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The ASP-RCM AI Suite

The ASP-RCM AI Suite. Every vendor says “AI.” We’ll show you the model card.

AI in revenue cycle is now table stakes. Trustworthy AI is the moat. Six capability clusters, eight production models, one credentialed human gate. Every model has a published evaluation cadence behind it. No black boxes. No “agentic” theater.

8 production models 6 capability clusters CPC human gate Quarterly external audit Retrained on your 835s
Position
AI runs volume.
People run judgment.
Evaluators run trust.
A different bar than the rest of the market
Most AI-RCM vendors stop at the first sentence. We finish the paragraph.
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AI capability hub

32 pages of AI for revenue cycle, without the hype.

Below: every AI capability we operate, every vendor-evaluation framework we use, every specialty-specific AI playbook, and the trust questions we recommend asking any AI vendor. No vendor names in the evaluation pages. Buyer-perspective only.

Plus the live tools we maintain.
The ABA Payer Matrix covers 244 cells across 52 jurisdictions and 8 payers, every cell linked to source, refreshed monthly. The 50-state ABA RCM cluster covers state-by-state Medicaid programs, dominant Blues, MCO contracting, and BCBA credentialing for every U.S. market.
The position

The market sells AI like it’s the answer. ASP-RCM sells the governance around it.

In 2024, “does it have AI” was a buying question. In 2026, it isn’t. Every RCM vendor on your shortlist now claims AI on every screen of their pitch deck. The interesting question moved.

The question that matters now: can you trust the output enough to bill against it? That answer doesn’t live in a model name or a parameter count. It lives in the human gate, the eval cadence, and the audit trail.

That’s the page you’re reading. This isn't a feature list. It's a governance brief for the AI we run on your revenue.

Diligence framework

Three questions every CFO should ask any AI-RCM vendor.

If a vendor can’t answer all three with a straight face, they’re selling you a demo, not a system. Here’s how the market typically scores. And here’s how we score.

01
Is there a credentialed human in the loop, on every chart that matters?
Pure-AI vendor
No. The pitch is “autonomous.” The audit is sampling.
Bolt-on AI
Sometimes. Coder reviews suggestions, but at low volume.
ASP-RCM
CPC-credentialed coder reviews every complex chart. Random + risk-based QA on the rest. Independent quarterly audit.
02
Does it retrain on your 835s, or a generic corpus?
Pure-AI vendor
Generic foundation model. Same denial logic for a Florida ER and a Texas ABA group.
Bolt-on AI
Industry-tuned, but rarely tenant-tuned. Updates on vendor cadence, not yours.
ASP-RCM
Payer-specific learners trained on your 835 outcomes. Denial-prediction model retrains weekly on your remits.
03
Can you see the model’s reasoning on a denied claim?
Pure-AI vendor
Black box. “Trust the model.” Audit trail is a status field.
Bolt-on AI
Decision logged. Reasoning often isn’t. Hard to defend at a payer appeal.
ASP-RCM
Per-claim reasoning trace, scored confidence, and human-attributable action log. Compliance-grade on every account.
The Suite

Eight tools, organized by what the AI actually does.

The eight tools aren’t a feature list. They’re a portfolio of six capability clusters. Each cluster solves a distinct AI problem (sequence modeling, payer rule learning, time-series surveillance, etc.). Click any model for the full deep-dive.

01 Front-end intelligence

Real-time payer reasoning & coverage discovery

Two models running pre-visit and on every aged self-pay account. Real-time 270/271 against national payers, plus a multi-payer sweep that finds active coverage hidden in registration data. Stops eligibility-driven denials before the claim is ever built.

02 Autonomous coding

Multi-specialty coding with a CPC gate

Sequence-to-sequence model trained on documentation patterns across hospital E/M, surgical, OB, ortho, cardiology, behavioral health, ABA, and HCC risk-adjustment. Confidence-scored. Below threshold routes to a CPC-credentialed coder. Every complex chart, not random sampling.

03 Predictive yield

Pre-submission scoring & upstream attribution

Two complementary models. The first scores every claim against payer-specific denial patterns and holds the high-risk ones. The second maps denials that did happen back to their upstream owner (registration, coding, eligibility, auth) so the same denial doesn’t come back next month.

04 Continuous surveillance

Always-on claim status monitoring

Time-series surveillance over every submitted claim. 276/277 polling on payer-specific cadence, IVR/portal scraping fallback for payers that don’t support 276, payer-behavior baselining so anomalies surface fast. Specialists work cases, not hold lines.

05 Workflow orchestration

Dollar-weighted routing & auditable action

Optimizer that prioritizes the AR queue by recovery probability × dollar value, not by age. Routes by specialist skill, payer, and complexity. Logs every action against every claim, compliance-grade. The work-list that finishes the work.

