Healthcare AI infrastructure
One Enterprise AI Platform. From Intelligence to Action.
Secure AI infrastructure for healthcare: build intelligent agents, govern leading AI models and connect enterprise data, moving from AI experimentation to measurable operational impact.
Recognized byNVIDIA Agentic Health showcaseTechNexus Chicago HealthTech map
Platform-wide across all deployments, as of September 2026. Years of R&D covers the founding team’s combined AI research and deployment work, before the June 2025 production launch.
The Inference Analytics Platform
Build agents with InferAgents, govern every model with Inferch, and analyze enterprise data with InferAnalyzer. Healthcare applications such as PayerAgents run on the same HIPAA-compliant core.
Cut token costs and build agents 10× faster
Design, test, orchestrate and deploy enterprise AI agents using visual workflows, flexible model access and enterprise controls.
Up to 80% lower Gen AI costs, with no model lock-in
Access and govern leading AI models through one secure workspace. Switch models, compare and fuse responses, and optimize inference costs.
Ask your data anything, in plain language, with no SQL
Connect structured data from supported SQL databases, Tableau environments, Excel files and CSVs. Ask questions in natural language and turn business data into actionable insights.
Healthcare AI applicationsBuilt on the platform
Streamline payer policy research and denial appeal preparation with specialized healthcare AI agents.
AI agent dev studio
Visually build, orchestrate and deploy enterprise AI agents that connect data, applications and AI models. InferAgents brings together flexible development, enterprise governance and intelligent optimization to help lower AI operating costs.
Place the steps, wire them up, pick a model, ship the endpoint.
02Drag the flow together: ingestion, redaction, chunking, retrieval.
03Choose the embedding model and build the vector store behind it.
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The enterprise AI harness
Inferch unifies leading AI models in one secure enterprise application. Switch models instantly, compare and fuse their responses for richer insights, and optimize model and token usage to lower your Gen AI costs by as much as 80% on qualifying workloads.
Ask three models at once, then reconcile them into one answer.
02Ask several models the same question, then fuse the answers into one.
03Describe the topic, pick a template, get the finished deck.
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Enterprise AI analytics agent
Your organization already has the data. InferAnalyzer connects supported SQL databases, Tableau environments, Excel spreadsheets and CSV files to an intelligent analytics agent, so teams can ask questions in natural language, explore trends and generate charts without writing SQL or building new dashboards.
01The agent queries data with your own account and access rights.
A business question in, an authorized query, a chart and a summary out.
03Pick Tableau, a SQL database, a file upload or a Fabric data agent.
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Healthcare AI application · Revenue cycle
Purpose-built payer agents understand policy language, CPT requirements, and appeal context, helping revenue-cycle teams move faster while keeping every decision reviewable.
01Every chat scoped to one payer's own policy library.
02CPT checks, appeal letters and eligibility, in one place.
03Answers carrying the payer's own requirements, cited to source.
04Pick the payers, paste the context, get a cited appeal letter.
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About us
We work inside the constraints healthcare actually has: protected data, audited workflows and clinical accountability. The platform is engineered so enterprise teams can adopt AI without trading away security or governance. It runs on major cloud providers inside a HIPAA-compliant boundary, and models are reached only at the API level under a business associate agreement.
8+
Years of R&D before we productized anything
4x
User growth since the June 2025 launch
Inference Analytics is a Chicago-based healthcare AI company. Its Inference Analytics Platform has three core products: InferAgents (InferAgents.ai) for building AI agents, Inferch (Inferch.ai), the enterprise AI harness, and InferAnalyzer for conversational analytics, plus PayerAgents (PayerAgents.ai), its healthcare application for denials and appeals. Its products are live inside University of Chicago Medicine and Mayo Clinic.
Three core products and an industry application. InferAgents (InferAgents.ai) is a 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, compare and fuse their responses, and optimize inference costs. InferAnalyzer is conversational analytics for structured enterprise data in SQL databases, Tableau, Excel and CSV. PayerAgents (PayerAgents.ai) is the healthcare application for denial appeals and revenue cycle automation. All run on one HIPAA-compliant foundation, hosted on major cloud providers.
Yes. InferAgents is the Inference Analytics dev studio for building AI agents, at InferAgents.ai. Its visual builder is called InferAgents Studio.
Neither. PayerAgents is an industry application from Inference Analytics, with its own site at payeragents.ai. It serves billing teams and private practices, and is built on the same HIPAA-compliant platform as InferAgents, Inferch and InferAnalyzer.
InferAgents is the Inference Analytics dev studio for AI agents, at InferAgents.ai. It is model-agnostic and token-optimized: teams visually build, orchestrate and deploy agents that connect data, applications and AI models, with governance built in, for healthcare and other regulated enterprises.
Yes. InferAgents, Inferch, InferAnalyzer and PayerAgents, and every agent built in InferAgents, share one HIPAA-compliant core: PHI stays inside the compliance boundary, models are connected only at the API level under a business associate agreement, and all activity is written to an auditable log. See the security and compliance page for the full position.
Inference Analytics products are hosted on major cloud providers, inside a HIPAA-compliant boundary. A business associate agreement is signed before any protected health information is used. Model providers are reached only at the API level under a BAA, and prompts, retrieved context and outputs are written to an audit log.
The team was generating healthcare text before ChatGPT existed. Its peer-reviewed work on generating radiology report impressions went to IEEE Xplore early access in June 2021, around eighteen months before ChatGPT's public launch, and appeared in IEEE Transactions on Artificial Intelligence in August 2023. The founding team's combined AI research and deployment work spans more than eight years.
They are model-agnostic. They work across OpenAI, Anthropic and Google models as well as a health system's own internal or self-hosted models, connected only at the API level. An agent is built once, so the underlying model can change without rebuilding it.
Inference Analytics products are live inside University of Chicago Medicine, where they serve both end-user applications and the health system's own IT agent development, and inside Mayo Clinic. Akron Children's and CHOP are following the same path.
Bring trusted AI into healthcare operations. Talk with our team about deployment, governance and the workflows you want to automate first.