We begin with a full read-through and a written map of the code base. We identify duplicated patterns, files that have grown too large, security gaps and missing tests. Then we work with you to reorder the code, add the missing pieces and launch in a controlled way. The result is a code base that can be maintained, extended and deployed without every change feeling like a gamble.
- Full read-through and architecture review of an AI-written code base
- Refactoring towards consistent patterns and clear boundaries
- Dependency audit: what is unused, outdated or unsafe
- Tests where they matter: critical flows, payments, authentication
- Security review: authentication, authorisation, data exposure, secrets
- CI/CD, environments, logging and error monitoring
- Documentation so the next developer can pick it up
- Finish remaining features and launch
Common problems we find
- —Several competing patterns for the same thing in one code base
- —Files that keep growing until nobody dares touch them
- —Authentication that looks right but is enforced only in the frontend
- —No tests around the flows that actually cost money when they break
- —Packages added for a single function and never removed
- —Environment configuration that only works on one machine
- —A README that no longer describes the project
Porting and migration
- →Move from a local experiment to a real repository with CI
- →Split a monolithic prototype into maintainable modules
- →Port the backend to Laravel, .NET, Node or Python where it belongs
- →Move the frontend to React, Next.js or TanStack Start
- →Move data from files or SQLite into Postgres
- →Containerise and deploy to your cloud of choice
How it works
Read
We read the whole code base and map what exists, what works and what is risky.
Decide
We agree on target architecture, conventions and what to keep versus rewrite.
Refactor & finish
We clean up, add the missing pieces and complete the remaining features.
Ship
CI/CD, monitoring, documentation and launch — plus support if you want it.
Common questions
We have thousands of lines of AI-generated code. Can you make sense of it?
Yes. We start by reading it and producing a written map of the project: modules, data flow, dependencies and risks. That document alone usually changes the conversation, because it makes clear what is actually built versus what was assumed.
Should we rewrite from scratch instead?
Sometimes, but far less often than people expect. Most AI-written projects contain a lot of usable work. We give you an honest recommendation with the trade-off in time and cost, rather than defaulting to a rewrite because it is easier for us.
Can you work in our repository and our workflow?
Yes. We work in your GitHub, GitLab or Azure DevOps, follow your branch strategy and submit pull requests for review just like an internal developer would.
Are you affiliated with Anthropic?
No. Claude and Claude Code are trademarks of Anthropic. We are an independent agency that uses the tools professionally.
How do you handle missing tests and documentation?
We add tests where they carry real risk — payments, authentication, data integrity — rather than chasing coverage numbers, and we write a short technical README covering architecture, environment variables and how to run and deploy the project.
Can you review the code without taking over the project?
Yes. A standalone code and security review is a common first step. You get a written report with prioritised findings and effort estimates, and you are free to act on it with your own team.
We are an independent digital agency and are not affiliated with Lovable, Anthropic or OpenAI. All trademarks belong to their respective owners.