Healthcare AI Agents

AI agents for health systems — past the pilot, through governance, into production.

Your EHR vendor ships native AI. Point solutions pitch you weekly. Your AI governance committee wants validation evidence, and your CFO wants denials down. We build the agents that fill the gaps between them, on your EHR’s supported APIs, with the evidence your committee asks for.

Book a 30-min architecture callGet the HIPAA AI blueprint
★★★★★ 5.0 on ClutchBAA signed as business associateYou own the code, no per-seat fees

What do health systems need from a healthcare AI agent partner?

Direct answer: Not another pilot. Health systems need agents that run on the EHR’s supported interfaces (Epic or Oracle Health FHIR and vendor APIs), pass security and vendor-risk review, come with validation evidence for the AI governance committee, are monitored after go-live for drift and safety, and keep a person in the loop wherever an error reaches a patient, a clinician’s signature or a payer. That is the work we do.

Where large health systems are deploying AI agents

The use cases with operating budgets behind them, and the hard part of each.

Denials and appeals

Classify denials, pull the supporting documentation, draft appeals for staff review. Hard part: payer-specific rules, audit trail, measurable recovery.

Prior authorization

Assemble requests from the chart and track status. CMS-0057-F requires impacted payers to offer prior authorization APIs by January 2027. Hard part: documentation templates per payer and service line.

Patient access center

Voice and chat agents for scheduling, referrals and refills that hand off cleanly to staff. Hard part: latency, scheduling APIs, consent and escalation rules.

Clinical documentation integrity

Flag missing specificity, conflicting diagnoses and query opportunities before coding. Hard part: clinician trust and honest omission metrics.

Clinician inbox and messaging

Triage and route patient messages, prepare drafts within policy. Hard part: safety rules, tone, and never sending without a clinician.

Policy and knowledge agents

Answer staff questions on policies, formularies and protocols with citations to the current version. Hard part: versioning and refusing when the source is missing.

Native EHR AI, point solution or custom agent?

Most health systems end up using all three. The question is which job goes where.

Option
When it fits
Native EHR AI features
The workflow lives entirely inside the EHR and the vendor’s feature covers it. Lowest integration effort; you take the vendor’s roadmap and pricing.
Point solution (SaaS)
A mature category with proven outcomes, such as ambient documentation. Fast to deploy; per-seat or per-encounter fees and limited control over models and data.
Custom agent
The workflow spans the EHR, payer portals, the contact center and internal systems, or your data and rules are the differentiator. You own the code and the data path; you need a partner who builds governance in.

How we take an agent from pilot to production

1

Use case and baseline

Pick one workflow with a measurable baseline (denial overturn rate, handle time, query rate) and agree the acceptance bar with the business owner.
2

Integration on supported APIs

Epic and Oracle Health FHIR and vendor APIs, SMART backend services, HL7 v2 where needed, with least-privilege scopes per agent tool.
3

Validation for governance

Test sets from your own cases, gold answers reviewed by clinicians or revenue-cycle experts, bias and safety checks, and a model card your committee can file.
4

Controlled rollout

Shadow mode first, then a pilot unit with human approval on every consequential action, then expansion against the baseline.
5

Monitoring after go-live

Accuracy, drift, override rates and incidents tracked per release, with a rollback path and an audit log of every read, decision and write.

Enterprise requirements we build for

✓BAA chain across every service that touches PHI
✓SSO with your identity provider and role-based access
✓Answers for your vendor security and risk questionnaire
✓Deployment in your cloud tenant when required
✓Validation report and model card for AI governance
✓Post-deployment monitoring and incident process
✓Minimum-necessary PHI and de-identification where possible
✓Full source code and IP ownership, no per-seat fees

Rules and frameworks shaping healthcare AI

What we design for on every project.

Rule or framework
What it means for an AI agent
HIPAA Privacy & Security Rules
BAA chain, minimum necessary, access controls, audit logs. HIPAA has no product certification.
CMS-0057-F
Payer prior authorization, provider access and payer-to-payer FHIR APIs due January 2027.
ONC HTI rules & information blocking
Transparency for predictive decision support in certified health IT; penalties for blocking access to electronic health information.
State AI laws
Disclosure when generative AI communicates with patients, limits on AI-only coverage denials, high-risk AI duties. Requirements differ by state.
Responsible-AI guidance
Governance, validation, monitoring and transparency practices that accreditation and industry bodies increasingly expect.
FREE

The HIPAA-Compliant AI Agent Blueprint

The architecture, controls and traps for an AI assistant that touches PHI and passes the security review.

→The 5-layer build order
→BAA, FHIR & HL7 in plain English
→The pre-launch HIPAA-for-AI checklist
→What compliance actually costs
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Frequently asked questions

Use the native feature when the workflow sits entirely inside the EHR and the feature covers it. Build when the workflow crosses systems such as payer portals, the contact center or internal tools, or when your own data and rules are the advantage. Many health systems do both.
Yes, through Epic’s supported routes: FHIR and other APIs, the Showroom program and backend services authentication, within the access your organization grants. We confirm the exact APIs and approvals for your instance before the build.
Typically a description of intended use, validation results on local data, known limitations, bias and safety testing, the human oversight design, and a monitoring plan. We deliver these as part of the build.
Models offered under a BAA, for example through AWS Bedrock, Azure OpenAI or Google Vertex AI, or provider enterprise plans that sign a BAA. We confirm coverage for the specific product and region before any PHI flows.
Fixed price per phase, from $10K, starting with one workflow and a measurable baseline. You own the code, and there are no per-seat or per-encounter fees.

Have a workflow stuck between pilot and production?

Bring the use case, the systems it touches and what your governance committee asked for. In 30 minutes we’ll map the integration route, the validation plan and a realistic path to go-live.

Book a 30-min call
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HIPAA-compliant AI agent development →EHR integration services →AI agent development company →Enterprise software →