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$70K
  • Standard$150K
  • Advanced$350K

A typical configuration lands near $281,000 over 2029 weeks.

$70K–$420KTypical range for this build
$70KCheapest realistic scope
20–29 wksTypical delivery window
18–22%Of build cost, per year, to run it

Configure your ai healthcare app

Work through the steps below — scope, features, compliance and integrations — and you get an itemised estimate with a range, a midpoint and a delivery window.

Configure your build

Question 1 / 8

How big is this build?Sets the baseline everything else is added to.

How big is this build?

What each scope tier includes

Every calculator starts from one of three baselines. This is what separates them.

Baseline cost by scope tier for the AI Healthcare App Cost Calculator
ScopeBaselineTypical shape
MVP$70KNarrowest useful release — one workflow, one user type, launched fast.
Standard$150KThe common case: multiple roles, reporting, and the integrations most buyers expect.
Advanced$350KMulti-site or enterprise scope, deeper interoperability and heavier non-functional requirements.

Baselines are before feature adders, compliance programmes, integrations and the platform, design and team-location multipliers. The headline range for this calculator is $70K–$420K. 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.

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.

Talk to Taction Software Solutions