Vectis Copilot — Clinical LLM Insights, Grounded in Your Data

Session · Investigator · project: Transplant-Associated CLABSI cohort: 506 patients · 14,208 encounters

Did time to first antibiotic differ by payer for PICU sepsis admissions in 2024?

CLABSI risk factors (NHSN) Why was P-04417 reintubated? CLABSI reduction QI plan Run orchestrate()

model · claude-opus-4-8 effort · very-high dbpath · picu_cohort.duckdb output · reports/

The Promise — Minutes, Not Weeks

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Ask in Plain Language

No SQL, no ticket queue, no waiting on an analyst. Ask the question the way you would ask a colleague — scoped to a cohort you define.

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A Team Assembles

The orchestrator classifies the question and routes it to the right specialist agents — research, causal, equity, safety — working in concert.

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A Cited Report

Out comes a structured, reproducible report with every finding traced to a table, column, and record ID in your source system.

The Agent Team — agent=None lets the classifier decide

16

Sixteen Specialists. One Orchestrator.

Leave routing to orchestrate() and the classifier picks the team, or name the agents yourself. Each specialist owns one job and does it well — from leak-audited ML to independent paper reproduction.

Auto

orchestrate() — the classifier picks the team

Research

cohort analysis, dataset assembly

Safety

root cause with five EMR checks

Equity

stratified disparity analysis

Causal

estimand, DAG, DoWhy identification

ML

leak-audited predictive modeling

QI

IHI aim, driver diagram, PDSA

Metric

deployable measure specification

Informatics

Epic build proposals

EBOC

protocol PDF to evidence standards

Vis

Altair figures, SVG and PNG

Paper

independent reproduction of findings

Data

row-level parquet extracts

Curators

primary source vs abstraction

Compare

two extracts against the EMR

File

render report to PDF or DOCX

Telemetry, REDCap, and Eval take inputs the classifier cannot inspect — call those teams directly, never through the orchestrator.

Why You Can Trust It — Every Claim, Traced

Not a Chatbot.
A Cited Investigation.

General-purpose LLMs hallucinate confidently and cite nothing. Vectis Copilot does the opposite: every finding points back to a specific table, column, and record in your source data — a CSN, an order number, a result timestamp.

A clinician can verify any claim, a safety officer can reconstruct any timeline, and a reviewer can reproduce any number. The output is an audit trail, not an opinion.

EMR-GroundedRecord-Level CitationsReproducibleLeak-Audited

Findings — Five EMR Checks (example)

01

Extubation logged 07:40 on D3 — flowsheets.MeasureNM = 'Airway Event', CSN 8841-2207

02

Dexmedetomidine stopped 09:15, last rate 0.4 mcg/kg/hr — meds_admin

03

Capillary gas pH 7.28 / pCO₂ 58 resulted 22:51 — labs.ResultDTS, order 55-118402

04

Deterioration BPA fired 19:05, no acknowledgement — bpa_events

05

Reintubation 02:44 on D4, 7.0 cuffed ETT — procedures

What It Produces — Artifact Library

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Cohort Analyses

Risk-factor studies grounded in NHSN definitions, stratified disparities, and reproducible datasets ready for review.

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Event Reconstructions

Timeline chronologies and contributing-factor reviews with five EMR checks per event — feeding straight into Vectis Safety.

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Improvement Plans

SMART aim statements, families of measures, and driver diagrams with change ideas — ready to launch in Vectis Ops.

Put an Analyst Team on Every Question.

Vectis Copilot is available now for clinical research and quality teams. Get in touch to scope a deployment against your data environment.

Request Access Explore the Suite

Clinical Questions In,Grounded Answers Out.