Pre-submission denial scoring
TensorRT-compiled NeMo classifier scores every claim in under 100 ms before submission. [ASPIRATIONAL]
Product · Revenue intelligence
Revix —Catch revenue leaks before they ship.
Revix applies RAPIDS GPU analytics to your claims history and a NeMo denial-risk model to every outgoing claim — surfacing undercoding opportunities, predicting payer denials before submission, and benchmarking your practice against anonymized specialty peers.
Layer 4 — revenue intelligence on top of Codexa and Authra
RAPIDSNeMoNVIDIA InceptionERA / 835HIPAAMIPS · MACRA
RAPIDS claims scan<5 min
Denial risk score<100 ms
Undercoding flagNeMo NLP
Peer benchmarkspecialty
The problem
Why Revix exists
Specialty practices lose 5–15% of collectible revenue to preventable denials and systematic undercoding. Existing RCM analytics tools show what happened last quarter; Revix scores every claim before it leaves the practice and flags every encounter where the documentation supports a higher code.
- Pre-submission denial risk score (0–100) displayed inline in Codexa [ASPIRATIONAL]
- NeMo NLP undercoding detector — compares documented complexity to submitted E/M level
- RAPIDS GPU analytics over multi-year, multi-million-claim ERA/835 history
- Specialty-peer benchmarking: coding mix, denial rate, and E/M distribution
01 / Ingest
Five years of claims, minutes to scan.
RAPIDS cuDF parses ERA/835 remittance data at GPU speed — 10M claim lines in under 5 minutes, joining to Codexa encounter records for full context.
02 / Predict
Score the claim before it ships.
A NeMo denial-risk classifier — trained on payer adjudication history and compiled by TensorRT — scores every outgoing claim in under 100 ms. The score surfaces inline inside Codexa's review UI. [ASPIRATIONAL]
03 / Flag
Find the money left on the table.
NeMo NLP compares the documented clinical complexity in each encounter note to the submitted E/M level — flagging every instance where the documentation supports a higher code.
04 / Report
The full picture, every quarter.
A NeMo LLM generates CFO-ready quarterly reports: top denial codes, undercoding patterns, peer benchmark, and estimated recoverable revenue. [ASPIRATIONAL]
Capabilities
What Revix does
Undercoding detection
NLP compares note complexity to E/M level — the single most common revenue leak in specialty medicine.
Payer pattern analytics
RAPIDS GPU clustering of ERA/835 data identifies denial patterns by payer, code, modifier, and provider.
Revenue reports
NeMo LLM generates quarterly CFO-ready summaries: top denial codes, undercoding trends, recoverable revenue. [ASPIRATIONAL]
Peer benchmarking
Compare your coding mix, denial rate, and E/M distribution against the anonymized Scribara specialty cohort.
Codexa integration
Denial risk score and undercoding flag surface inline in the Codexa review UI — one workflow, zero context-switching. [ASPIRATIONAL]
GPU-essential
Why accelerated compute is required
Scanning a 5-year, 10M-claim ERA/835 history in RAPIDS takes under 5 minutes on GPU; CPU Pandas would take hours per scan. TensorRT per-claim denial scoring must complete in under 100 ms — a hard SLA that CPU inference cannot meet at the submission rate of a 50-provider practice.
- RAPIDS cuDF + cuML for GPU-parallel claims analytics
- TensorRT denial-risk model <100 ms per-claim SLA
- NeMo training on H100/H200 — denial predictor + undercoding NLP
- NIM on NVIDIA AI Enterprise for on-prem health-system deploy [ASPIRATIONAL]
RAPIDS cuDF / cuMLERA/835
NeMo denial modelH100/H200
TensorRT inference<100 ms
Triton servingmulti-tenant
Impact
What it moves
0
Per-claim denial scoring SLA
0
Max specialty revenue leakage [ASPIRATIONAL]
0
Claims scanned per analytics run
0
RCM analytics market (US, 2026)
The ecosystem
Works with the rest of Scribara
Revix sits on top of the encounter data layer, sharing analytics with the full platform.
Answers
Frequently asked
Revix ingests ERA/835 electronic remittance files from your clearinghouse and joins them to Codexa encounter records via a secure SFTP or API connection.
Yes — the NeMo model is trained per payer on your adjudication history, so scores reflect that payer's specific denial patterns and policies for your specialty.
An outcome-based pricing option (share of documented revenue recovery above baseline) is planned for enterprise customers. Contact us for terms. [ASPIRATIONAL]
Stop sending money to the payer.
See Revix score your last 12 months of claims and surface the recoverable revenue.