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Inference Analytics Platform · agentic AI for healthcare

Agentic AI that works inside your health system.

Build AI agents, put them to work across clinical, operational and revenue-cycle teams, and govern every action they take. One HIPAA-compliant core, hosted on major cloud providers, on the models you choose.

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Representative activity across the products.

80+
Agents live in production
3,000+
Active users
200,000+
Queries processed

Live insideUniversity of Chicago MedicineMayo Clinic

How the platform fits together

One agentic AI platform for healthcare

Healthcare applications run on three core products: build agents, govern every model, analyze your data. All of it inside one HIPAA-compliant boundary, over the models and data you already have.

Agentic AI platform for healthcareInference Analytics AI

04 Healthcare AI applications

HIPAA-compliant boundary

03 Core platform products

02 Shared enterprise services

  • Identity & RBAC
  • PHI safeguards
  • Audit & policy
  • Model routing
  • Token optimization
  • Connectors & APIs

01 Data & model infrastructure

  • AI modelsAzure FoundryGPTClaudeGeminiPrivate models
  • Enterprise dataSQL ServerTableauExcelCSVEnterprise systems
Conceptual platform architecture. Integrations and supported connectors are confirmed for each deployment.
The products

Three core products, one HIPAA-compliant core

Build agents with InferAgents, govern every model with Inferch, analyze enterprise data with InferAnalyzer. Healthcare applications such as PayerAgents run on the same core.

01

InferAgents

Build · AI agent dev studioinferagents.ai

A dev studio where teams design, test, orchestrate and deploy enterprise AI agents using visual workflows, flexible model access and enterprise controls, with token-cost optimization built in.

  • Visual agent builder (InferAgents Studio)
  • Multi-model runtime across commercial, open-source and private models
  • Token and cost optimization
  • Enterprise knowledge and RAG
  • APIs and tools
  • Security and lifecycle governance
For IT, informatics and engineering teams in healthcare and other regulated enterprisesInferAgents in detail →
02

Inferch

Govern · Enterprise AI harnessinferch.ai

The enterprise AI harness: a secure, model-agnostic multi-model workspace where teams access and govern leading AI models, switch models, compare and fuse responses, and optimize inference costs, by as much as 80% on qualifying workloads.

  • Model freedom: supported leading AI models in one workspace, without vendor lock-in
  • Multi-model response fusion, with visibility into contributing models
  • Intelligent cost optimization: model selection, token consumption and usage controls
  • Analytics agent and presentation agent
For Enterprise teams, including clinical and operational staff in health systemsInferch in detail →
03

InferAnalyzer

Analyze · AI analytics agentinferenceanalytics.ai/inferanalyzer

An enterprise AI analytics agent that connects supported SQL databases, Tableau environments, Excel files and CSVs, so teams can ask questions in natural language and get summaries, comparisons and charts without writing SQL or building new dashboards.

  • Supported SQL databases, Tableau environments, Excel files and CSVs
  • Questions in natural language, answered with summaries and charts
  • Controlled data access and transparent calculations
For Business, operations and finance teams, and the analysts who support themInferAnalyzer in detail →
04

PayerAgents

Healthcare application · Revenue cycle automationpayeragents.ai

A healthcare application for intelligent revenue cycle automation: specialized AI agents that streamline payer policy research and denial appeal preparation, with CPT coding checks against payer policy libraries tracked daily and a biller reviewing every draft.

  • Denial management and drafted appeals
  • CPT coding support
  • Payer policy libraries tracked daily
For Revenue cycle and billing teams, and US private practicesPayerAgents in detail →
What the platform gives your team

Everything an IT team needs to build agents, nothing they need to bolt on later

Model-agnostic by design, and built on the same HIPAA-compliant core as every end-user application Inference Analytics ships.

Model-agnostic orchestration

Build once, run across OpenAI, Anthropic, Google, or internal models, connected only at the API level.

Token & user management

Govern access, usage, and cost per user, team, or agent, with a full audit trail for compliance review.

InferAgents: the full agent SDLC

Design, test, stage and ship. Built for healthcare change control.

Analytics built in

InferAnalyzer answers questions about your data in plain language, on the same platform your agents run on.

HIPAA-compliant core

Every agent inherits the same compliance boundary. That is the reason health systems hand us backend tooling, not just apps.

Generalizes across specialties

80+ agents run on the same core today, which shows the platform doesn't need a rebuild for every new department.

Time to production

The compliance work is already done

Most programmes lose a year building governance before the first agent ships. That work is already done.

Generic cloud AI platform
11 months
Build in-house from scratch
16 months
InferAgents
3 months

Typical elapsed time from engagement start to a first agent running in production, based on Inference Analytics deployments and customer-reported timelines for comparable approaches.

Live on the platform today

Agents built on the same core

More than 80 agents run on Inference Analytics products. These illustrate the range a single compliant core has to cover, from the ward to the back office.

Clinical

Infectious Disease Agent

Specialty-specific agentic support, proving the core generalizes across very different clinical workflows.

Request a demo →
Operational

Supply Chain Agent

Helps operational teams manage supply chain workflows on the same platform used for clinical agents.

Request a demo →
EHR-adjacent

Epic Tip Sheet Agent

Surfaces Epic tip sheets directly in clinical workflows, alongside the system of record rather than replacing it.

Request a demo →
Proof, not projections

Adoption that compounds through every phase of rollout

3,000+
Active users on the platform
200,000+
Queries processed to date
80+
Agents live in production

“UCM’s own IT organization builds agents directly in InferAgents. It is infrastructure they build on, not a tool they consume.”

On InferAgents, as told by Inference Analytics
Platform questions

How it works, answered directly

What products does Inference Analytics offer?

The Inference Analytics Platform has three core products. InferAgents (InferAgents.ai) is the dev studio where teams build, orchestrate and deploy AI agents across any model. Inferch (Inferch.ai) is the enterprise AI harness, where teams access and govern leading AI models in one secure workspace. InferAnalyzer is conversational analytics for structured enterprise data. PayerAgents is an industry application built on the platform, for denial appeals and revenue cycle automation. All of them share one HIPAA-compliant foundation, and more than 80 agents run in production today.

Is InferAgents a dev studio?

Yes. InferAgents is the Inference Analytics dev studio for building AI agents, at InferAgents.ai, and its visual builder is InferAgents Studio. It is one of the three core products of the Inference Analytics Platform, alongside Inferch and InferAnalyzer.

Which models do the products run on?

They are model-agnostic. They orchestrate across OpenAI, Anthropic and Google models, and across a health system's own internal or self-hosted models, connected only at the API level. An agent is built once against the platform's interfaces, so the underlying model can be swapped without rebuilding the agent.

How do the products handle PHI and HIPAA compliance?

Protected health information stays inside the platform's compliance boundary. Model providers are reached only at the API level under a business associate agreement, data is encrypted in transit and at rest, access is governed per user, team and agent, and every agent action is written to an auditable log. Each agent inherits this core rather than implementing its own controls.

Do health-system IT teams build their own agents?

Yes. That is the intended use. University of Chicago Medicine's own IT organisation builds agents directly in InferAgents. The platform is designed as infrastructure a health system builds on, not a closed vendor tool it only consumes.

How long does it take to get a first agent into production?

Typically about three months from engagement start to a first agent running in production, compared with roughly eleven months on a generic cloud AI platform or sixteen months building in-house from scratch. The difference comes from the compliance core, governance and SDLC already being in place rather than being assembled per project.

Give your teams one platform, not another point solution.

See how our products fit into your model environment, compliance requirements, and existing agents.

Contact usBack to Inference Analytics