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AI MVP Development – Proof of Concept for AI Applications

Working AI application prototype in 4-8 weeks. Concept validation, core features, ready to show investors and first users.

SERVICE DETAILS

AI MVP development is the fastest path from idea to working product. I design and build an AI application prototype in 4-8 weeks — functional enough to validate your business hypothesis with real users, solid enough to show investors. Stack: React/Next.js on the frontend, Python (FastAPI) or Node.js on the backend, integration with GPT-4, Claude 3, or Gemini through standardized APIs. Deployed on Vercel or Render with automated CI/CD from day one. I deliver source code in your GitHub repository with documentation so your engineering team can take over seamlessly.

> INVESTMENT:

from €4,500
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Key Benefits

Working prototype in 4-8 weeks — fast enough to validate the idea before committing your full production budget.

Integration with top LLMs (GPT-4, Claude 3, Gemini) configured for your specific use cases, not a generic demo.

Source code in your GitHub repository with documentation — ready to hand over to your engineering team at project completion.

Deployed on Vercel or Render with CI/CD from day one — your MVP is live at a real URL, ready to demo to investors or pilot users immediately.

Architecture designed for scale — even the MVP is built so it can grow into a full application without a complete rewrite.

The Process

1

Discovery and scope

Over 3-5 days we map the core MVP features together: what it must do, what it doesn't need to do, and what success looks like after 8 weeks. I establish the stack, AI integrations, and sprint plan.

2

Prototype and core AI

In the first 2-3 weeks I build the foundation: data architecture, LLM integration, and the first working product loop. You have something to click through after the first sprint.

3

Feature development and UI

In the middle phase I add further layers: React/Next.js user interface, authentication, database, and full end-to-end flow. We sync progress regularly via Slack or Notion.

4

QA, deploy, and handover

Automated and manual testing, production deployment, monitoring setup (Sentry, Datadog), and a handover session — full documentation of code, environment variables, and architecture.

Frequently Asked Questions

What is the difference between an MVP and a proof of concept?

A PoC is a technical experiment — proof that something can be built. AI MVP development produces a working product with core features you can show to real users and collect feedback from. I deliver MVPs, not PoCs.

Will you continue developing the product after the MVP?

Yes, if you want. The MVP is a starting point — after validation we can plan further sprints and add features together. You can also hand the code to your own engineering team with full documentation.

Which AI models can be integrated?

OpenAI GPT-4o, Anthropic Claude 3.5, Google Gemini Pro, Mistral, Llama 3 (self-hosted), or your own models via API. Model selection depends on use case, token budget, and data privacy requirements.

Will I own the code?

Yes, 100%. I deliver the code to your GitHub repository — you have full rights to the project and can develop it with anyone you choose. No vendor lock-in.

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All modules of AI App Development

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BIAŁYSTOK, PL
+48 732 022 086pawel.wiszniewski95@gmail.com