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AI MVP development for funded startups

We take your AI product from idea to a launched MVP that real users can sign up for, use and pay for, built on an architecture your future team can grow rather than rewrite.

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The short answer

Venzpire builds AI MVPs in 4–8 weeks, starting from $5,000. Every MVP begins with a 1–2 week, $1,500 discovery sprint that produces a clickable prototype and a fixed-scope quote. You get a launch-ready web or mobile product with AI features grounded in your data, sign-up, payments and analytics, with all code in your own repository.

What you get

A real product, not a slide deck or a notebook demo. Everything a first paying customer needs, and nothing that delays your launch.

Led by Venktesh RBuilt with Nithin and Deepak, the same senior team from first call to launch.

Investment
From $5,000, fixed quote after discovery
Timeline
4–8 weeks
Best for
Founders launching a new AI product
You own
All code, IP and cloud accounts from day one
After launch
30 days of support included
Apply for a strategy call How we price
  • Product and UX designUser flows, a design system and high-fidelity screens, tested with a clickable prototype before we write production code.
  • The AI coreLLM features built on GPT, Claude, Gemini or open models, grounded in your data with retrieval (RAG), with evaluation sets so accuracy is measured, not hoped for.
  • Web or mobile appA responsive web app, or native-quality iOS and Android apps in Flutter, with sign-up, onboarding and an admin console.
  • Payments and analyticsStripe or Razorpay subscriptions, usage limits per plan and the analytics you need for your next investor update.
  • LaunchDeployment to your cloud and the app stores, monitoring, cost alerts on AI usage and 30 days of included support.
  • HandoverCode in your GitHub from day one, architecture notes and a recorded walkthrough for your future engineers.

MVPs we’re built for

  • AI SaaS products: document analysis, report generation, research and writing assistants.
  • Vertical AI tools for a specific industry, such as healthcare, legal, logistics or real estate.
  • AI-first consumer apps with voice, chat, personalization or image understanding.
  • Internal AI tools a business wants to validate before rolling them out company-wide.
  • Pilots that need to impress a design partner or investor and survive real usage afterwards.

What it costs

Typical Venzpire price ranges. Every project starts with a $1,500 discovery sprint that ends in a fixed quote; the sprint fee is credited to the build.

ScopeTypical investmentTimeline
Discovery sprint: prototype, architecture, fixed quote$1,500 fixed1–2 weeks
Focused AI MVP: one core AI workflow, web app, auth, payments$5,000 – $15,0004–6 weeks
AI SaaS MVP: multiple AI features, RAG, admin, subscriptions$15,000 – $35,0006–8 weeks
Web plus iOS and Android MVP$25,000 – $50,0008–12 weeks

AI model usage and hosting are billed to your own accounts at cost. How we price

How the project runs

  1. Week 1–2 · $1,500 fixed

    Discovery sprint

    Users, data, model choice and cost per user, pressure-tested. You keep the prototype, architecture and fixed quote.

  2. Weeks 3–10

    Design & build

    A staging link in week one, a live demo every week and a short written update every day.

  3. Before launch

    Evaluate & harden

    Tested on real examples, with guardrails, cost limits and a security review.

  4. Launch & after

    Ship & improve

    Deployed to your cloud and the app stores, with 30 days of support included.

Related work

Knewz — AI news app for iOS, Android and web screenshot

Knewz — AI news app for iOS, Android and web

A personalized, audio-first news app for a US client: AI voice summaries, morning-to-night audio bulletins, local news by location and a publisher dashboard with analytics.

The brief
Readers wanted to keep up with the news on the go, and the client wanted one product for readers on iOS and Android plus the publishers feeding it.
What we built
Built in Flutter for iOS and Android with a web publisher panel, RSS import, moderation tools and behaviour-based notifications. An OpenAI-backed summarizer condenses articles for an audio reader, and separate admin and publisher APIs manage categories, articles and accounts. Shipped to both app stores in about three months.
  • United States
  • ~3 months
  • Flutter iOS + Android
  • AI voice

Read the Knewz case study

i2AO — AI reader for French public-tender documents illustration

i2AO — AI reader for French public-tender documents

A SaaS platform that reads a French public-tender's RC, CCAP, and CCTP PDFs and hands back a structured summary of the clauses that matter, with an admin side to manage plans and users.

The brief
Bidding on a French public tender means reading dense RC, CCAP, and CCTP documents by hand to find the deadlines, requirements, and clauses that decide whether a bid is even eligible.
What we built
We built the document pipeline that uploads a bidder's RC, CCAP, and CCTP PDFs or DOCX files, sends each to an OpenAI assistant with a clause checklist tailored to that document type, and assembles the extracted findings into a downloadable PDF report, plus the user and admin web apps around it for accounts, plans, and history.
  • France
  • PHP/MySQL
  • OpenAI Assistants API
  • PDF & DOCX ingestion
  • Plan-based subscriptions

Read the i2AO case study

Questions about AI MVP development

How much does an AI MVP cost?

At Venzpire, a focused AI MVP costs $5,000–$15,000 and a fuller AI SaaS MVP with several AI features, retrieval over your data and subscriptions costs $15,000–$35,000. Adding native iOS and Android apps brings it to $25,000–$50,000. Industry-wide, AI MVPs typically range from about $5,000 for a narrow single-feature product to $60,000+ for a full SaaS product.

Can an AI MVP really be built in 4–8 weeks?

Yes, when scope is fixed before the build starts. That is the job of the discovery sprint: we cut the MVP to the one or two workflows that prove your idea, reuse proven building blocks for auth and payments, and spend the build time on what makes your product different. Our i2Ao document-analysis SaaS went from kickoff to production in about a month.

Will the MVP scale, or will we need to rebuild it?

We build MVPs on production architecture: a proper database, background jobs, provider-agnostic AI calls and logging from day one. What we leave out is features, not foundations, so your team extends it after product-market fit rather than rewriting it.

Do you sign NDAs and who owns the MVP?

We sign your NDA before the discovery call if you want. You own everything: code, prompts, designs and data, in your own GitHub and cloud accounts from the first commit.

Guides on AI MVP development

Have an AI product worth building properly?

Tell us what you are building. Venktesh reads every application himself and replies within one business day.

Apply for a strategy call