Clinical NLP · Applied AI

Brevai
Clinical Note Summarizer

Paste any clinical note discharge summary, SOAP note, consult, or progress note and get a structured AI-generated summary in seconds, in any language.

Demo only — do not enter real patient data. This tool is not HIPAA-compliant and is not intended for clinical use. No text is stored or transmitted beyond your current browser session. Built by Astrid Bernaga, MD · MSc Applied AI.
Try a sample:
Clinical note input 0 chars
Works with clinical notes in any language.
Output format:
Output language:
Analyzing clinical note...
AI-Generated Summary
claude-sonnet-4
How it works
01
Input
Paste any free-text clinical note the model handles unstructured, abbreviated, or specialty-specific language.
02
Extraction
Claude identifies key clinical entities: diagnoses, medications, vitals, assessment, and plan structured into defined output fields.
03
Summary
Output is formatted for clarity. Modifiable risk factors are highlighted. A plain-language patient summary is generated separately.
Why this matters

Physicians spend an estimated 4.5 hours per day on documentation more than half their working hours. Clinical NLP tools that extract, structure, and translate medical notes have the potential to return that time to what matters: the patient.

Reduces documentation burden
Structured summaries from free-text notes cut the time physicians spend reviewing charts before a visit or handoff from minutes to seconds.
Improves care transitions
Discharge summaries and consult notes are dense and time-consuming to parse. A structured extract reduces handoff errors and missed follow-ups.
Surfaces modifiable risk factors
Identifying actionable factors smoking, uncontrolled diabetes, medication non-adherence supports preventive care and chronic disease management at scale.
Patient-centered communication
A plain-language summary generated alongside the clinical one bridges the gap between what clinicians write and what patients can understand and act on.
EHR-agnostic by design
Because it works on raw text, it integrates with any EHR system Epic, Cerner, or plain text exports without custom connectors or vendor lock-in.
Foundation for clinical AI
Structured note data is the input layer for downstream applications: risk stratification, readmission prediction, population health analytics, and clinical trial matching.
Real-world applications

Every day, critical medical information fails to reach the right person at the right time. Brevai helps bridge that gap, wherever care happens.

01
Pre-visit chart review
Physicians arrive at each consultation already briefed past diagnoses, medications, and pending follow-ups surfaced in seconds instead of minutes of manual chart review.
Abridge · Suki · Nuance DAX
02
Nursing shift handoffs
One of the highest-risk moments in hospital care. A structured summary of the outgoing shift's notes reduces handoff errors a leading cause of adverse events in inpatient settings.
Hospital systems · ICU workflows
03
Inter-facility transfers
When a patient moves from a hospital to a clinic, rehab center, or specialist, the receiving team needs a concise, structured summary not 40 pages of raw notes.
Discharge workflows · Referral letters
04
Patient & family understanding
Medical notes are written at a postgraduate reading level. The plain-language summary bridges the health literacy gap so patients and families can make informed decisions about their care.
MyChart · Patient portals · FHIR apps
05
Cross-language care
When a patient receives care in a different language than the one they or their physician speaks, the summary can be generated in the language that works for them. Clinical information stays complete regardless of the language it was written in.
Telemedicine · Global health · LATAM
06
Clinical research data extraction
Extracting structured data from hundreds of free-text notes for a retrospective study a task that takes weeks manually becomes a scalable, automated pipeline.
EHR data mining · Trial screening
What's next

Brevai v1 focuses on single-note summarization. The roadmap expands toward a full clinical intelligence layer.

In development
Cross-note comparison
Track clinical changes between admission and discharge notes, or across visits over time.
Planned
Clinical alerts
Flag potential drug interactions, out-of-range lab values, and follow-ups documented but not scheduled.
Planned
Recipient-specific output
Tailored summaries for the receiving physician, nursing handoff, insurance authorization, or patient portal.