AI healthcare app cost calculator
An AI feature layered onto an existing healthcare product — a triage chatbot or a document assistant — costs $70,000–$130,000. Ambient scribes, RAG over clinical content and predictive risk models with a proper evaluation harness land at $150,000–$350,000, and regulated-adjacent builds reach $700,000. Every configuration here assumes AI assists, humans decide: a clinician stays accountable for the output.
- 6 separately priced features
- Compliance costed as line items
- Itemised, not a single guess
- ±15–20% confidence range
At a glance
Baselines before features, compliance and multipliers.
- MVP$20K
- Standard$43K
- Advanced$100K
A typical configuration lands near $113,150 over 28–39 weeks.
Configure your ai healthcare app
Work through the steps below — scope, features, compliance and integrations — and you get an estimate with a range, a midpoint and a delivery window.
What each scope tier includes
Every calculator starts from one of three baselines. This is what separates them.
| Scope | Baseline | Typical shape |
|---|---|---|
| MVP | $20K | Narrowest useful release — one workflow, one user type, launched fast. |
| Standard | $43K | The common case: multiple roles, reporting, and the integrations most buyers expect. |
| Advanced | $100K | Multi-site or enterprise scope, deeper interoperability and heavier non-functional requirements. |
Baselines are before feature adders, compliance programmes, integrations and the platform and design multipliers. Every configuration this calculator can produce falls inside $17K–$407K — the floor is the cheapest tier at the cheapest multipliers with nothing added, the ceiling is the top tier with every option selected at the dearest ones. Both ends are computed from the price table above, not written by hand. A typical mid-market configuration lands near $113,150. See how the numbers are built.
Frequently asked questions
How much does an AI healthcare app cost to build?
An AI layer on an existing product costs $70,000–$130,000. A purpose-built AI product with an ambient scribe or RAG assistant, human review workflows and an evaluation harness costs $150,000–$350,000. Builds that touch regulated clinical decisions run $350,000–$700,000 before any FDA work.
Which LLM providers can handle PHI?
The PHI-safe options that will sign a BAA or run in your own boundary are OpenAI via Azure, Anthropic via AWS Bedrock, Google Vertex AI, Azure OpenAI, and on-prem Llama, Mistral or Mixtral. Expect $0.25–$15 per million tokens on hosted APIs, or $2,000–$8,000 per month in GPU capacity for a self-hosted open-weight model. Never send PHI to a consumer endpoint with no BAA.
Why is the evaluation harness the most expensive AI feature?
At $40,000 the eval harness is the difference between a demo and a product you can defend. It covers a labelled gold set, automated regression runs on every prompt or model change, hallucination and omission scoring, and drift monitoring in production. AI assists, humans decide — and the harness is how you prove the assistance is safe enough for a human to rely on. Taction runs it as a fixed $40,000 Eval Harness Build.
Related calculators
Need a number you can put in a board deck?
A fixed-scope quote comes out of a 4-week Discovery sprint, which starts at $45,000 and ends with an architecture, a backlog and a firm price.