First version · for startups

The first version of your AI product, in front of real users.

Scoped to what your first users need, and built front end to back end in production code you own.

Book a free 30-minute call

Working in 21 days from access, or your build fee back. Half paid only when it works. Full terms

The problem

What gets in the way of a first version.

There's no engineering team yet, or the one you have is busy.
The scope keeps growing, so the launch date keeps moving.
A quick build has to be thrown away the moment real users arrive.

First version (MVP)

What you get.

A scope that fits 21 days

We agree what the first version must do for real users, and leave the rest for later.

Front end to back end

Sign-up, the core screens, the AI, the database and the admin side, in one codebase.

Built to keep

Production code from day one, not a demo that gets rewritten when users arrive.

Your accounts, your keys

Hosting, AI services and the repository are set up in accounts you own.

Timeline

From scoping call to launch.

Scoping
We agree what the first version does, and it ends in a fixed price.
Week 1
The foundations: accounts, sign-up, the data model and the core screen.
Week 2
The AI and the rest of the core flow, tested with real examples.
Week 3
Finishing, testing with real users, and launch.

Our promise

A first working version in 21 days from access, or your build fee back. Half paid only when it works.

Read the full terms

Fit

Who it's for, and who it isn't.

A good fit

Funded or already making money, with a budget for building
An AI feature, AI product or full-stack app to build or finish
A team too small or too stretched to ship it on time

Not a fit

Solo founders without a budget for the build
AI that decides who gets hired, a loan, housing or insurance
Automated texts or calls to consumers

Startups

AI features we buildfor startups.

Each one is built in production code, with the parts that keep it working once real users arrive.

Support answer assistant
Next.jsPostgrespgvectorClaude APIIntercom
1Ticket arrivesFrom Intercom or the in-app help form.
2Sorted by topicThe model tags topic and urgency, and urgent ones jump the queue.
3Docs searchedOnly your help articles and past answers are searched for the facts.
4Reply draftedA draft that links the sources it used, or says it doesn't know.
5Agent sends itEdits are saved and become test cases for the next release.
AI app · Customer support
100%Answers sourced
Support answers from your own docs, or an honest "I don't know".
Tickets are sorted by topic and urgency, answered from your own help articles with the sources linked, and sent by a support agent who can edit the draft.
How the support answer assistant works
Document extraction feature
ReactNode.jsS3GeminiZod
1File uploadedPDFs, scans or photos, stored privately against the user's account.
2Fields readThe model pulls out dates, names, totals and terms into a fixed format.
3Checked in codeEvery field is validated, so a wrong date or total can't get through.
4Unsure fields flaggedAnything the model isn't sure of is highlighted for the user to confirm.
5Saved to the appClean records the rest of the product can search and report on.
AI app · Document processing
EveryField validated
Upload a contract, get clean data back.
Users upload PDFs, scans or photos. The AI pulls out the dates, names, totals and terms into a fixed format, and anything it isn't sure of is highlighted for the user to confirm.
How the document extraction feature works
In-app data assistant
Next.jsPostgresOpenAI APIRedisPostHog
1User asksA plain-English question inside the product.
2Permissions checkedOnly records that user is allowed to see are ever searched.
3Answer builtThe reply links to the records it came from, so users can check it.
4Costs cappedPer-user limits and caching keep the AI bill predictable.
5Usage trackedWhich answers helped and which didn't, to guide the next change.
AI app · In-product assistant
EverySearch permission-checked
Answers from each user's own data, and nobody else's.
Users ask questions in plain English inside the product. Answers come only from records they're allowed to see, with links back to each one and a cap on AI costs.
How the in-app data assistant works

All startup case studies

The team

Who you'll work with.

Senior people scope, build and look after every project. The people you meet on the first call are the people who answer when something needs fixing.

Muhammad Furqan Abid

Founder

Leads engineering on every build: the scope, the architecture, and how the AI parts behave once real people use them. Six years building software.

Muhammad Zaid Ashfaq

Managing Director

Runs delivery and care. He keeps each build on its 21 days, and he's the person you talk to when something needs a decision, during the build and after it.

How we handle your accounts and data

FAQ

First version (MVP), answered plainly.

See every question

It depends on the job, so we don't quote a number before we've seen it. For businesses, the Ops Map ends in a fixed price for the build. For startups, the scoping session does. Either way you know the price before any build starts.

The 21 days start on the day we have the access we agreed we need: logins, API keys, repositories and so on. If what we agreed isn't working 21 days after we get access, you get the build fee back. The full conditions are on our guarantee page.

The build fee is split in two. The second half is only paid once the build does what we agreed it would do.

You do, from day one. We build in accounts you own, the code lives in your repository, and the keys are yours. If we stop working together, nothing has to be moved or bought back.

More ai apps