06 Financial close AI

Daily three-way reconciliation

Match-and-resolve engine that reconciles bank deposits, lockbox files, ERAs, and posted transactions every business day. Auto-posts 835s with adjustments. Flags variances inside 24 hours, not at month-end. Compresses the close.

Model cards

Eight production models. One spec sheet each.

For every model in the Suite: what it does, where the human gate sits, how it’s evaluated, and the cadence of retraining. Hover any card and tap through for the full workflow + capabilities.

M-01 / FRONT-END

Eligibility Verification AI

live · 270/271

Real-time eligibility against national payers (commercial, Medicaid, Medicare, MA). Surfaces inactive policies, deductible/copay, prior-auth requirements, and COB order before the patient walks in.

Evaluated by
First-pass match rate against payer 271 ground truth, weekly.
Retraining
Continuous on payer 271 responses; monthly drift review.
Human gateFront-desk re-verifies on any anomaly: terminated policy, wrong primary, missing auth. AI never blocks a check-in unilaterally.
Full model card
M-02 / CODING

Autonomous Coding AI

live · multi-specialty

Full coding (CPT, ICD-10, HCPCS, modifiers, sequencing) across hospital E/M, surgical, OB, ortho, cardiology, behavioral health, ABA, and HCC risk-adjustment. Confidence-scored per chart.

Evaluated by
Independent CPC review of a meaningful chart sample, every quarter.
Retraining
Specialty-tuned models updated on coder feedback + audit corrections.
Human gateCPC-credentialed coder reviews every chart below confidence threshold. Risk-based QA sample on the rest. Not random sampling at the rate level. Chart-level.
Full model card
M-03 / YIELD

Denial Prediction AI

live · payer-specific

Pre-submission scoring of every claim against payer-specific denial patterns. Surfaces missing modifiers, NDCs, units, auth gaps, and medical-necessity risk. Each one ships with a fix suggestion, not just a risk score.

Evaluated by
Precision/recall against 835 outcomes, weekly per payer cohort.
Retraining
Weekly on your 835 remits; payer policy bulletins ingested as features.
Human gateAbove threshold, claim holds for biller review with an actionable fix list. AI never auto-releases or auto-rejects.
Full model card
M-04 / FRONT-END

Insurance Discovery AI

live · multi-payer sweep

Finds active coverage hidden in self-pay accounts (Medicaid retro-eligibility, COBRA, secondary, tertiary) via demographic + SSN multi-payer sweep. Daily re-sweep on aged AR.

Evaluated by
Hit rate × recovered cash, monthly per AR cohort.
Retraining
Sweep heuristics tuned per-payer; monthly false-positive review.
Human gateAR specialist verifies coverage and rebuilds the claim on the new payer. Found coverage is never auto-billed without confirmation.
Full model card
M-05 / SURVEILLANCE

Claim Status Surveillance

live · 276/277 + IVR

Continuous surveillance across the claim lifecycle. 276/277 polling on payer cadence, IVR/portal scraping fallback, payer-behavior baselining, aging-bucket triggers. Routes only human-needed cases to specialists.

Evaluated by
Time-to-status-change detection vs payer adjudication baseline.
Retraining
Per-payer cadence model retuned monthly on observed turnaround.
Human gateAR specialist works every claim that breaches its expected adjudication window. AI never auto-writes off, auto-appeals, or auto-resubmits.
Full model card
M-06 / WORKFLOW

AR Workflow Engine

live · $-weighted

Optimizer that prioritizes the queue by recovery probability × dollar value. Routes by skill, specialty, payer, complexity. Logs every action with timestamp and actor for a compliance-grade audit trail per claim.

Evaluated by
Recovery-per-touch + first-touch-on-aged metrics, weekly.
Retraining
Routing heuristics tuned monthly on outcome-weighted specialist scorecards.
Human gateSenior AR lead reviews escalations, sampled QA, and any account flagged compliance-sensitive. Engine recommends, lead approves writes.
Full model card
M-07 / YIELD

Denial Root-Cause Analytics

live · CARC/RARC + owner

Maps every denial past CARC/RARC code into its upstream owner: registration, coding, eligibility, auth, or payer policy. Detects repeat-denial patterns across provider × payer × code. Fix at source, not at appeal.

Evaluated by
Repeat-denial decline rate per pattern, monthly trend review.
Retraining
Reason-code taxonomy refreshed quarterly on payer policy bulletins.
Human gateSenior partner walks the trends with your CFO every month. Provider retraining and payer escalations are human-led, AI-evidenced.
Full model card
M-08 / CLOSE

Cash Reconciliation AI

live · daily 3-way

Daily three-way reconciliation across bank deposits, ERA/EFT, and posted transactions. Auto-posts 835s with adjustments + contractual write-offs. Variances flagged inside 24 hours, not at month-end.

