Health plans are spending $5M per upgrade cycle on systems built before smartphones existed. Here is what a modern agentic AI adjudication architecture looks like — and the ROI numbers that come with it.
Receives claim input · routes to specialists · aggregates decisions
Autonomous appeal drafting · Payer rule lookup · Resubmission routing · Triggered on denial signal from Adjudication Agent
Built from 20+ years inside payer systems. Open to conversations with engineering and product leaders at health plans, TPAs, and healthtech platforms.
Principal AI Engineer · LangGraph · MCP · RAG · HIPAA · FHIR R4
| Metric | 🏚️ Old System | 🤖 Agentic AI System |
|---|---|---|
| Claim Decision Speed | 30+ days average | < 30 seconds Real-time |
| Prior Auth Time | 45 min – 8 hours | < 60 seconds Innovaccer · Risant Health |
| Denial Rate | Baseline (high) | 68–88% reduction Optum data |
| Upgrade Cost | $500K – $5M per cycle | Agent-level versioning vs. $5M legacy cycle |
| AI / ML Capability | None — rules only | Full LLM reasoning + RAG |
| Interoperability | Proprietary EDI | FHIR R4 native |
| Appeals Handling | Manual, weeks-long | Autonomous drafting, <60s Optum PreCheck |
| Real-time Decisions | No — batch only | Yes — streaming inference |