Eligibility & Coverage Failures
Insurance inactive at service. Secondary coverage missed. Coverage that doesn't cover the service. Wrong COB order. Preventable with eligibility verification run at the right points, against the right sources.
Most Denials Aren't Surprises. They're Visible Before You Submit.
Lapsed eligibility, missed authorizations, auto-rejected modifiers — predictable failures, not bad luck. We build the automation that catches them before they become denials.
Talk to Us About Denial PreventionTrusted by startups and global leaders
Where Denials Actually Come From
Working a single denied claim costs $25–$118 — $12,500–$59,000/month for a group denying 500 claims, on top of written-off revenue. The higher-leverage move is prevention, not more denial management. Prevention depends entirely on the root cause.
Authorization Failures
No prior auth. Auth for the wrong procedure code. Auth expired before service. Documentation not attached. These trace back to not flagging auth at scheduling and not tracking it through to service.
Coding & Documentation Failures
Combinations that fail payer clinical editing. Missing or wrong modifiers. Codes that don't support medical necessity. Insufficient specificity. Unbundling. These trace back to coding accuracy and the documentation behind it.
Technical & Administrative Failures
Duplicate submissions. Timely filing violations. Wrong demographics. NPI errors. Place-of-service mismatches. Denials that shouldn't exist — no clinical complexity — and the easiest to automate away entirely.
Medical Necessity Failures
Services that missed the payer's clinical criteria for the diagnosis billed. Frequency limits exceeded. Care setting deemed inappropriate. These need clinical documentation plus payer policy intelligence — knowing what each payer requires and making the claim reflect it.
What We Build
Full-stack denial prevention and eligibility automation — from real-time verification through pre-submission editing, denial prediction, and appeals. Each module catches failures at the step where they originate.
The AI Layer
Three AI capabilities that shift revenue cycle operations from reactive denial management to proactive prevention. Each is trained on your data and payer mix — not applied from a generic model.
Denial Prediction That Gets Specific
Denial prediction is only useful when it's specific. "High probability because this payer denies this code/diagnosis when documentation lacks X — here's what it needs to say" is actionable. "68% denial probability" isn't. We train on your claims so the output names the factors driving the score, not just the number.
Eligibility Anomaly Detection
Eligibility data has patterns — insurance active for years that suddenly drops at a Monday check isn't the same as a patient always uninsured. Anomaly detection flags coverage changes most likely to cause claim problems: lapsed coverage, COB shifts, plan changes affecting auth. Issues route for resolution before service, not after denial.
Payer Policy Intelligence
Payer auth requirements, coverage rules, and coding edits change constantly. We maintain current rules for your top payers and apply them automatically at scheduling, coding, and pre-submission — not a reference tool staff consult, but logic in the workflow.
Denial Prevention Systems We've Built. What Changed.
Each result is tied to a specific denial problem — an eligibility failure rate too high to manage, an authorization process with no screening at scheduling, a payer editing pattern nobody had mapped. Click through to see what the prevention infrastructure fixed.
Talk to Us About Denial Prevention3.1%
Denial rate — Multi-specialty Group (20 providers). Down from 21%. Eligibility denials eliminated, auth denials down 89%.
94%
Pre-submission edit catch rate — Cardiology Practice. Modifier denials eliminated. AR days reduced 18.
Zero
Auth denial rate — Behavioral Health Network. Telehealth coding compliance 100%. Zero filing violations in 12 months.
78%
Implant denial reduction — Ambulatory Surgery Center. Medical necessity appeal success up to 91%.
94%
Eligibility denial reduction — Health System Outpatient. COB errors eliminated at point of registration.
0.8%
Drug administration denial rate — Oncology Practice. Down from 14%. Chemo prior-auth gaps closed.
How We Build
We start with your denial data by root cause, not a template. Hover or tap a stage to see what it involves.
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Start With Denial Data
Start With Denial Data
We analyze your denial patterns by payer, provider, and reason code. The gaps set the priority order for everything we build.
