AI Code Cleanup and Refactoring
Make your AI-built app easier to change.
Your app works, but every new feature brings another round of cleanup. We help you untangle fragile logic, give repeated rules a clear home, and protect the behavior your users rely on.
Request a project fit reviewNo repository access required for the initial project fit review.
The feature is small. The impact keeps spreading.
When the same rule appears in several places, a simple change becomes a search for everything it might break. Code cleanup starts by finding those connections.
Explore project setup for coding agents- Different screens apply different versions of the same rule.
- A change in one feature breaks an apparently unrelated flow.
- Error handling hides the failure until a user runs into it.
- AI-generated changes need repeated manual cleanup before you can trust them.
Keep the behavior. Improve the structure.
Start with a project fit review. If the work is a match, we agree the assessment, access, and implementation scope before making changes.
- 01
Map what must stay true
Identify the affected user journeys, business rules, and dependencies. Agree which areas need attention and what behavior the work must preserve.
A bounded cleanup plan with acceptance criteria.
- 02
Give the rules a home
Consolidate duplicated logic and clarify module boundaries within the agreed scope. Make failures explicit and retain useful working parts.
Code changes organized around clear responsibilities.
- 03
Check the next change
Add relevant regression checks and verify the affected journeys. Explain the important decisions and any remaining risks so development can continue with context.
Verification evidence and a practical handover.
A technical assessment is separately scoped. After fit and repository access are agreed, we inspect the agreed system areas and provide prioritized findings, an implementation plan, and acceptance criteria.
Code changes, product completion, testing, and release preparation are a separate implementation engagement with agreed requirements. Sending the review form does not start implementation.
From our own products
Bounded: one search boundary, two ways to ask.
A real example from our relationship-context app of giving a business rule one authoritative implementation.
The engineering problem
Bounded makes workspace search available in its app and through tools for AI assistants. Those entry points need to respect the same permissions and filtering rules. Otherwise, a second interface can become a second interpretation of what a person may see.
How the work is organized
The app and assistant tools use the same server-owned workspace search reader. Its contract keeps filtering, authorization, and result shaping together. The assistant interface exposes the search capability as a read-only tool.
What the record shows
The repository includes integration coverage for the app’s search call and a registry check that maps the documented search capabilities to read-only assistant tools. The shared boundary gives both interfaces one place to inherit the search rules.
This describes the inspected implementation and its regression coverage. It is not a measured before-and-after refactoring result, a new security audit, or a guarantee that every search condition is covered.
Bounded is Bayon’s own product. This is an engineering example, not a client engagement or a claim about how the original code was written.
Explore BoundedTwo entry points
The app’s search interface and the assistant’s read-only search tool.
One owner of the rules
A shared server reader applies permissions, filters, and result shaping.
A boundary worth checking
Integration and registry coverage connect each interface to the documented contract.
Before we look at your project.
Is this the same as fixing one bug?
A focused repair targets a specific blocker. Code cleanup addresses structures that repeatedly make changes difficult. The initial fit review helps identify the right starting point.
Will you rewrite my whole app?
A rewrite is not the default. We retain useful working parts and explain any recommended replacement before agreeing the scope. Fewer lines alone are not the success criterion.
Will my coding agent stop making mistakes?
We cannot promise error-free changes. This work improves the code boundaries and checks available to development and review; it does not change the underlying AI model.
Can I keep adding features during cleanup?
The assessment identifies how cleanup and feature work can be bounded. Coordination, sequencing, and any release constraints belong in the agreed plan.
What does the first review include?
No repository access required for the initial project fit review. The initial review does not include a code audit, implemented fixes, or a production-readiness sign-off.
How is the work priced?
Bayon AI service prices are not published on this website. We agree the scope of an engagement before work begins.
Make the next change easier to understand.
Tell us where development keeps becoming fragile or repetitive, and what you want to build next.
Request a project fit reviewNo repository access required for the initial project fit review.