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AI app cost by build type
Most of the spread in AI app pricing comes from one decision: do you call an existing model's API, or do you train or fine-tune your own? API-based apps reuse a model that already works and spend the budget on the product around it. Custom-trained apps spend most of the budget on the model itself.
| Tier | Examples | Cost | Timeline |
|---|---|---|---|
| API-based feature | One AI feature added to an existing app, e.g. summarization or drafting | $15,000-$40,000 | 3-7 weeks |
| API-based AI MVP | Standalone product: LLM + RAG + UI + 1-2 integrations | $15,000-$50,000 | 6-12 weeks |
| Production AI product | Own RAG pipeline, eval suite, guardrails, multiple integrations | $50,000-$250,000 | 4-7 months |
| Custom or fine-tuned model | Model fine-tuned or trained on proprietary data | $150,000-$400,000+ | 7-12+ months |
| Enterprise AI platform | Multiple models, compliance, large-scale fine-tuning programs | $250,000-$650,000+ | 12+ months |
What each component adds
| Component | Hours | Notes |
|---|---|---|
| Discovery | 40-80 h | Scoping the use case, deciding API vs. fine-tune |
| Data audit and prep | 40-160 h | Often the most underestimated line item |
| LLM backend | 80-200 h | Prompting, orchestration, API integration |
| RAG pipeline | 80-200 h | Retrieval over your own content or documents |
| Eval set and tests | 60-160 h | The component most often missing from low quotes |
| Guardrails and access control | 40-120 h | Rate limits, input validation, permissions |
| UI | 60-160 h | The actual product surface users interact with |
| Integrations | 60-200 h per system | Each connected tool or data source |
| Fine-tuning (if needed) | 160-480 h | Only relevant for the custom-model tier |
Cost by who builds it
| Option | Hourly rate | Total for a typical v1 | Trade-offs |
|---|---|---|---|
| US team, hourly | $80-$160/h | $12,000-$64,000 for a 150-400 hour MVP | Highest quality, highest hourly cost |
| Eastern Europe team, hourly | $35-$80/h | $5,250-$32,000 for the same scope | Lower cost, usually a bit more coordination overhead |
| Agency, fixed-price | Quoted as a fixed price, not hourly | $15,000-$50,000 for an API-based MVP | Price agreed before work starts; RapidDev's band sits here |
| In-house ML/AI engineer | Salary-based, not hourly | $150,000-$220,000+/yr loaded | Right once you need continuous model work, not a one-off build |
Running cost per AI call (worked math, Nov 2026 prices)
Model running cost is calculated as (input tokens x input price + output tokens x output price) / 1,000,000. Worked example: an AI writing or summarizing feature using 3,000 input tokens and 800 output tokens per call.
| Model | Per call | 50,000 calls/mo | Per active user (30 calls/mo) |
|---|---|---|---|
| Claude Sonnet 5.5 / GPT-6.1 Sol ($2/$10 per M) | 3,000 x $2/1M + 800 x $10/1M = $0.014 | $700 | $0.42 |
| Claude Haiku 5.5 / GPT-6 Luna ($0.10/$0.50 per M) | $0.0003 + $0.0004 = $0.0007 | $35 | $0.02 |
| Gemini 3.8 Flash ($0.75/$3.75 per M, doubles Jan 1 2027) | $0.00225 + $0.003 = $0.00525 | $263 (rising to about $525 after Jan 1 2027) | $0.16 |
| Claude Opus 5.5 ($4/$20 per M) | $0.012 + $0.016 = $0.028 | $1,400 | $0.84 |
| Batch API, Sonnet 5.5 (async, -50%) | $0.007 | $350 | - |
Model fees are rarely the biggest running-cost line. Budget $200-$1,500/mo in infra for an API-based app, $2,000-$8,000/mo once you're fine-tuning, and $15,000-$60,000+/mo for a fully custom-trained model. Add maintenance of 15-25% of the build cost per year (or 3-8% per month, by one agency's rule of thumb), plus $0-$50/mo for a vector database if you're running RAG on something like Supabase pgvector or Pinecone's Builder tier.
How to spend less without regretting it
- Use a hosted model API instead of fine-tuning. Fine-tuning alone adds 160-480 hours to the build
- Route easy calls to a cheap model like Claude Haiku or GPT-6 Luna, roughly 20x cheaper per token than Sonnet or GPT-6.1 Sol, and reserve the expensive model for hard cases
- Use prompt caching wherever the same system prompt or context repeats. Cached input tokens cost around 5% of the uncached price
- Build RAG on Postgres with pgvector instead of standing up a separate vector database
- Before building, check whether a bought product solves it. Menlo Ventures found 76% of enterprise AI use cases in 2025 were bought, not built
- Scope the eval set and guardrails into the original quote. They're the line item low quotes leave out, and the one that causes the most rework later
What it costs with RapidDev
RapidDev's standard engagement is a fixed $13,000-$25,000 over 6-10 weeks, and it fits the API-based end of AI app development: an LLM feature, a RAG pipeline over your own content, a UI, and one or two integrations, built on a hosted model rather than a custom-trained one.
To make that concrete, the Project Scoper on this page has priced builds like a RAG chatbot with an admin CMS and login at $14,000-$18,000 over 6-8 weeks, and an AI agent with two integrations plus login and admin at $16,500-$21,500 over 7-9 weeks. Both are API-based AI apps that land inside the fixed-price band.
What's out of range: fine-tuned or custom-trained models, enterprise AI platforms with compliance programs, and anything needing formal red-teaming. Those tend to start around $150,000 in the broader market, well above a scoped v1. Describe your use case in the scoper above and a call turns it into a fixed quote within about 48 hours.
Get a fixed-price quoteFrequently asked questions
How much does it cost to build an AI app?
An API-based AI app built on a hosted model like Claude or GPT costs $15,000 to $50,000 for an MVP. A production AI product with its own RAG pipeline and evaluation suite runs $50,000 to $250,000, and a custom-trained or fine-tuned model climbs to $150,000-$650,000 or more.
Why do AI app cost estimates vary so much?
Agency guides for 'AI app development' quote both a single AI feature and a full custom-trained model under the same phrase. The actual cost driver is whether you're calling an existing model's API or training your own; everything else is a smaller adjustment on top of that choice.
Is it cheaper to use an AI API or train my own model?
Using a hosted API from a provider like Anthropic or OpenAI is cheaper almost every time. Fine-tuning adds 160-480 hours to the build on top of the base AI app, and running a custom-trained model costs $15,000-$60,000+ a month in infra versus $200-$1,500/mo for an API-based app.
How long does it take to build an AI app?
An API-based AI MVP typically takes 6-12 weeks. A production AI product with evaluation and guardrails takes 4-7 months, and a custom-trained model project runs 7-12 months or longer.
How much does it cost to run an AI app per month?
At moderate volume, an API-based AI app usually costs $200-$1,500/mo in combined LLM and infra fees. A single AI call with Claude Sonnet 5.5 on a 3,000-token prompt costs about $0.014; at 50,000 calls a month that's roughly $700 in model fees alone.
What's the single biggest hidden cost in an AI app build?
Evaluation and testing. Teams that skip it save 10-20% of the quote up front and then spend far more fixing hallucinations, bad retrieval, or unsafe outputs after launch. It's the line item most often missing from low quotes.
Does RapidDev build AI apps?
RapidDev's $13,000-$25,000 fixed-price band covers API-based AI apps, meaning an LLM feature, RAG, a UI, and a couple of integrations built on a hosted model. Fine-tuned models and enterprise AI platforms are outside that range.
