iolite.health provides an agentic AI platform for revenue cycle management (RCM) that automates claims workflows, contract analysis, and payer data mapping without downtime. The platform processes millions of claims, extracts contractual carve-outs from payer agreements using LLMs, and integrates with existing systems in weeks. It is designed for billing companies and MSOs seeking to reduce collection costs and accelerate AI deployment across complex data environments.
Funding
Funding not disclosed
Founders
Product
Problem
RCM operators struggle to deploy AI across their operations because critical data is scattered across practice management systems, clearinghouses, payer portals, and eligibility engines that lack a shared data model. This fragmentation slows implementation, increases costs, and prevents teams from realizing the operational gains of agentic AI.
Solution
iolite.health provides an agentic AI platform that automates high-value revenue cycle workflows, including claims processing, payer contract analysis, and data mapping. The platform uses LLMs to inspect claims, identify missing or incorrect codes, and automatically patch payer data format changes. It also extracts contractual carve-outs from payer agreements denormalized into a searchable format. Agents execute tasks proactively, such as flagging claims that lack anesthesia CPT codes or remapping plan IDs to follow payer layout changes, enabling RCM teams to resolve issues before batches reject. The platform is designed to deploy in weeks, not months, with no downtime even in complex data environments, and supports pay-per-use pricing without seat licenses.
Target Audience
Primary customers are RCM billing companies and management services organizations (MSOs) that handle revenue cycle operations for multiple healthcare clients and need to automate complex claims and payer workflows.
Features
- Agentic AI that autonomously queries claims data, applies filters, and flags anomalies such as missing anesthesia CPT codes on place-of-service OR claims
- Automated payer mapping patches that detect changes to 837 layouts (e.g., plan info moved to subscriber loop) and validate against recent payers to prevent rejects
- LLM-based contract analysis that chunks and normalizes payer agreements to extract searchable terms and carve-outs (e.g., 212 carve-outs from 38 contracts)
- Client-level data isolation with encryption in transit and at rest, role-based access, and audit logging
- Scalable claims processing pipeline capable of scanning millions of claims (e.g., 2.1M claims in a single query)
- Fast deployment with no downtime and ability to go live in weeks rather than months