Talk to an AI architectBook a free AI assessment
AgentsWorkflowsService DeskAnalytics
AI Agent DevelopmentAI Development CompanyAI Automation AgencyConversational AIGenerative AI ConsultingAnswer Engine OptimizationAI SEO AgencyAI Agents for Marketing
AI agents for businessHow to become AI-nativeBuild vs buy AI agentsAI agents vs chatbotsAI agent development costAI agent glossaryTop AI agent companiesFounders Grit podcastBlog
IntegrationsBlogCareersBook a free AI assessment
ai agents for healthcare

Gaper builds and deploys supervised AI agents into healthcare operations.

Gaper designs, builds, and deploys production AI agents for scheduling, intake, eligibility, and documentation, wired into your EHR and phone systems. They run in your own cloud, on your data and auth, with a human approving every clinical step.

Book a free AI assessmentWhat is an AI agent?
Map the workflowBuild the supervised agentSandbox, verify, go live
gaper · opportunity map
Support triage92
Invoice processing84
Lead enrichment71
Report drafting58
ranked by ROI × feasibilityship #1 first
In one sentence

AI automation for healthcare is the use of supervised production AI agents to handle operational work such as scheduling, intake, eligibility checks, and clinical documentation. Gaper builds these agents into a provider's existing EHR and systems, deploys them in the provider's own HIPAA-aware cloud, and keeps a clinician in the loop on every care decision.

ProductionNot another demo
Model-agnostic
In your cloudYour auth, your data
You own itCode, evals, runbook
Why this matters

Most healthcare AI never leaves the pilot. The hard part is not the demo: it is connecting an agent to Epic, Cerner, or athenahealth, meeting HIPAA, and proving it is reliable enough to put in front of patients and staff every day.

Production filter
  • Does it touch real systems?
  • Can the outcome be measured?
  • Where does human approval stay?
  • Who owns it after launch?
Free AI assessment

Book a free assessment. We will identify one high-leverage workflow, make the build-vs-buy call, and scope the smallest production release.

Map your first production agent
How we work

From strategy to production, owned by your team.

  1. 01

    Map the workflow

    We start from the documents, SOPs, portals, inboxes, and spreadsheets your team already uses, then turn the repeatable path into an agent workflow map.

  2. 02

    Build the supervised agent

    We build on OpenAI, Claude, Gemini, or the right model for the job, with evals, guardrails, citations, and human approval gates where risk matters.

  3. 03

    Connect the stack

    The agent gets the data layer, APIs, MCP tools, auth, and write-backs it needs to finish work inside your systems, not beside them.

  4. 04

    Sandbox, verify, go live

    We launch in a sandbox, verify every run, then move into supervised production with traces, rollback, and an owner.

What we build

Agents wired into the systems you already run.

Scheduling and intake agents

Agents that book, reschedule, and run patient intake against your calendar and EHR around the clock, then write structured records back into the system of record.

Eligibility and prior-auth checks

Agents verify coverage and surface gaps before the visit, drafting prior-authorization requests for staff to review so claims are not denied after care.

Clinical documentation support

Agents draft visit summaries and after-visit instructions from your existing notes. A clinician reviews and signs off before anything reaches the chart or the patient.

No-show and recall outreach

Agents confirm, remind, and re-book across SMS, voice, and email, recovering appointment slots and keeping recall lists current without manual phone work.

HIPAA-aware deployment

Agents run inside your own cloud on your data and auth, with audit logs, role-based access, encryption, and a signed BAA so your compliance team can sign off.

Model-agnostic builds

Each workflow runs on OpenAI, Claude, or Gemini, chosen per task on accuracy, latency, and cost, with evals that measure quality before and after go-live.

Human-in-the-loop on every clinical step

Operational load comes off your team while care decisions stay with clinicians. Agents handle the repetitive, rules-based work and pause for human approval anywhere judgment, safety, or compliance is involved.

  • Agents act autonomously on scheduling, reminders, and data entry, and stop for review on anything clinical
  • Approval gates and confidence thresholds decide what an agent ships versus what a person checks
  • Every action is logged and explainable, so audit and quality teams can trace each decision
Release gate
  1. 01Eval suiteknown + edge casespass
  2. 02Policy checkguardrails enforcedpass
  3. 03Human fallbacklow-confidence routedhold
  4. 04Releaseshipped to prodlive

p95 latency 1.2s

eval pass 12/12

rollback ready

Deployed in your cloud, on your data

Agents run inside your own AWS, Azure, or GCP environment, connected to your EHR and auth. Patient data never leaves your governed boundary, and security review happens before anything reaches production.

  • Runs on your infrastructure with your encryption, access controls, and data-residency rules
  • Connects to Epic, Cerner, and athenahealth through APIs and MCP, not a siloed chatbot
  • Signed BAA, audit logging, and SSO built in from the first sprint
Deploy target
OpenAIOpenAIClaudeClaudeGeminiGeminiSalesforceSalesforceSnowflakeSnowflakePostgresPostgres
SSORBACAudit logCloud

You own the agent after we ship

Gaper hands over the code, evals, and runbook so your team runs and extends the agents without depending on us. A scoped first workflow can be live in as little as 24 hours.

  • Source code committed to your repos with documentation and an operating runbook
  • Eval suites and observability so you can measure reliability and catch regressions
  • First workflow live in as little as 24 hours, deeper EHR integration in the first sprint
Handover state
handoff packageCode, runbook, evals, dashboard
owned by your team
Source repoRunbookEval suiteOwner training

Access your auth

Data your environment

Ops monitor or handoff

Model and stack agnostic
OpenAIClaudeGeminiMCPYour APIsSnowflakeSalesforcePostgres
FAQ

Questions buyers ask us.

Is the deployment HIPAA-aware?+
Yes. Agents run inside your own cloud with encryption, role-based access, audit logging, and a signed BAA. Patient data stays within your governed environment, and we run a security review before anything reaches production.
Does it connect to our EHR?+
Yes. We build agents that integrate with Epic, Cerner, athenahealth, and similar systems through APIs and MCP, reading and writing to your system of record rather than running as a separate chatbot.
How do you keep clinical steps safe?+
A clinician stays in the loop on every care decision. Agents handle operational work autonomously and pause at approval gates for anything clinical, with confidence thresholds and full action logs behind each step.
How fast can a workflow go live, and who owns it?+
A scoped first workflow can be live in as little as 24 hours, with deeper EHR integration in the first sprint. We hand over the code, evals, and runbook so your team owns and extends it.
See what operators from other companies think about AI Agents:
Learn more
Keep exploring
Ai Agent Development CompanyAi Agents For BusinessAi Automation Agency
Production AI agents, shipped with an owner

Ready to deploy your first agent?

Book a free 30-minute assessment. We'll map the highest-leverage workflow and scope the smallest thing worth shipping, live in as little as 24 hours.

Build, deploy, runYour cloudYou own the code