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Payer Rules Built In
Payer Rules Built In
Each top payer's auth rules, edits, and filing limits are built into the platform and maintained as policies change.
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Verify at Every Touchpoint
Verify at Every Touchpoint
Eligibility runs at scheduling, registration, check-in, and pre-submission — with results that reach staff while action is still possible.
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Integration First
Integration First
Automation is wired into scheduling, registration, and billing — so it runs where the work already happens, not in a separate system.
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Feedback Loop
Feedback Loop
Every returned denial is traced to its upstream failure and used to improve the prevention logic. The system gets better over time.
Compliance We Treat as Engineering Inputs, Not a Checklist
Every standard below is scoped during discovery and built directly into the platform — across the data privacy, EDI, coding, payer, legal, and security frameworks that govern denial prevention and eligibility automation.
Data Privacy
HIPAA & Healthcare Data Privacy
Foundational data privacy and security frameworks — applied to every data store, transmission, and access control.
Transaction Layer
EDI Transaction Standards
Standards governing how eligibility, claims, remittance, and authorization data move between providers, clearinghouses, and payers.
Coding & Editing
Clinical Coding & Editing
Standards governing how diagnoses and procedures are coded, classified, and represented — and what clinical edits they must survive.
Payer & Coverage
Payer Rules & Patient Rights
Payer billing rules, federal claims processing manuals, and patient cost-transparency protections built into denial prevention workflows.
Security
Security & Payment Protection
Security certifications and payment standards required for handling protected health information and patient financial data.
Global Data Protection
Global Privacy Regulations
Cross-border data protection regimes scoped in when the platform serves patients across multiple jurisdictions.
The Best Time to Prevent a Denial Is Before the Claim Is Submitted. The Second Best Time Is Now.
Every denial your team works is a claim that should have gone out clean. Prevention costs less than working one — and revenue lands on first submission, not sixty days later if the appeal wins. Thirty minutes, no pitch: where your denials come from and how to stop them upstream.
Book a Discovery Call
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Frequently Asked Questions
[ 1 ]
What percentage of denials are actually preventable?
It varies, but typically 60-75% of denial volume traces to preventable root causes — eligibility failures, authorization gaps, coding errors, and technical administrative failures automation addresses directly. The remaining 25-40% are medical necessity denials and coverage disputes needing clinical documentation and appeal strategy, not upstream prevention. We tell you your specific preventable percentage during discovery, before the project begins.
[ 2 ]
How does real-time eligibility verification work technically?
We connect to your top payers through X12 270/271 EDI transactions — the standard electronic eligibility inquiry/response format. The query fires at the trigger point — scheduling, check-in, pre-submission — and a structured response returns within seconds with coverage status and benefit details. For payers without real-time EDI, we use clearinghouse batch verification, timed to when the information is needed.
[ 3 ]
How do you keep payer authorization requirements current?
We maintain payer authorization data through payer policy monitoring, clearinghouse feeds, and the feedback loop from your own denial data. When a payer changes auth requirements for a procedure or medication, the platform updates. When your denial data shows a new requirement emerging — a procedure that didn't previously need auth now drawing authorization denials — it gets added to the screening logic.
[ 4 ]
How long does implementation take?
A focused implementation — eligibility automation, authorization screening, pre-submission editing — for a single-specialty practice typically runs three to five months. A full platform with AI denial prediction, payer policy intelligence, and appeals automation runs six to ten months. We give you a milestone-based timeline after discovery.
[ 5 ]
What kind of denial rate reduction can we realistically expect?
It depends on your current denial rate and its root cause mix. Organizations above 15% with a high proportion of eligibility and authorization failures — the most automatable categories — consistently drop to 3-5% within six months of full implementation. Lower starting rates or more medical necessity denials see more modest but still meaningful improvement. We give you a realistic projection from your specific denial data during discovery.
[ 6 ]
Who owns the platform?
You do. Full IP transfer at project close. No per-claim fees, no licensing costs tied to your denial volume.
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