Your codebase keeps breaking. We can fix that.
A lot of founders come to us with the same problem: they built something fast, maybe with AI tools, and it worked until it did not. Now users are hitting bugs they cannot explain, the codebase is too fragile to touch without breaking something else, and the original builder is gone. Or they are running on a system that has been limping along for years and every new feature takes three times longer than it should. We do not do big-bang rewrites. We audit what you have, figure out what is worth keeping, and give you a clear plan for fixing or rebuilding the rest in a way that does not put the business at risk.
Book a free discovery callHow we approach it
Codebase audit first
We start by reading what is actually there, not what the original developer said was there. We map the architecture, flag the fragile parts, and give you an honest picture of what you are working with before we touch anything.
Prioritised fix list
Not everything needs to be fixed right away. We rank issues by business impact and risk, so you know what to address first and what can wait. No scary all-or-nothing decisions.
Phased rebuild, not a risky rewrite
We replace the parts that need replacing while keeping the business running. Each phase is scoped, testable, and reversible so you are never betting the whole operation on a single big launch.
Security and scalability review
We look at the things that tend to get skipped in a fast build: authentication, data handling, rate limiting, and how the system behaves under real load. We tell you what is exposed and how to close it.
Human engineering judgment throughout
AI can generate code fast, but it takes a senior engineer to know what to keep, what to fix, and what to rebuild from scratch. That judgment layer is what we bring to every rescue project.
Who it's for
- Founders whose AI-built MVP worked in demo but keeps breaking under real users and real data
- Teams running on a system that was built years ago and now slows down every new feature they try to ship
- Businesses that inherited code from a developer who is no longer available and no one can safely change it
- Companies that are growing and can see their current system will not hold up, but cannot afford to stop operating while they fix it
The judgment layer
AI tools can generate code fast. But fast-generated code without a senior engineer in the loop is how you end up with a codebase that works until something real happens. We bring the judgment layer: we know what patterns to keep, what to refactor, and what to throw away. We have built with those tools ourselves, which is why we know where the landmines are. One senior PM owns your engagement from audit to close. We are a Canadian shop, so you are not handing the project to an offshore team that disappears after handoff. And where the rescue work involves genuine technical problem-solving, we document it so it is SR&ED-ready.
Questions people ask us
My MVP was built with AI tools and keeps breaking. Can you actually fix it?
Yes, and this is one of the most common things we get asked. AI-generated code can be perfectly functional for a demo, but it often misses the things that matter under real load: error handling, edge cases, data consistency, and scalable patterns. We audit what is there, figure out which parts are solid and which are the source of the instability, and give you a fix plan you can act on without throwing everything away.
Do you rewrite from scratch or fix what is there?
Neither extreme is usually right. A full rewrite is risky and expensive, and it delays getting real user feedback on the new version. Keeping everything as-is means you are building on a shaky foundation forever. We do a phased approach: audit first, then fix the critical things, then rebuild the parts that genuinely cannot be saved. You stay operational throughout.
How do you avoid breaking things during the rebuild?
We work in phases, not big-bang releases. Each phase is scoped to a specific part of the system, tested in isolation before it touches production, and reversible if something unexpected happens. We also do the codebase audit before touching anything, so we know where the landmines are before we start walking through the field.
Can a rescue or modernization project qualify for SR&ED funding?
It can, especially if the work involves solving a technical problem that was not straightforward to solve. Modernizing an AI-built codebase, for example, often involves tackling genuine engineering uncertainty around architecture, reliability, or scalability. We document as we go so the work is SR&ED-ready if it qualifies. Reach out early so we can structure the engagement with that in mind from the start.
How long does a modernization project typically take?
It depends on the size and state of the codebase. The initial audit typically takes one to two weeks and gives you a clear picture of what you are dealing with. From there, a focused rescue of a small AI-built MVP might run four to eight weeks. A larger legacy system modernization is usually broken into phases of six to twelve weeks each. We scope it clearly before you commit to anything.
Not sure if your codebase is rescuable?
Book a free 30-minute call. We will ask the right questions, look at what you have, and give you an honest read on what it would take to fix it.
Book a free discovery call