Maestro, through smart decisions based on input (rule-based engine, AI-driven image analysis), automatically prioritize and assigns studies reducing operational turnaround time.
Why teams choose maestro
Subspecialty aware routing
Worklists are dynamically organized based on subspecialty, urgency, and radiologist availability, ensuring each case reaches the appropriate reader.
Smart decision-making
Route via a configurable rule engine when metadata is available and switches to AI image analysis, ensuring accurate assignment regardless of data quality.
Zero disruption deployment
Maestro embeds directly into evoRIS and overlays on existing PACS environments. Enabling orchestration, without requiring changes or disruption.
Proven classification precision
Validated across 34,000+ images, using evoTag engine, 89% precision is achieved on CT and MRI study classification, giving department leaders confidence that every case reaches the right hands.
Infrastructure Integration
Unlike traditional PACS worklist tools, maestro operates as a vendor-neutral orchestration layer across mixed environments, routing cases from any modality or system without requiring a platform change.
How It Works
Maestro connects to your evoRIS, and modalities, automatically routing every incoming study to the right radiologist — in real time, without changing how your teams work.
It evaluates both rules-based logic and AI image analysis to assign cases by urgency, subspecialty, and reader availability, ensuring accurate routing regardless of metadata quality or system complexity.
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Modalities(CT, MR, XR, US, MG)
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maestroRules + AI routing engine
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Radiology worklist
Subspeciality-aware priority -
evoViewer
Study delivered, priors loaded
Combine with
01
evoRIS
Live scheduling and study state data from evoRIS makes every routing decision smarter and more precise.
02
evoTag
Clean metadata means smarter routing. Normalize study labels at entry, giving maestro the accurate data it needs to assign every case correctly.
