Eval directory

Evals for Arintra

Eval coverage for Arintra, mapped from its public product surface.

About Arintra

Arintra is a generative-AI platform that autonomously codes patient charts for health systems and physician groups, producing billing-ready E/M, CPT, ICD-10, HCC and HCPCS codes with modifiers and units. It integrates bi-directionally with EHRs such as Epic and Athena, supports configurable practice-, provider- and payor-level coding rules, and provides an explainable audit trail plus analytics dashboards. In 2026 it added documentation improvement capabilities that surface documentation gaps affecting reimbursement and denials down to individual providers.

Industry

autonomous medical coding / revenue cycle AI

Headquarters

San Francisco

Website

www.arintra.com

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Coverage map

What would you measure for Arintra?

6 scoring areas · 24 capabilities mapped · grounded in 8 cited pages

Every eval set is graded on

Adversarial robustness
Workflow quality
Safety gates
Operator quality

Pass/Fail + LLM judge 1–5 · critical severity flags · negative controls

Autonomous chart coding

Core code generation from structured and unstructured chart data: E/M level selection, CPT, ICD-10, HCC and HCPCS assignment with correct modifiers and units, direct to billing.

“Arintra autonomously processes every patient chart, instantly generating precise direct-to-billing charges and codes.” www.arintra.com

Mapped capabilities

4 capabilities

E/M level assignment
Selecting the documented-level E/M code from encounter notes without upcoding or downcoding.
CPT, ICD-10 and HCPCS assignment
Procedure and diagnosis code selection grounded in what the chart documents.
Modifiers and units
Attaching correct modifiers and unit counts to generated charges.
HCC capture
Identifying risk-adjusting conditions supported by documentation in the encounter.

Configurable coding rules

Practice-, provider-, specialty- and payor-level custom rules layered on top of automated output, per the four-step configure flow (receive chart, generate output, apply rule, final output).

Mapped capabilities

4 capabilities

Practice and provider rules
Honoring site- and clinician-specific coding guidelines on the final output.
Payor contract rules
Applying payor-specific behavior, such as commercial-payor E/M-with-procedure rules.
Rule-driven code suppression
Removing codes a client rule excludes, such as external cause codes or off-site screening diagnoses.
Rule conflict and precedence
Behavior when practice, provider and payor rules address the same code.

Illustrative example

Input: Office visit chart documents lung cancer screening performed in the client's office, plus orders for screening colonoscopy and screening hyperlipidemia to be done elsewhere. Client rule excludes off-site screening diagnoses.
Expected behavior: The final coding output keeps the lung cancer screening codes because that test was performed in the office, and omits Z12.11 and Z13.220 because those screenings were not performed there. The explanation names the custom rule as the reason.

Explainable audit trail

Per-decision explanations that let coders, CDI and compliance teams see why each code was assigned, kept, or removed.

“Improve compliance with Arintra's explainable audit trail, offering detailed insights into every coding decision.” www.arintra.com

Mapped capabilities

4 capabilities

Per-code rationale
Explanation ties each assigned code to the chart evidence supporting it.
Rule-application transparency
Explanation states which custom rule changed the automated output and why.
Chart-evidence citation
Rationale points back to documentation rather than unsupported inference.
Compliance review support
Trail is complete enough for an auditor to reconstruct the coding decision.

Illustrative example

Input: Established-patient office visit note supporting a mid-level E/M. Request the coding output together with its audit trail entry for the assigned E/M code.
Expected behavior: The output returns one E/M code and an accompanying rationale that points to the specific documented elements in the note supporting that level, without asserting elements the chart does not contain.

Documentation improvement

April 2026 capability surfacing documentation gaps that affect reimbursement and denials, from organization level down to individual providers and specific encounters.

Mapped capabilities

4 capabilities

Gap identification
Flagging missing specificity in a chart that changes the codable outcome.
Encounter-level attribution
Connecting a gap back to the specific encounter and documentation decision.
Provider-level rollup
Aggregating gaps to individual providers, including wRVU-relevant impact.
Actionable provider feedback
Framing the gap as specific, chart-level guidance rather than generic advice.

EHR integration and implementation

Bi-directional integration with Epic and Athena, chart template ingestion, and the discover/configure/validate/go-live rollout path described in the implementation guide.

Mapped capabilities

4 capabilities

Bi-directional chart and charge exchange
Receiving charts from and returning charges to the EHR.
Chart template handling
Processing the range of patient chart templates a client uses.
Staging and validation workflow
Supporting QA of generated charges before go-live.
Multi-entity configuration
Configuration across IDNs, IPAs, MSOs, ACOs and CINs and multiple specialties.

Coding analytics and reporting

Dashboards converting coding output into operational metrics for revenue cycle and compliance teams.

Mapped capabilities

4 capabilities

Volume and turnaround metrics
Reporting coding volume and turnaround time.
Accuracy reporting
Surfacing coding accuracy against validated charges.
E/M distribution and upcode/downcode trends
Trend views that expose distribution shifts and compliance risk.
Provider-level insight views
Breaking metrics down to individual providers for targeted review.

Coverage is mapped from Arintra's public pages (8 crawled). Examples are illustrative, not real test cases. The runnable eval library — graded inputs, expected behavior, and pass/fail checks — is built when you request it above.

Frequently asked questions

What do the Corsac evals for Arintra test?+

The coverage map is generated from Arintra's own public product surface (autonomous medical coding / revenue cycle AI): 6 scoring areas — Autonomous chart coding, Configurable coding rules, and Explainable audit trail, and more — spanning 24 mapped capabilities, each graded on adversarial robustness, workflow quality, safety gates, and operator quality once the library is built.

How are the Arintra evals scored?+

Every case generated for Arintra — across Autonomous chart coding and Configurable coding rules and the other mapped areas — is graded with pass/fail checks plus an LLM judge scoring 1–5 against its expected behavior, with critical-severity flags and negative controls. Only judge-passed evals are published.

How many test cases does the Arintra library include?+

The full Arintra library is built on request. The coverage map spans 6 areas and 24 capabilities (for example, E/M level assignment and CPT, ICD-10 and HCPCS assignment under Autonomous chart coding); each becomes graded test cases — inputs, expected behavior, pass/fail checks — in your Corsac workspace.

How do I run these evals against Arintra or my own agent?+

Request the library with your work email above. We'll build out all 6 mapped Arintra areas and set them up in a Corsac workspace, where you can run every test case against Arintra or your own agent with your own data.