98%
Multi-specialty Group (18 providers) — 19% denial rate, AR days at 52. → Denials 2.8%, AR days 14, manual work down 60%.
Most organizations are managing six of them. We build end-to-end RCM platforms that automate the full cycle — first patient interaction through final payment — with AI finding the leaks before they become losses.
Talk to Us About Your RCM Platform
An end-to-end platform fixes the handoffs. Data flows from scheduling through payment without manual re-entry, errors are caught before they propagate, and the AI layer sees the full claim journey rather than one phase of it.
Capture the insurance and demographic data the cycle depends on, flag visits that will need prior authorization, and get billing right before the encounter rather than after.
Real-time eligibility at scheduling and again at check-in — returning deductible, copay, coinsurance, and out-of-pocket so patient responsibility is estimated accurately upfront.
Identify which procedures need authorization from which payers at ordering, pre-populate requests from clinical docs, track status in real time, and alert before expiration.
Automated capture from clinical documentation — notes, procedures, supply usage — with discrepancy and missing-charge flagging. Mobile entry fast enough that staff use it.
AI-assisted ICD-10 and CPT suggestions from documentation, gaps flagged before they fail an audit, and provider query workflows that fix docs before the claim ships.
Pre-submission validation against payer-specific rules — modifiers, bundling edits, code compatibility, auth, timely filing. Failed claims are held and routed for correction, not denied.
EDI 837 submission through clearinghouse and direct payer connections, real-time 277 status tracking, rejection management, and automated resubmission for correctable claims.
ERA-based denial categorization by root cause, routing with the context needed to appeal in-system, deadline management, and pattern reporting that surfaces the upstream fix.
Automated ERA posting, manual EOB entry for non-ERA payers, contractual adjustments, and every payment compared to the contracted rate — variances flagged for recovery.
Cost estimates, balance statements, payment plans, and online payment — with reminders calibrated to balance and history, plus financial-assistance screening.
Payer contract terms maintained in-platform for real-time adjustment and underpayment detection, plus analytics on which payers underpay and where renegotiation pays off.
They have six or seven smaller ones that add up to one. Point solutions don't fix the handoffs between steps — where most leakage happens. An end-to-end platform fixes them.
Talk to Us About Your RCM Platform
Each platform below replaced a revenue cycle that was leaking money. The numbers are measured in production, not projected in a pitch deck.
Multi-specialty Group (18 providers) — 19% denial rate, AR days at 52. → Denials 2.8%, AR days 14, manual work down 60%.
Oncology Practice — Auth gaps and incomplete drug-cost capture. → Auth denials gone, drug recovery up 22%, coding errors down 85%.
Behavioral Health Network (8 locations) — Time-based coding errors. → Clean claim rate from 69% to 97%.
Ambulatory Surgery Center — Implant capture missing, underpayments untracked. → Implant recovery up 31%, $180K/quarter recovered.
DSO Dental Group (25 locations) — 25 billing operations, no group visibility. → Unified RCM, group denial rate down 60%.
Home Health Agency — Documentation and billing disconnected. → Medicare compliance 100%, AR days 61 to 22.
We design the handoffs first and build the steps around them. Drag, click a card, or use the dots to walk the approach end to end.
Every setting has its own payer mix, coding requirements, and revenue cycle failure points. Here's where we've built end-to-end platforms that collect more of what the clinical team earned.
Across the full cycle, not just one step. A model that only sees the claim at submission misses what was visible at scheduling — an AI layer spanning the full cycle sees all of it. Hover a card to see what each model does.
Collecting ninety-five percent of what you earn takes constant effort. The five percent that doesn't get collected isn't lost because the care wasn't delivered — it's lost because the infrastructure wasn't built to protect it.
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Compliance is a design constraint we wire in from day one — not a review step before launch. We build to the standards that govern healthcare billing and data across the regions our clients operate in.
Patient data protected across every region you operate in.
Independently audited security controls and PCI-compliant payment flows.
The X12 transaction set and government billing rules built into the platform as maintained logic — not a configuration exercise your billing team manages by hand.
Coding and fee-schedule standards calibrated to your payer mix, with the specificity that survives audit engineered into every claim rather than corrected after a denial.
Built to the price-transparency and patient-protection rules.
STARK and Anti-Kickback considerations engineered into billing logic.
Get in touch
Thirty minutes. No pitch. An honest discussion about where your revenue cycle is losing money and what closing those gaps would actually require.
Point software automates one or two steps. An end-to-end platform connects every step in one system where data flows without re-entry, errors are caught before they propagate, and the AI sees the full claim journey. The difference shows up in the handoffs — where most leakage happens.
A single-specialty platform typically runs five to eight months. An enterprise platform across multiple specialties, locations, and complex payers with full AI runs ten to sixteen months. You get a milestone-based timeline after discovery.
Migration scope — claims, AR aging, payment history, patient balances — is defined during discovery. We tell you what migrates cleanly, what needs transformation, and what the parallel operation looks like. Nothing is discovered at go-live.
We extract two to three years of historical claims with outcomes during the build. Denial prediction, coding, and AR prioritization models are trained and validated before launch, and keep improving on live data.
Yes — and this is where custom builds beat commercial options. We configure specialty-specific coding, payer rules, and documentation requirements within one unified platform rather than separate systems that don't share data.
You do. Full IP transfer at project close — source code, documentation, trained model artifacts. No per-claim fees, no licensing that scales with your billing volume.