Real-Time Clinical Decision Support System

AI-powered analytics and documentation
for Code Blue events

AIIMMS utilizes computer vision and natural language processing to streamline the code blue workflow and provides digital tools that improve consistency, reduce cognitive load, and drive better patient outcomes.

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How it works

From Chaos to Clarity
in Real-Time

Five integrated steps that transform raw data and live emergency readings into structured clinical intelligence.

Step 01

Multi-source data ingestion

AIIMMS simultaneously captures video, audio, pulls live EHR data, and streams real-time biometric data — all synchronized from the moment a code blue is called.

Video · Audio · EHR · Biometrics
Step 02

Computer vision and NLP

Proprietary CV models analyze camera footage to detect clinical actions and recognize medical equipment in use — all timestamped automatically. NLP models extract relevant clinical terms from audio to corroborate the action.

CV · NLP · Pose Estimation
Step 03

Temporal alignment

Features extracted from all data sources are precisely time-aligned and fused into a single unified transcription of the event — eliminating the gaps and errors of manual documentation.

Time-sync · Data fusion
Step 04

ML-powered clinical analytics

A trained machine learning model processes the unified transcription to generate structured event logs, flag deviations from protocol, and surface real-time diagnostic suggestions for the clinical team.

ML Model · Structured logs
Step 05

Clinician-facing display & decision support

Analytics are delivered to a bedside display in real time — giving the team a live event timeline, alert flags, and diagnostic prompts that reduce cognitive load precisely when it matters most. Post-event reports are generated automatically for QA and compliance.

Live dashboard · Post-event report · QA ready
FAQ

Common questions

Everything your IT and procurement teams need to know before getting started.

How does AIIMMS integrate with our existing EHR system?
AIIMMS supports HL7 FHIR and standard EHR APIs, allowing integration with major platforms including Epic, Cerner, and Meditech. Our implementation team works directly with your IT department to configure secure, bidirectional data flows with minimal disruption to existing workflows.
What camera or hardware infrastructure is required?
AIIMMS is designed to work with industry-standard IP cameras already present in most modern resuscitation bays and ICUs. Our team assesses your existing infrastructure during onboarding and provides guidance on any additional hardware required. No proprietary cameras are needed.
Is patient data handled in compliance with HIPAA and local regulations?
Yes. AIIMMS is built with privacy-by-design principles. All data is encrypted in transit and at rest, processed within compliant cloud environments, and subject to configurable data retention policies. We provide a Business Associate Agreement (BAA) and support your compliance and legal review process.
How long does deployment and staff training take?
Typical deployment timelines range from 4 to 8 weeks depending on the size of your institution and existing IT infrastructure. Clinical staff training is streamlined — most teams are operational within one to two sessions, as the system is designed to be intuitive during high-pressure events.
Can we pilot AIIMMS in a single department before a full rollout?
Absolutely. We encourage a phased approach starting with a single resuscitation bay or ICU unit. Our team supports the pilot with dedicated implementation support, outcome tracking, and reporting to build an internal business case for broader adoption.