Expertise
Coding expertise by specialty, code set, and revenue cycle surface
Automation readiness is not uniform. It is determined by documentation structure, code set depth, and payer rule density — so scope is set per specialty, not per product tier.
Production benchmarks
- 95%+
- F1 on discharge summaries
- 60%
- Reduction in coder review time
- 4 wks
- Typical integration to go-live
- Zero
- EHR workflow changes required
01Capabilities
Four capability areas, one clinical pipeline
Coding, NLP, interoperability, and datasets are the same architecture viewed from four angles. Select an area to see what it does and where it sits in the pipeline.
Capability 01
Automated medical coding — production-grade accuracy on real charts
Clinical NLP engine that reads unstructured notes and returns ICD-10, CPT, and HCPCS code suggestions with evidence linking, confidence scoring, and payer rule validation — before suggestions reach the coder.
Evidence-linked suggestions
Every code carries the exact source span that generated it, so validation takes seconds.
Confidence stratification
High-confidence codes accept in one step; low-confidence rows are flagged for judgement.
Payer rule layer
NCCI edits, bundling, and payer-specific policy applied outside the standard code sets.
Coder authority preserved
Accept, modify, or reject per suggestion — final submission stays with the coding team.
Ingest
EHR notes, PDFs, dictations
De-identify
PHI removed before model sees text
Extract + code
Clinical NLP · negation · ICD-10 specificity
Evidence linked · payer rules applied
Coder review
Accept · modify · reject with source text
03Integration & Deployment
Integration considerations and deployment timeline
The most common source of extended deployment timelines is not technical complexity — it is the security review process triggered by direct EHR API access. Understanding this early significantly affects project planning.
Kickoff
Discovery
SOP alignment, payer mapping
Week 2
Pipeline setup
PHI validation, integration
Week 3
Pilot — 500 charts
Accuracy measurement on your data
Week 4
Production
Full rollout + feedback loop
SFTP path — no IT security review triggered, typically 2 weeks faster
Direct EHR API — triggers full IT security review, add 4–8 weeks
Integration path selection is the single largest determinant of go-live timeline. Secure file exchange (SFTP) bypasses the IT security review process that direct API access triggers.
REST API
Structured JSON output, most common
Secure SFTP
Fastest to deploy, no security review triggered
Direct EHR connector
Epic, Cerner, Meditech
RCM system feed
Optum, Waystar, Experian Health
05Standards & Compliance
Code systems and compliance architecture
The system outputs to the standard code sets and interoperability formats in use across hospital billing and RCM operations. PHI handling is architecturally integrated, not a configuration option.
03Engagement Model
How a specialty scope becomes production output
- 01
Documentation review
A sample of your own notes across the target specialties, assessed for dictation patterns, structure, and abbreviation density.
- 02
Scope and SOP alignment
Code sets, payer rules, and coder authority boundaries agreed in writing before any pipeline work begins.
- 03
Pilot on 500 charts
Accuracy measured on your data, reported as precision, recall, and F1 stratified by document type — not as one aggregate figure.
- 04
Production and feedback loop
Coder accept, modify, and reject decisions feed retraining, so accuracy compounds against your documentation patterns.
Contact
Talk to someone who has built this in production
Bring your documentation patterns, payer mix, and integration constraints. We will walk through accuracy expectations and a realistic go-live sequence.