A deployed product, not a demo
Real users can sign in and use it. Frontend, backend and LLM layer ship together.
AI Products & MVPs
From AI idea to a product people can use.
We take an AI product idea from prototype to a working, deployed product: frontend, backend, LLM layer and the evaluation that keeps it honest.
- LLM apps
- MVPs
- Next.js + FastAPI
product.build · illustrativedeployed
- 01Ideaproblem · users · first version
- 02Prototypeworking software early
- 03Evalscores computed in codefail → iterate
- 04Deployfrontend · backend · LLM layer
Outcomes
What you walk away with.
Evaluation built in
Scores are computed in code and the LLM cites real data, so quality is measured, not guessed.
A first version scoped in writing
We agree what the first release does and what done means before we write code.
Code and docs you own
We hand over the codebase and documentation, and stay available to plan the next version.
How we deliver
From idea to first release.
- 01Honest yes / no on fit
Call
We learn what you want to build, who it is for, and what a good first version looks like.
- 02Written scope
Plan
Scope, architecture, milestones and how we will measure quality, written down.
- 03Weekly demos
Build
Short cycles with working software every week and your feedback each cycle.
- 04Live product
Launch
Deployment, code and docs handover, post-launch fixes and next-version planning.
Related work
Our productPublic beta
VakSutra AI
VakSutra AI is our own product: on-device vision, speech and scoring in code, built and shipped end to end by our team.
- Per practice answer
- 2 min
- Areas scored
- 4
- During public beta
- Free
Typical stack
- Next.js · Reactproduct frontend
- FastAPI · Node.jsbackend and APIs
- LangChain · LangGraphLLM layer
- Supabase · PostgreSQLdata and auth
- Vercel · Render · AWSdeployment
FAQ
Questions about MVPs.
We agree the scope and timeline in writing before we start, then show you working software every week, so you see progress early and can change priorities.
Anything that must be correct, like scores and totals, is computed in code. The LLM works from real data, and its output is structured and validated before users see it.
Every project is scoped individually and quoted as a fixed-scope proposal. No hourly rates or template pricing.
Yes. We hand over the code and documentation at launch and stay available after.
Ready to start?
Tell us what you want to build.
The product idea, who it is for, and what a good first version looks like. A few lines are enough; we reply within 24 hours.