Use Case 1
Pre-Submission Pipeline
Trigger: Claims batch ready for submission
1.Validate data completeness and code combinations
2.Score denial probability against payer-specific patterns
3.Flag high-risk claims with remediation recommendations
4.Route correctable claims back to billers
5.Route complex claims to human review
6.Submit clean claims to clearinghouse
✓
Submitted claims are dramatically cleaner, denial rates drop, and A/R days shrink.
Use Case 2
Payer Pattern Detection
Trigger: New denial trend emerges
1.Detect anomaly in denial rates
2.Cluster root causes
3.Identify policy or edit changes
4.Alert operations
5.Update denial model
✓
Payer policy changes get caught in days, not after a quarter of damage.
Integrations
Practice Management / Billing System
Clearinghouse (Availity, Change Healthcare, Waystar)
Payer Eligibility & Policy Feeds
Coding Reference (ICD-10, CPT, HCPCS)
EDI 837 / 835 Processing
Industries
healthcare
See It In Action
A sample conversation with this agent
Run pre-submission on today's claims batch.
Processing 1,247 claims. Four-stage pipeline: (1) Data completeness validation — required fields, valid code combinations, patient eligibility. (2) Denial probability scoring against learned payer patterns. (3) Flag high-risk claims with specific remediation. (4) Submit clean claims to clearinghouse. Early results: 1,018 clean and submitting, 187 flagged for correction with specific fixes, 42 routed for human review. Average denial probability on flagged batch: 38% without remediation, 6% after applying my fixes.
Why did you flag claim #4421 for review?
Three issues: (1) Procedure code 99214 with diagnosis E11.9 (unspecified diabetes) — this payer denies 23% of unspecified-diabetes E/M claims; diagnosis can likely be coded more specifically based on the encounter documentation. (2) Missing NDC number for the administered J-code. (3) Prior auth number present but format doesn't match this payer's expected pattern. I've drafted the corrections and flagged for a biller to review before resubmit.
Which payer is denying us most frequently this month?
Payer X is at 14.2% denial rate this month (vs. their 9% historical baseline). Root cause pattern: 68% of their new denials are CO-197 (authorization) driven by a policy change on specialist referrals that took effect March 1. I've updated the denial model to catch these upstream, and I've flagged the policy change for your operations team. Payer Y and Z are stable. Recommending a Payer X outreach to clarify the new referral requirements.