Cost guide
How Much Does an AI MVP Cost?
AI products carry two costs founders routinely conflate: the one-off cost of building the product, and the per-request cost of running the model forever. Budgeting only for the first is the most common mistake we see.
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Short answer
A focused AI MVP — one AI capability inside a real, deployed product — starts at our fixed $3,500 and 14 days. Retrieval over private data, agent behaviour and human review steps push the build higher, and model usage is a separate monthly bill paid to your provider.
- $3,500
- fixed price
- 14 days
- to launch
- 100%
- code ownership
- No equity
- ever taken
- No retainer
- no hourly billing
01
The two costs of any AI product
Build cost is finite: design, engineering, deployment, handoff. It ends. Run cost is per request and continues as long as the product is live, scaling with your users rather than with your development.
A pricing model that ignores run cost is how AI pilots become unaffordable at exactly the moment they start working. Estimate both before you commit to an architecture.
- Build cost: the product, the AI integration, the safeguards around it
- Run cost: model calls, embeddings, storage, transcription or image generation
- Hidden run cost: retries, long context windows, and agents that call the model repeatedly per user action
02
What each AI capability adds to the build
| Capability | Build impact | Run-cost profile |
|---|---|---|
| Chat assistant | Low — prompt design, streaming UI, conversation history | Low, predictable per message |
| Document Q&A (RAG) | Medium — ingestion, chunking, retrieval, citations | Medium; grows with document volume |
| AI agent with tools | High — tool definitions, guardrails, failure handling | High; several model calls per task |
| Image generation | Low — provider integration, moderation, storage | Per image, easy to forecast |
| Voice / transcription | Medium — audio pipeline, accuracy handling | Per minute of audio |
The cheapest AI MVP is nearly always the one that does a single job extremely well. Every additional capability multiplies both the build and the ways the product can fail in front of a user.
03
What increases the cost
- Private or fast-changing data that must be indexed and kept current
- Outputs where a wrong answer has legal or financial consequences, requiring review workflows
- Multiple AI capabilities in the first release instead of one
- Strict latency targets that force caching and streaming architecture
- Compliance requirements around where data is processed and stored
04
What reduces the cost
- Choosing one capability for version one and staging the rest
- Starting on a smaller model and upgrading only where quality demonstrably fails
- Constraining the AI to a narrow domain instead of an open-ended assistant
- Caching repeated queries and reusing embeddings rather than regenerating them
- Accepting a human approval step early instead of engineering full autonomy up front
05
What $3,500 buys in an AI MVP
One AI capability, wired into a real product: accounts, a usable interface, a database, production deployment and a documented handoff. Not a notebook, not a demo, not a prompt in a chat window.
If your scope is bigger than that, the blueprint stage exists to find the version that is not — and to tell you plainly when the honest answer is a larger project.
Questions
Straight answers.
Is an AI MVP more expensive than a normal MVP?
The product around the model usually costs the same. What adds cost is everything that makes the AI trustworthy: retrieval over your own data, structured output validation, evaluation of answers, and a human review step where mistakes would be expensive.
What does it cost to run an AI feature each month?
Model usage is billed per request to your own provider account. A low-volume assistant on a mid-tier model is typically a small monthly bill; an agent that makes many model calls per user action can be an order of magnitude more. The AI cost calculator estimates both ends.
Do I need to train my own model?
Almost never at MVP stage. Retrieval over your own documents plus careful prompting solves the majority of early use cases at a fraction of the cost, and it is far easier to change when you learn what users actually ask for.
Can an AI MVP be built for $3,500 in 14 days?
A focused one can: a single AI capability inside a real product with accounts, a working interface and production deployment. Multi-agent systems, fine-tuning pipelines and heavy data engineering are quoted separately.
Next step
Find out if your idea fits in 14 days.
Tell us what you want to build. We reply within one business day with a straight yes, no, or here is what we would cut.