For people building with AI
Cursor, Lovable, Bolt, v0, Replit, Claude — the demo works and you are genuinely most of the way there. The last stretch is the part these tools are worst at: security, data, deployment and everything that only matters once real people are using it. That part we do every day.
Quick answer
Samvara finishes, secures and deploys applications built with AI coding tools. We review what you have, fix the parts that are genuinely risky — exposed keys, weak access control, no backups — and deploy it properly so you can put customers on it. Review and hardening starts at £199; finishing or taking over a build is quoted after we look at it. You keep ownership of the code throughout.
None of this means you did it wrong. It means you reached the boundary of what the tool does well.
The honest gap
Eight things AI tools routinely skip. Each one is fixable, and each one is a genuine problem if you are about to put real users — or real money — through it.
AI tools happily put keys where the code can reach them, which often means the browser. Anyone who opens dev tools can read them, and a leaked key can be used until you notice the bill.
What done looks like
Keys live server-side in environment config, never in the client bundle or the repo. Rotating one is a config change, not a code change.
Generated apps usually get sign-in right and access control wrong. Users are logged in, and can then read or edit records that belong to someone else by changing an id in the URL.
What done looks like
Every request checks not just who you are, but what this specific user is allowed to touch — enforced server-side, not hidden in the UI.
Prototypes get a database shaped around the first screen. Once real data arrives, changing it means editing production by hand and hoping nothing was lost.
What done looks like
A modelled schema with versioned migrations, so a change is a reviewable step you can run, repeat and roll back.
Demos assume good input. Real users paste emoji into number fields, double-click submit, and lose connection halfway through a payment.
What done looks like
Input validated at the boundary, failures handled deliberately, and errors that tell you what happened instead of a blank screen.
If there is one copy of everything, then testing a change means testing it on your customers, and a bad afternoon means real data is gone.
What done looks like
Local, staging and production kept apart, with their own data and config, so changes are proven before anyone sees them.
Most early projects have no backups. The ones that do have never tested a restore, which is the same thing with extra confidence.
What done looks like
Automated backups with a restore that has been run at least once, so you know the recovery path works before you need it.
Without monitoring, your alerting system is a customer sending an annoyed message — usually hours after it started.
What done looks like
Error tracking and uptime checks that tell you first, with enough context to find the cause instead of guessing.
Dragging files onto a server works until the day a deploy breaks the site and there is no way back except fixing it live under pressure.
What done looks like
A repeatable deploy from source control, and a rollback that takes a minute rather than an evening.
Three ways in
Start with a look at what you have. We tell you which of these you actually need — including if the answer is none of them.
from £199
The build broadly works. You need it live, secure and not a liability.
quoted after review
You got most of the way and hit the part AI could not carry.
quoted after review
You would rather own the product and not the plumbing.
Prices scale with what is actually there — you get a fixed number before any work starts. See our packages for other fixed-price work.
Proof
Picked up part-built · completed by us
A matrimonial platform that came to us partly built. We took what existed, completed it, and shipped it to production across three codebases — a Node.js API, a Next.js admin panel and the public Next.js site — with a shared form library so the same fields behave the same way everywhere, and the biodata rules that the business actually runs on.
This is the exact shape of work on this page: someone else started it, we finished it and put it live.
Our own products
Both are our own builds, designed and shipped by us — not projects we inherited. We build them using AI in the loop, the same way you are building yours.
That is the point: we are not sceptics telling you AI code is bad. We use it daily. We just also know which parts it does not finish.
When you should not hire us
FAQ
It does not matter much. We have picked up builds from Cursor, Claude, Lovable, Bolt, v0, Replit and plain ChatGPT copy-paste. What we look at is the code, the data and the deployment — not which tool typed it.
No. Rewriting is usually the lazy answer and it costs you the most. We keep what works, fix what is actually dangerous, and tell you honestly which parts are worth replacing later rather than now.
A review and hardening pass starts at £199. Finishing an unfinished build or taking it over is quoted after we have looked at it, because the honest answer depends on what is there. You get a fixed number before any work starts.
Yes, always. Your repository, your hosting accounts, your data. We work inside your accounts wherever possible so nothing is locked to us and you can walk away at any point.
A deploy-and-harden pass is usually days rather than weeks. Finishing a partly built product depends on how much is missing — we tell you the range after the review, not before.
Not remotely. We build with AI ourselves, every day. Getting something working with AI is a genuine head start — the gap is in the parts AI is not good at yet, which is precisely the boring production work.
Next step
A short look at your build, and a straight answer on what it needs before real users touch it — including if the answer is nothing. No pitch.
