Senior risk review for AI-built apps
AI-Built App Review
Find launch risk before users do.
A private senior-engineering review for apps built fast with AI tools, templates, low-code platforms, contractors, or internal teams, now close to launch, revenue, diligence, or handoff.
Review packet
What you can inspect before acting
Decision memo
Go / mitigate / block recommendation with the reason in plain language.
Evidence ledger
Affected flows, files, repro notes, screenshots, logs, or access gaps.
Fix sequence
Ordered next moves so builders know what to do first and what can wait.
Who it's for
You shipped fast. Now you need a senior technical read.
This is for teams that shipped quickly and now need to know what will break, what matters, and what can wait.
Founder-built MVP
You built the first version with AI and taste.
Now users, revenue, or investors are close enough that instincts need to become risk language.
Inherited product
The app works, but nobody trusts the inside.
We turn an anxious handoff into a clear map of data, auth, deployment, dependencies, and failure modes.
Diligence window
You need signal before money or reputation moves.
A concise technical risk report lets non-technical decision makers see which risks are existential and which are ordinary debt.
Client launch
You want an outside review without public blame.
We review the system, not the team. Findings stay private, specific, and usable.
Report preview
A board-readable risk map, backed by senior code review.
No generic audit PDF. The report names decisions, blockers, evidence, and the shortest credible fix path.
Private Risk Report
AI-built app review
Launch blockers
User data exposure, missing auth boundaries, destructive admin paths, or deploy fragility.
- Evidence
- Reproduced in staging; affected route, role, and data object listed.
- Impact
- Could expose customer data or force rollback during launch.
- Next
- Block launch until boundary is fixed and retested.
Trust gaps
Logging, backups, permission model, AI prompt/data handling, observability, and incident recovery.
- Evidence
- Observed missing runbook, no restore proof, or AI data path without owner.
- Impact
- Team may not detect, explain, or recover from ordinary incidents.
- Next
- Fix before scale; assign owner and prove the operating loop.
Ordinary debt
Messy but survivable code, duplicated UI, thin tests, brittle naming, or framework drift.
- Evidence
- Code samples and dependency notes attached, with affected change areas.
- Impact
- Slows future work, but does not by itself decide the launch.
- Next
- Sequence after blockers; fold into roadmap or rebuild plan.
Every finding has severity, evidence, business impact, and a recommended next move.
Read a full sample report →What we review
From product surface to production risk.
We look where AI-built apps usually fail: hidden coupling, insecure defaults, missing operating model, and unclear ownership.
Architecture and boundaries
Service shape, data model, tenancy, auth boundaries, API contracts, and places where one change breaks many flows.
Security and privacy basics
Secrets handling, access control, file uploads, logging, data retention, third-party tools, and accidental public exposure.
AI integration risk
Prompt/data boundaries, model calls, eval gaps, unsafe automation, user-visible failure modes, and vendor lock-in.
Reliability and operations
Deploy path, rollback, backups, queues, cron, monitoring, alerting, ownership, and what happens at 2x load.
Codebase maintainability
Framework usage, tests, dependency health, type safety, state management, and the parts a future team will fear touching.
Product truth
Where technical risk collides with the promise users, buyers, or investors think the product already makes.
Packages
Choose the review depth for the decision you need to make.
Fixed-scope advisory, not a disguised build sprint. The prices below anchor the common cases; access limits, urgency, and diligence depth can change scope before we accept the review.
48 hours
Risk Triage
Fast read before a go/no-go call.
from €4.5k
Fixed fee when access is ready.
Best for launch calls, handoffs, or one critical flow.
One senior pass over repo, staging app, deploy notes, and critical flows. We rank P0-P2 risks and call the go/no-go decision.
- P0-P2 blocker list with evidence
- Launch recommendation: proceed, mitigate, or block
- 30-minute partner readout
Excludes Not for full diligence, broad architecture redesign, or implementation work.
5-7 business days
RecommendedTechnical Risk Review
Full private review for real decisions.
€12k-25k
Typical fixed range after fit check.
Best for the standard investor, launch, or rebuild decision.
Architecture, security/privacy basics, AI/data paths, operations, and maintainability reviewed against the promise the product is making.
- Executive risk memo plus technical finding tracker
- Evidence bundle with affected flows, files, and reproduction notes
- Remediation sequence builders can execute
Excludes Not a regulated pentest, legal opinion, or fix sprint.
Custom scope
Diligence Review
Decision support for investors, buyers, or boards.
from €25k
Scoped to the transaction or board window.
Best for investment, acquisition, board approval, or vendor risk.
Independent technical risk read for investment, acquisition, or board approval, with deeper dependency, ownership, data, and delivery-risk review.
- Risk memo for non-technical stakeholders
- Deeper dependency and ownership review
- Remediation budget framing
Excludes Not a substitute for legal, tax, or formal compliance certification.
How it works
Private, direct, and designed for decisions.
Boundaries
No shaming. No theater. No fake certainty.
The point is to make risk legible without turning a fast build into a public morality play.
Private intake
Bring the app. We will bring the risk map.
Send the product URL, repo context, launch pressure, and the decision you need to make. We will reply with scope, access needs, timing, and fit.
Use scoped test accounts and minimum necessary access. Do not paste passwords, tokens, API keys, private keys, recovery codes, customer data dumps, or production secrets into this form.
FAQ
Short answers before access changes hands.
Is this only for AI-generated code? +
No. The pattern is speed outrunning review: AI tools, templates, low-code platforms, rushed delivery, or founder-heavy iteration. If the app now has real users, money, or diligence pressure, it fits.
Do you need production credentials? +
Usually no. We prefer least-privilege repo access, staging access, read-only logs or docs, and a short walkthrough. Secrets should stay in your vault.
Will the report scare non-technical stakeholders? +
It is written to clarify, not dramatize. Each risk gets severity, evidence, business impact, and a realistic next step.
Can you fix what you find? +
Sometimes, but not inside the review package. We separate diagnosis from build scope so the review stays honest.
How can you price before access? +
The public numbers price common review shapes, not unknown implementation work. Before we accept, we confirm package, access state, review areas, deadline, and whether the scope still fits the range.
What changes the price? +
Rush timing, missing access, regulated data, complex AI/data paths, many critical flows, or investor/board diligence depth can move a review out of the listed anchor.
Is rush review extra? +
Often, yes. Urgency changes who we need to pull in and what we can responsibly inspect. If the deadline makes the review weaker, we will say no rather than sell fake certainty.