Epic powers more U.S. hospital beds than any other EHR. If your AI feature does not work inside Epic, it does not work in most of the U.S. healthcare market. Embedding AI inside Hyperspace via SMART on FHIR, writing back to the patient chart, surfacing predictions in the right activity tab, and passing App Orchard security review are all distinct disciplines that determine whether your AI ever reaches a clinician’s screen.
Taction Software has delivered 80+ Epic integrations including SMART on FHIR launch apps, Bulk Data pipelines, USCDI v3 compliance work, and direct API integrations. We have shipped ambient documentation that writes back to Epic, clinical copilots that launch from Hyperspace, and predictive analytics fed by Epic Bulk Data exports. Engagements begin with our $50K Epic AI Integration Discovery and scale into pod-based delivery through pilot and production.
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Use Epic AI Integration When You are building or selling an AI feature that needs to reach Epic-using health systems You want App Orchard distribution for scale across multiple hospitals You are an Epic-using health system building internal AI features You are a digital health company that needs Epic on your roadmap before your next funding round You are an existing AI vendor integrating Epic as a new EHR target Choose Different Services When You are targeting Cerner / Oracle Health specifically — see our Cerner AI Integration service You are targeting multiple EHRs without Epic priority — start with the healthcare AI Discovery Sprint You need general AI development without EHR integration — hire healthcare AI engineers
Epic AI integration combines two specialties that rarely live in one engineering team:
We map your AI use case against the Epic surface, identify the right launch context (provider, patient, or backend services), select the BAA-eligible model path, and produce an App Orchard submission strategy if distribution is the goal. Deliverables include a technical architecture, FHIR resource map, security model, predicate analysis if FDA SaMD applies, and a fixed-price quote for Phase 2.
We build the SMART on FHIR launch, the AI inference pipeline with PHI redaction, the first end-to-end use case, the eval harness skeleton, and the audit logging layer. Output is a working Epic-integrated AI feature in your sandbox and a clinical-evidence plan for Phase 3.
We harden the feature for clinical pilot. App Orchard submission package, App Orchard security review, clinical evidence collection plan, eval harness operating in production, drift monitoring, and care-package handoff documentation.
For productized sprint pages, see Discovery Sprint, MVP Sprint, and Pilot-Ready Sprint.
Real-time clinical conversation transcription, structured note generation, and write-back to Epic via DocumentReference and Encounter. See our ambient documentation 12-clinic group case study and our deep-dive on building ambient clinical documentation.
SMART on FHIR launch apps that surface AI-generated clinical reasoning, treatment matching, or specialty-specific recommendations inside the Epic clinician workflow. See our work on embedding AI inside Epic via SMART on FHIR.
AI features that surface in real time during the Epic encounter, including triage prioritization, deterioration scoring, and decision support. See our AI triage copilot case study.
AI-generated prior authorization requests using FHIR plus Da Vinci profiles, fed from Epic patient context.
Structured note generation and clean write-back to Epic patient charts. See our SOAP notes write-back to Epic via FHIR guide.
Group-level $export pipelines feeding predictive analytics and population health models.
If you have an existing roadmap and prefer dedicated engineers, hire Epic integration developers or hire healthcare AI engineers at $8K per engineer per month.
For estimates, use the healthcare AI cost calculator and the EHR integration calculator.
For background on the wider Epic ecosystem, see our Epic EHR integration service page and the Epic EHR integration guide.
The Epic AI Integration Discovery Sprint is $50K over 4 weeks. The full pathway through MVP Sprint ($95K, 8 weeks) and Pilot-Ready Sprint ($145K, 12 weeks) totals $290K over 24 weeks. Dedicated engineers are $8K per engineer per month if you prefer staff augmentation.
End-to-end from Discovery to a clinical pilot inside Epic typically takes 20 to 28 weeks, depending on whether App Orchard submission is in scope and how fast App Orchard review proceeds.
Only if you want distribution across multiple Epic-using health systems. If you are an Epic-using health system building internal AI, you do not need App Orchard. If you are a vendor selling to multiple Epic hospitals, App Orchard is usually the right path.
Any BAA-eligible model can be used: OpenAI via Azure, Anthropic Claude via AWS Bedrock, Google Gemini via Vertex AI, AWS Bedrock multi-model, Azure OpenAI, and on-prem Llama, Mistral, or Mixtral. Model selection happens in the Discovery Sprint.
Yes. App Orchard security review readiness is baked into the engineering workflow from week one. We have shipped multiple apps through App Orchard review.
Some AI features inside Epic are classified as Software-as-a-Medical-Device under FDA rules. We identify this during Discovery and pair the engagement with our FDA SaMD Pathway add-on at $60K over 8 weeks.
Yes. Provider launch, patient launch, and Backend Services flows are standard. Bulk Data $export for population-level pipelines is also standard.
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