FireScriptTurn emergency calls and radio traffic into usable records
FireScript is an AI platform for EMS and emergency-response communications. It transcribes calls and radio traffic, summarizes events, extracts critical data, and proposes preliminary classifications so operators can review and act with less manual reconstruction.
Explore your use caseEmergency communications mix noise, interruptions, short radio exchanges, codes, abbreviations, locations, units, and organization-specific language. When that stays as audio or free text, it is hard to use for review, training, audit, statistics, and continuous improvement.
FireScript does not stop at transcription. It identifies incident type, location or district, priority, radio codes, units, and key facts, then produces summaries and preliminary classifications. The final decision stays with the operator while documentation and review effort drop.
Audio comes in. FireScript transcribes, summarizes, extracts, and classifies in parallel. The result is a structured record that operators can review and use.
Audio input
Transcript + Structured data
Category / Priority / Summary
The record is ready for summaries, analysis, training, and audit.
FireScript turns emergency communications into reviewable information step by step.
Emergency calls, radio traffic, or recordings enter the workflow.
Speech becomes readable text for fast confirmation and review.
Locations, districts, codes, units, priority, and key terms are identified.
FireScript proposes an incident category based on the communication.
Operators verify and correct the output where needed.
The record is ready for summaries, analysis, training, and audit.
Processes emergency calls, radio traffic, low-quality recordings, and short exchanges.
Treats radio codes, abbreviations, units, districts, and recurring terms as operational language.
Structures location, incident type, priority, involved units, risks, and key facts.
Suggests an incident category from the communication while leaving final judgment to the operator.
Generates summaries and operational records for review, handoff, training, and analysis.
Designed around access control, anonymization, and processing history for sensitive audio data.
Extract location, district, incident type, and priority from noisy calls so the operator can review faster.
Turn short radio exchanges into searchable records with unit names, codes, and action notes.
Arrange multiple communications into a readable timeline with the key decision points visible.
Generate summaries and extracted data for post-event review, training, audit, and statistics.
Evaluate FireScript with training audio or approved samples. Explore how transcription and structured information can support an operator's review.
CHOOSE YOUR SCENARIO
Use simulated calls to compare the transcript and extracted location or incident details with an operator's review. Identify unclear speech and information that needs confirmation.
Evaluate missing facts, recognition errors, unsupported extraction, and the effort required to correct the record.
AI supports review. Location confirmation, dispatch, resource assignment, and hospital acceptance remain subject to human confirmation and decisions.
Select simulated or explicitly approved audio and agree on the facts to verify and who will review them.
Compare transcription, extraction, and preliminary classification with the source audio; record errors and uncertainty.
Use the findings to define data handling, operator review procedures, and approved integration requirements before considering the next stage.
A practical starting point for your operations, technology, and data teams.
No. FireScript is advisory: it presents information and preliminary suggestions for review. Authorized people and organizations retain decisions on dispatch, resource allocation, destinations, and hospital acceptance.
Initial evaluation uses simulated calls, training scenarios, or approved samples. Operational adoption requires separate authorization, integration validation, and safety and data-handling review.
Feasibility depends on approved interfaces, provider participation, data freshness, and operational requirements. This page does not establish a live integration with an existing dispatch or hospital system.
Bring a training scenario and the facts that matter. Let's design an evaluation with the operator at its center.
