Custom software
Web apps, portals and internal tools built around your process, with clean, documented code.
Custom AI app & SaaS development
Your product depends on AI. We build it with you, from MVP to SaaS
“Our product only works if the AI part works, and we can’t hire that team fast enough.” The idea is validated, early customers are waiting, and there’s no one to build it properly.
The problem
Demos are easy. Products that survive real users are not
When AI isn’t a feature but the point of your product — a tool that writes, analyses, recommends or answers — no off-the-shelf app can be your product. And a prototype stitched together from no-code tools rarely survives paying customers.
Hiring solves it slowly. A senior AI engineer takes months to find and is expensive to keep, and you still need people for the front end, back end, billing and infrastructure. Meanwhile, your runway shrinks and your window narrows.
The solution
What we build: a real product, scoped to prove your idea fast
We start by cutting your idea down to the smallest version that real users will pay for. That MVP gets a proper foundation: sign-up and team accounts, subscription billing, a database designed to grow, and an AI layer built so you can switch models or providers later without a rewrite.
On the AI side, we handle what separates a demo from a product: prompt and retrieval design, test sets that catch quality regressions before your users do, guardrails against bad output, and usage tracking so you know exactly what each customer costs to serve.
BuildAI was founded in 2024 and is a team of 15 based in Dhaka, Bangladesh. More about the people who would build your product.
The kind of products we build
Vertical AI assistant
An AI writing tool for one profession, with industry templates, shared team workspaces and Stripe subscriptions.
Document intelligence
An app that reads uploaded contracts, flags risky clauses and keeps an audit trail of every result for compliance.
Field-work mobile app
A mobile app that turns technicians’ voice notes into structured job reports and syncs them to the back office.
What goes into a typical MVP, and what waits
Scope is where most MVPs succeed or fail. A typical first release looks like this:
In the first release
- Sign-up, login and team accounts
- The one core AI workflow your users pay for
- Subscription billing with Stripe
- Admin dashboard and user management
- Usage and AI-cost tracking per customer
- Product analytics to see what people use
Deliberately left for later
- Native iOS and Android apps (a mobile-friendly web app first)
- An integrations marketplace
- Fine-grained roles and permissions
- White-labelling for resellers
What you get
- Product scope and clickable UI design, agreed before development
- A working web app, plus a mobile app if needed, deployed to your own cloud account
- AI features with evaluation tests, cost tracking and model-switching built in
- Subscription billing, user accounts and an admin panel
- Source code in your GitHub, with documentation and a technical handover
- A roadmap for the next release, based on what users actually do
Every project also includes a free initial consultation, a dedicated timeline, written progress updates on a fixed schedule and full source code ownership on final payment.
Typical timeline
Typically 4–12 weeks for an MVP, depending on scope.
Weeks 1–2
Scope and design
User flows, UI design and architecture, plus a quick technical spike that proves the AI approach works on real examples.
Weeks 3–8
Build in sprints
Two-week sprints, each ending in a demo on a live staging site you can click through.
Weeks 8–12
Beta and launch
Beta users, fixes, performance and security checks, then the production launch.
The weeks shown describe a project at the upper end of the range. A narrower first release runs the same three stages in less time.
Questions businesses ask before starting
Do we own the code and the IP?
Yes. Everything is built in repositories and cloud accounts you own, and all intellectual property transfers to you on final payment.
Can you take over our existing prototype?
Yes. We review what exists first and tell you honestly what to keep, what to refactor and what to rewrite, with the reasons and the cost of each.
How do you keep AI costs under control?
We track AI usage per user and per feature from day one, cache repeated work and use smaller models wherever they are good enough. That gives you real numbers to price your plans on.
What happens after launch?
You can keep us on for new features and support, or take the code in-house. Both work, because the code is documented for handover from the start.
Typical investment
Growth package
$2,000–$8,000
Growing companies
A focused MVP usually fits the Growth package. Full SaaS platforms with several user types and integrations are Enterprise projects.
Compare all packagesPart of our Build services, for startup founders and early-stage SaaS teams.
Related services
AI integration
Add AI to the systems you already run — CRM, ERP, help desk or internal tools — without replacing them.
Talk to us about custom AI apps & SaaS
Describe the problem in a few sentences. We reply within 24 hours on weekdays, and after a free call you get a clear plan, timeline and fixed quote, with no obligation.