In this demo, our product lead explains how Nanonets Health AI agents can:

1. Read complex patient documents
2. Do patient intake into your EHR
3. Verify insurance across 150+ payers
4. And then call up the patient to schedule an appointment!

What this solves:

1. Eliminates manual referral sorting and data entry
2. Handles multi-patient packets without human intervention
3. Captures consistent demographic, insurance, and clinical data
4. Reduces intake errors that lead to downstream denials
5. Speeds up intake without adding headcount

This is upstream RCM automation built for real intake workflows, where faxes are messy, referrals are incomplete, and accuracy matters.

What this solves:

1. Eliminates manual outbound and inbound scheduling work
2. Reduces missed calls and delayed bookings
3. Handles patient questions without staff involvement
4. Ensures appointments are accurately synced to the EHR
5. Gives clear visibility into scheduled and pending cases

This is downstream RCM automation built for real scheduling workflows, where speed, accuracy, and patient experience matter.

What this solves:

1. Eliminates manual eligibility and benefits verification work
2. Reduces front desk errors caused by outdated coverage
3. Ensures primary and secondary insurance are identified correctly
4. Prevents downstream denials due to eligibility issues
5. Keeps insurance data accurate across intake, scheduling, and day of service

This is upstream RCM automation built for real eligibility workflows, where coverage accuracy and timing directly impact collections and patient experience.

What this solves:

1. Eliminates manual EOB review and payment posting
2. Ensures accurate application of payments, adjustments, and patient responsibility
3. Reduces posting errors and reconciliation gaps
4. Keeps AR in sync without manual follow up
5. Improves payment visibility and downstream collections

This is downstream RCM automation built for real payment posting workflows, where accuracy, traceability, and financial integrity matter.

What this solves:

1. Eliminates manual charge capture and code selection
2. Reduces coding variability across providers and facilities
3. Ensures coding decisions are defensible and audit-ready
4. Prevents missed or incorrect charges caused by documentation gaps
5. Accelerates claims readiness without adding coding headcount

This is core RCM automation built for real coding workflows, where accuracy, consistency, and revenue integrity matter.