Evaluated by
Match rate & time-to-variance-resolution, daily dashboard.
Retraining
Match heuristics retuned per-payer EFT/ERA schema changes.
Human gateAR specialist resolves every flagged variance and any orphan deposit. Refunds + credit balances are compliance-tracked, never auto-issued.
Full model card
How we sit in the market

The four kinds of vendor on your shortlist. And which one we are.

Every AI-RCM vendor falls into one of four archetypes, and each archetype has a structural gap. We’re calling the gaps out by category, not by name. Diligence the rest yourself.

Archetype
What they pitch
Where it breaks
ASP-RCM
Pure-AI software vendors
SaaS · subscription · “autonomous”
“Replace your billing team with AI. Pay per claim. Watch the dashboard.”The deck is a model card and a logo wall.
No accountable senior partner. When the model is wrong on 1% of charts at hospital scale, that’s an audit risk no dashboard can absorb. You own the cleanup.
We sell outcomes. Not software. A senior partner is named on your account and their bonus is tied to your collections, not your seat count.
Clearinghouse + AI bolt-on
legacy pipes · features added on top
“We already move your claims. Now there’s an AI tab.”AI is a feature line on the renewal.
AI is bolted onto a switching pipe, not built into a service. The model touches the claim once. Nobody on their side gets paid to fix the upstream cause.
AI is built into the service. Not bolted onto pipes. Every layer feeds the next, and a senior partner closes the loop on root cause monthly.
Single-point AI tools
one capability · stitched into your stack
“Best-in-class AI coder.” “Best-in-class AI denial predictor.”Pick three. Integrate. Maintain.
You become the system integrator. Three vendors, three contracts, three audit trails, three different definitions of “done.” Nobody owns the cycle.
One Suite, one accountable senior partner. One audit trail per claim from eligibility to cash posted. The integration is our problem, not yours.
Offshore RCM, low-tech
labor arbitrage · scripts & macros
“We do it cheaper at scale.”The pitch is FTE rate cards.
Volume problem solved with more people. Quality problem unsolved. Eight hold-line FTEs is not a strategy; it’s a margin until the payer changes a rule.
We run AI on volume and a credentialed human gate on judgment. The cost-to-collect line bends because the work-mix bends, not because we hired more.
Trust & governance

The part of the AI conversation most vendors skip.

Independent audit cadence, role-defined human gates, model-retraining policy, and what happens when the AI is wrong. This is the section that closes with a security team.

Independent audit

Quarterly external CPC review

An external CPC firm pulls a meaningful sample of charts the AI coded and reviews them blind. Findings publish to client leadership and feed back into model retraining. No marking your own homework.

cadence: quarterly
Human gate, by role

Defined credential per layer

Coding gate: CPC. Eligibility/discovery gate: Patient Access lead. AR escalations: Senior AR lead. Compliance-sensitive accounts: Senior partner + Compliance Officer. Every gate is named and credentialed.

CPC · CRCR · CCS-P · COC
Retraining cadence

Models stay current with payers

Denial prediction retrains weekly on your 835 remits. Eligibility heuristics drift-checked monthly. Coding models updated against quarterly CPC audit findings. Reason-code taxonomy refreshed on payer policy bulletins.

weekly · monthly · quarterly
Compliance & data

HIPAA, SOC 2 Type 2, ISO 27001, HITECH

U.S. data residency for production claim data. PHI access logged at the user/action level. Independent SOC 2 Type 2 audit annually. ISO 27001 certified ISMS. Model training never on identifiable PHI.

U.S. residency · audited annually
When the AI is wrong

Named escalation path

Every account has a written SLA on response time and a named senior partner accountable for outcome. AI errors caught at the gate go back into retraining; AI errors that reached a payer get worked, root-caused, and reported in the QBR.

SLA in 90 days · named partner
What we don’t do

The autonomy lines we won’t cross

No AI auto-write-offs. No AI auto-appeals. No AI auto-refunds. No coding submitted without a CPC gate on the charts that matter. No model output presented to a payer without a human-attributable action log behind it.

human-in-the-loop, by policy

How a chart actually moves through the Suite, with the gate visible.

Coding example · M-02
STEP 01
Chart enters queue
EHR pushes documentation. Specialty + provider + payer attached as features.
actor: system
STEP 02
AI assigns codes
Full coding (CPT, ICD-10, HCPCS, modifiers, sequencing) with confidence per code.
actor: M-02
STEP 03 · GATE
CPC review on complex
Below confidence threshold or specialty-flagged → routes to credentialed coder. Human approves, edits, or rejects.
actor: CPC
STEP 04
QA sample
Random + risk-based sampling on auto-coded charts. Senior coder scores, errors flow back into retraining.
actor: Senior coder
STEP 05
Quarterly external audit
Independent CPC firm pulls a sample blind. Findings published to client leadership.
actor: External CPC

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