◎ CASE / 006◎ AI AGENT◎ KR◎ 2025◎ SHIPPED
Clinic NetworkPOWERED BY CREWLESS
Medical Records Summarizer
Medical Records Summarizer
ROLE
AI Agent Design & Build
PERIOD
2025
MARKET
KR
HEADLINE
-75% · Summary time
(01) Challenge · The problem
“Starting point”
Beyond seeing patients, clinic physicians spend considerable time reading and organizing medical records. Records are long and inconsistently formatted, and the sensitivity of patient data made off-the-shelf AI tools unsuitable.
(02) Solution · How we solved it
“Approach”
A Python pipeline de-identifies records before Claude condenses the clinical history into a structured summary, following a HIPAA-safe design. Physicians grasp a patient's history from the summary and consult the source record only where needed.
(03) System · How it runs
Running on the engine.
INTAKE
EMR · DOC
CREW
LESS
LESS
ORCHESTRATOR
DEIDENTIFY AGENT
PII MASKING
SUMMARY AGENT
CHART DIGEST
>pipeline · medical-records-summary · production▌● IN PRODUCTION
Runtime log · Sample run
▌
(04) Outcomes · Results
Proven by numbers.
-63%
Summary time
Structured summaries sharply reduced the time spent reading and organizing records.
0
Raw data exposure
Only de-identified data reaches the model, by HIPAA-safe design.
Auto
Structured summaries
Inconsistent record formats are normalized into a consistent summary layout automatically.
(05) Stack · Tools used
Trusted tools only.
01 · AI
- ▸Claude API
02 · Backend & Security
- ▸Python
- ▸HIPAA-safe
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START / FREE CONSULT · NDA OK