Scope Definition Workshop
We cut the feature list down to what actually tests the AI hypothesis.
AI Products
AI MVP DevelopmentTest the AI in Weeks, Not Quarters.
AI MVP development for the test that decides whether the AI is worth the product — a working AI prototype in 6 to 10 weeks, with the data pipeline, the model, the eval suite and the user-facing slice, not a demo that lives in a notebook.
10+Years Experience
100+Projects Delivered
50+Expert Developers
20+Industries Served
Scope Definition Workshop
Core AI Workflow
Data Pipeline & RAG
Model & Prompt
User-Facing Slice
Eval Suite & Guardrails
Overview
An AI MVP is a test of the AI, not a small version of the product
An AI MVP exists to answer one question: does the AI do the job well enough that users will pay for it? Everything that does not help answer that question is scope you are paying for twice — once to build, once to maintain while you find out it did not matter.
We start by writing down the question your AI MVP is testing, then cut the scope until only the parts that test it remain. Typically that is one core AI workflow, the data pipeline, the model, the eval suite, the user-facing slice and enough analytics to read the answer.
This is the wrong service if the AI is already proven and you need product engineering with proper migrations and uptime guarantees. At that point you need a full AI product, not an AI MVP.
- Fixed Scope — A written feature list before we start, and a change process if it moves.
- You Own It — Repositories, models and cloud accounts in your name from the first commit.
- Built to Extend — Conventional architecture your next hire will recognise on day one.
- Eval from Day One — The eval suite, the safety filters and the cost controls the AI needs from sprint one.
What we deliver
Everything included in our ai mvp development
Core AI Workflow
The one AI workflow the product lives or dies on, built properly.
Data Pipeline & RAG
The ingestion, the chunking, the embeddings and the retrieval the AI needs.
Model & Prompt
The model selection, the prompt and the context engineering, with the eval suite.
User-Facing Slice
The user-facing slice the test users can actually use, with the analytics wired in.
Eval Suite & Guardrails
The eval suite, the safety filters and the cost controls the AI needs.
Our process
A proven process for successful delivery
01
Discover
We write down the question the AI MVP must answer.
02
Plan & Design
We cut scope and design the core AI workflow.
03
Develop
We build in two-week sprints with a working slice every Friday.
04
Deploy
We ship to production with the eval, the analytics and the monitoring live.
05
Optimize & Grow
We read the data with you and plan what comes next.
Technology
Built with a stack that stays maintainable
Models
- OpenAI
- Anthropic
- Google Gemini
- Open source
Backend
- Python
- Node.js
- LangChain
- LlamaIndex
Data & Retrieval
- Pinecone
- Weaviate
- pgvector
- PostgreSQL
Frontend
- Next.js
- React
- TypeScript
- Tailwind CSS
What you can expect
- Typical Build Window
- 6-10 wksTypical Build Window
- Core AI Workflow Shipped
- 1Core AI Workflow Shipped
- Included Post-Launch Support
- 4 wksIncluded Post-Launch Support
- Code, Models and Accounts Owned by You
- 100%Code, Models and Accounts Owned by You
Industries we serve
Delivered for teams in your sector
Most AI MVPs we build land between ₹8 lakh and ₹22 lakh, depending on the data pipeline, the model and the eval suite. After a 30-minute discovery call we send a written scope with a fixed price. If your idea needs more than that, we will say so before you commit.
Yes, through a change process rather than silently. Anything that replaces something already in scope is a straight swap. Anything additive gets a written estimate and a revised date before we start it. The change process is the single biggest reason AI MVPs slip, so we handle it explicitly.
That is a successful AI MVP. You spent two months and a defined budget learning something that would have cost a year and a full team to learn the slow way. We help you read the data honestly, and if the answer is no, we will say so rather than sell you a version two.
Not immediately. Many clients stay on a small retainer while they validate the AI, then hire in-house once the roadmap is clear. We hand over documentation and do a walkthrough with your first AI hire at no cost, whenever that happens.
Related services
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Business software
ERP, CRM, HRMS & custom software we build
Ready to start your ai mvp development project?Let’s scope it together.
Tell us the outcome you need. We’ll come back with an approach, a timeline and a written estimate.