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AI MVP development for products that actually use the model well

From LLM features to agents and RAG — we build AI-first MVPs where the intelligence is the product, not a bolted-on demo.

AI MVP development is its own discipline. The hard part isn't calling a model — it's the product design around it: where the AI adds real value, how it fails gracefully, what you evaluate, and how it stays fast and affordable at scale. We've built AI products and know where the demos quietly break.

We design and ship AI-first MVPs end to end — LLM-powered features, agents, retrieval over your data, and the analytics to see whether any of it is actually working. We integrate the latest Claude and frontier models and pick the approach that fits your product and budget, not the one that's trending.

Like every Starterlyst build, it ships to production in weeks with a senior team on it the whole way, and a clear path to keep iterating once real users start pushing on it.

What you'll get

AI product scoping — where the model earns its place and where it doesn't
UX designed around AI's strengths and failure modes
LLM features, agents, and retrieval (RAG) built to production standards
Latest Claude and frontier model integrations
Evals, analytics, and cost/latency tracking
Private Slack channel and updates 3x per week

How we work

1Scope

We pin down the one job the MVP has to do and strip everything that doesn't serve it.

2Design

Wireframes to a clickable, branded interface you can put in front of real users.

3Build

Senior engineers ship production code — not a throwaway prototype.

4Launch

We deploy, wire up analytics, and hand you a product that's learning from day one.

Simple, fixed pricing

For early-stage founders with an idea.

$8,917

launch in 21 days

$12,000 /month

For products that need more room to think, build, and adapt.

4 - 6 weeks production

Frequently asked questions

What is AI MVP development?

AI MVP development is building a first, shippable version of a product where AI — an LLM, agent, or retrieval system — is core to the value. It validates both the product idea and that the AI approach works reliably and affordably with real users.

Which AI models do you build with?

We work with the latest Claude and other frontier models, choosing the model and architecture that fit your product's quality, latency, and cost needs rather than defaulting to whatever's popular.

Can you add AI to a product I already have?

Yes. We scope AI features into existing products as well as building AI-first MVPs from scratch, and we're honest about where AI adds value versus where it's just hype.

How long does an AI MVP take to build?

Typically 3–6 weeks. Simpler AI features fit our 21-day project-based build; more involved agentic or RAG products run on a 4–6 week retainer.

How do you keep AI features reliable?

We design for failure modes, add evaluation and monitoring, and track cost and latency from the start — so the product holds up once real users hit it, not just in a demo.