Quick Audit
$350-$500
For founders who need to know what is risky before launch.
- 2-3 business days
- Written report
- Priority issue list
- 30-minute walkthrough
dotfm audits, hardens, fixes, and deploys AI-generated apps so founders can move from fragile prototype to production-ready product.
Practical engineering help for prototypes that were built fast and now need to survive real users.
A focused review of architecture, code quality, auth, data access, deployment, performance, and hidden risks in AI-generated projects.
We turn the audit into shipped improvements: broken flows, fragile integrations, missing tests, deployment issues, and rough edges.
Strong focus on schemas, migrations, constraints, permissions, query performance, background jobs, and data integrity.
Deployment pipelines, environment configuration, logging, monitoring, backups, and operational basics before real users arrive.
Fixed-scope first
Start with a focused audit, then move into implementation only when the risks and priorities are clear.
$350-$500
For founders who need to know what is risky before launch.
$900-$1,500
The recommended starting point: find the issues, then fix the important ones.
From $2,500
For apps with real users, launch pressure, or messy infrastructure.
We are strongest in backend, data, and DevOps, but we can review and stabilize the common stacks used by AI app builders.
The first goal is not stack purity. It is making the app understandable, safer to operate, and easier to keep improving.
Small-agency execution for founders who need clarity, fixes, and a realistic path to launch.
We focus on the gap between a good demo and a reliable product: data integrity, deployment, error handling, and maintainable code.
AI builders often struggle where systems become real: databases, permissions, queues, infrastructure, and operational visibility.
English or French, founder-friendly explanations, fixed-scope entry points, and implementation help from day one.
Send the current state of your app. We will reply with the best next step: quick audit, fix sprint, or a no-fit answer.
Website, GitHub/GitLab link, or screenshots if access is private
Django, Next.js, Supabase, Lovable, Cursor, Bolt, Replit, etc.
Bugs, deployment, auth, database, payments, performance, or launch risk
Launch date, first users, demo, production migration, or maintenance