findings
- concrete recommendations
- guidance: fix now, fix before launch, plan for later
- an optional recommendation for Oversight, Guard or Launch
What a finding looks like
A package pulled in by prompt has a known CVE in the version you use, a documented attack path is reachable. Recommendation: update to a patched version and review how it is used in the code.
Pure review tool or Veriploy AI code audit?
| AI code review tool | Veriploy audit | |
|---|---|---|
| Result | Automated score and list | Prioritised, explained findings |
| Prioritisation | All findings weighted equally | Human prioritisation by risk |
| Context | Does not know your business context | Rates findings in the context of your app |
| Infrastructure | Mostly code only | Repo, CVEs and infrastructure together |
| Point of contact | No direct contact | German point of contact, async sparring |
Frequently asked questions
What exactly is an AI code audit?
An AI code audit is a systematic review of AI-built code for production readiness. As an AI code audit Germany service, I look at repo, security, CVEs and infrastructure, rank every finding by severity and explain what to do. It is more than an automated scan and not a classic penetration test.
How does it differ from an AI code review tool?
A tool runs automatically and hands you a score without knowing your context. Veriploy uses automation as the base and puts human review on top: we prioritise findings, rate them in the context of your app and include infrastructure and CVEs, instead of only scanning the code.
Is the point of contact based in Germany?
Yes. At Veriploy you have a named point of contact in Germany, Timo handles the review personally. Communication runs in German or English, async and traceable, without an anonymous ticket system.
Do you need write access to our repo?
No. We work with read-only access by default. Read access to the repository is fully enough for the review, because we do not commit the fixes ourselves. On request we agree confidentiality up front via an NDA.
What does an AI code audit cost?
The entry point is fixed: Baseline 790 € as a one-off review. Ongoing oversight starts at 990 € per month (Oversight), then Guard at 1.950 € and Launch at 3.900 € per month. All prices net plus VAT. Ongoing packages start with a 3-month minimum term, then cancelable monthly, unless agreed otherwise.
Is a one-off audit enough?
For a first assessment yes, for ongoing operation rarely. AI-built code changes fast, new CVEs surface weekly and the architecture shifts with every prompt. So after the Baseline we recommend ongoing oversight with Oversight, Guard or Launch.
- Get your AI app reviewed, with ongoing technical oversight instead of a one-off gut check
- Repo review subscription, a recurring senior look at code, CVEs and architecture
- Infrastructure audit for AI-built software, review your deployment, backups, monitoring and secrets
- Fractional CTO alternative for AI-built software
Do you recognize these risks in your own app?
The AI-app risk self-check assesses product status, stack, auth, data access, infrastructure, CVEs and your technical knowledge, and shows whether a review makes sense.
AI code audit from Germany, with ongoing oversight afterwards.
Start with the Baseline, then we keep the code monitored in the plan that fits.
Check repo fit
Briefly describe the project.
Direct contact with me, no anonymous ticket system. I get back to you with a first assessment and the right entry point.
Timo Wevelsiep
Software engineer, cloud architect, founder & managing director