MVP and product launches for founders
We help turn a product idea into a first version real users can touch: scope, engineering, launch, and feedback.
— 01 / TASKS
What an MVP launch includes
An MVP should test the bet: who the user is, why the product matters, and what deserves the next build.
First-release scope
We lock the core flow, MVP boundary, and cut list.
The project stops expanding before launch.
Clickable prototype
We show the user path before engineering when UX or sales is the main risk.
The idea becomes easier to explain to customers, investors, and the team.
Working product
We build the core flow, data, auth, and integrations that matter.
Early users can complete a real task.
Admin and analytics
We add basic control for users, errors, content, and feedback.
The founder can see what happens after release.
Launch materials
We prepare plain positioning, onboarding, and first-user messages.
Launch day does not depend on improvisation.
Post-launch iteration
We review usage, fix blockers, and choose the next scope.
The next version is based on evidence, not guesses.
— 02 / FIT
When a founder needs an MVP
A good MVP candidate has a specific pain, access to first users, and a founder willing to cut scope for the sake of launch.
The problem has already shown up in customer conversations, sales, or current manual work.
There are people who can try the first version quickly and give honest feedback.
The feature list is growing faster than confidence that the product is needed.
The founder can make decisions quickly and keep the release narrow.
— 03 / PROCESS
What the build includes
Task and data audit
We inspect real tickets, documents, spreadsheets, and access rules.
Scenario design
We define where AI replies, where it acts, and where a human stays in the loop.
Prototype
We build a working first version against samples from your actual workflow.
Integrations
We connect CRM, messengers, databases, documents, or internal APIs.
Testing
We test on real dialogs, questions, and files, not just friendly demo prompts.
Launch
We put the system into work with clear roles, logs, and control points.
Quality monitoring
We review wrong answers, edge cases, escalations, and user behavior.
Support and iteration
We improve scenarios after launch, once real usage starts showing the truth.
— 04 / WORK
Relevant launches
These products differ by market, but the work is similar: narrow the first release, ship it, then improve from use.
AI Platform · EdTech
LiftEd
An AI platform for education: it builds a knowledge map and finds gaps. Advanced analytics for everyone involved. Already ~500 paying teachers and ~20,000 students.
AI Infrastructure · Telegram Mini-App · EventsKaizen Club · TheNext
AI infrastructure for Margulan Seisembai's business summit in Abu Dhabi — one Telegram Mini-App: tickets, entry, networking, AI avatars, and business diagnostics.
Product · Forecasts · MVPjua.ai
An MVP web product for jua.ai (weather forecasts): maps, charts, alerts, and customer access. Built directly with the founder — the version the team showed ahead of a ~$2.5M round.
AI Product · Mobile · Computer VisionDreamBody.ai
An AI product with a mobile experience and computer vision at the center of the user workflow.
— 05 / TIMELINE
Timeline and working format
Fast audit
2-3 business days when sample data and a process owner are available.
Prototype
1-2 weeks for a narrow scenario with a limited integration set.
MVP
3-6 weeks when the system needs real integrations and team access.
Production
Timeline depends on integrations, data quality, and security requirements.
— 06 / PRICING
Pricing
Pricing depends on integrations, data quality, access roles, testing scope, and infrastructure requirements. Each stage is paid separately.
Discovery
A paid review of the task, data, risks, and first sensible scope.
Prototype
We test the scenario on a small data set before debating it in theory.
MVP
We build a working version with UI, integrations, and basic quality control.
Production system
We harden the system for access control, logs, operations, and support.
Support
We monitor quality, fix issues, and add new scenarios after launch.
— 07 / azamat.ai
Why azamat.ai
We build working products instead of demo-day slides.
We help cut scope to something that can actually launch.
We connect product logic, interface, backend, integrations, and launch.
The founder stays involved in architecture and key decisions.
Our work spans education, events, mobile AI products, community products, and internal tools.
— 07 / FAQ
FAQ
With narrow scope and fast decisions, a working MVP often takes 3-6 weeks after discovery and scope lock.
Yes. If the main risk is the flow, sales story, or clarity of the idea, a prototype may be the honest first step.
The problem, first users or a path to them, real examples of the current work, and someone who can make decisions.
No. MVPs usually need scope, UX, engineering, analytics, launch materials, and a short post-release iteration.
We review real user actions, questions, errors, and drop-off points. Then we choose the next release or change the bet.
— 08 / LINKS
Related AI services
— 08 / LINKS
Let’s discuss the task
Send the idea, first user, and what you have already tried. We will help find the first release people can use.