Your AI Agent Said the Right Thing. Then It Wrote the Wrong Dosage.

Execution integrity verifies that what a healthcare AI agent writes to clinical systems (EHR notes, prescriptions, referrals) faithfully reflects the actual patient conversation. It goes beyond checking what the agent said to verify what it actually wrote.

Lithrim ingests the conversation transcript and the artifact the AI agent produced (SOAP note, referral letter, etc.), then runs faithfulness, completeness, and safety checks. Each artifact receives a verdict: PASS, WARN, or BLOCK based on alignment with the source conversation.

Lithrim detects critical clinical safety issues including: WRONG_DOSAGE (medication dosage doesn’t match transcript), FABRICATED_HISTORY (medical history not mentioned in conversation), MISSED_ALLERGY (allergy mentioned but omitted from note), WRONG_LATERALITY (left/right body side errors), WRONG_CODE (incorrect billing or diagnostic codes), and MISSED_ESCALATION (urgent findings not flagged for follow-up).

Lithrim is built for companies deploying AI agents in healthcare — clinical scribe companies, telehealth platforms, health plans, and any organization whose AI agents write to electronic health records. It provides the verification layer between the AI agent and the patient record.

AI scribes can introduce several categories of errors into clinical notes: wrong medication dosages, fabricated medical history not mentioned by the patient, omitted allergies, left/right body side errors (wrong laterality), incorrect billing or diagnostic codes, and missed urgent findings that need escalation. A 2024 study found 127 errors across 44 AI-generated clinical notes.

Clinical artifact verification compares the AI-generated document (SOAP note, referral, prescription) against the source patient conversation, checking three dimensions: faithfulness (does every claim have transcript support?), completeness (are all clinically relevant details captured?), and safety (are there dangerous errors?). Each artifact receives a PASS, WARN, or BLOCK verdict.

Traditional AI evaluation measures whether the agent said the right thing — task completion rate, response accuracy, latency. Artifact verification measures whether the agent wrote the right thing — comparing the clinical document it produced against the actual patient conversation. An agent can score 100% on conversation quality while writing a clinical note with fabricated medical history.

Artifact lineage is the end-to-end traceability chain from patient conversation to clinical document to EHR write. It tracks: (1) the raw transcript, (2) HIPAA compliance check results, (3) per-artifact faithfulness, completeness, and safety scores, (4) safety flags like WRONG_DOSAGE or FABRICATED_HISTORY, and (5) the final verdict that gates whether the artifact can be written to the patient record.

Lithrim integrates via API or webhook. Scribe companies send the conversation transcript and the AI-generated clinical note to Lithrim’s /v1/analyze endpoint. Lithrim returns a verdict (PASS/WARN/BLOCK), safety flags, faithfulness score, and evidence spans showing exactly where the note diverges from the conversation. This runs before the note is written to the EHR, acting as a release gate.

A BLOCK verdict means the AI-generated clinical artifact has a faithfulness score below 70% — indicating critical divergence from the source conversation. BLOCK artifacts should not be written to the EHR without human review and correction. Common causes include fabricated medical history, wrong medication dosages, and missed allergies.