911plus

Inspiration Emergency response times are critical, but the process of handling calls can sometimes delay the flow of crucial information. We wanted to streamline emergency call operations by developing an AI assistant that enhances efficiency, clarity, and safety for both call operators and callers. Our goal was to create a solution that reduces operator workload while maintaining human oversight and ensuring every call is handled with precision.

What it does 911plus is a call-taker AI assistant that enhances emergency call handling from start to finish. It begins by asking standardized questions before a live operator picks up, transcribing and summarizing caller information. During the call, the AI continuously monitors for potential life-threatening conditions and provides real-time transcription assistance to the operator. After the call, it can offer live updates to the caller, monitor the situation, and reconnect to the ops center if necessary.

How we built it We developed 911plus using a combination of natural language processing (NLP) for real-time transcription and machine learning models to detect life-threatening conditions. The platform integrates with existing emergency call systems, providing seamless interaction between the AI, the caller, and the operator. We leveraged cloud-based services for scalability and ensured low-latency responses through optimized real-time communication protocols.

Challenges we ran into One of the major challenges was ensuring that the AI could correctly identify life-threatening conditions in various ways callers might describe them. Another challenge was minimizing false positives, as the system needed to balance between caution and efficiency. Integrating the AI assistant into existing emergency call infrastructure while maintaining security and privacy also required significant effort.

Accomplishments that we're proud of We’re proud of how well the AI can transcribe and summarize emergency calls with high accuracy and its ability to flag potential threats in real time. Successfully integrating the assistant into an existing ops center, ensuring both speed and reliability, was another key accomplishment. Additionally, the post-call monitoring system enhances the overall safety of emergency responses, which we believe can significantly improve outcomes in critical situations.

What we learned We learned that designing AI for such high-stakes environments requires careful consideration of edge cases and the importance of operator control. Emergency situations vary widely, and while AI can greatly assist, maintaining human oversight is crucial. We also gained deeper insights into how to develop AI that both supports and augments human decision-making without replacing it.

What's next for 911plus Next, we plan to further optimize the AI’s ability to handle complex, multi-lingual calls and improve its integration with emergency services worldwide. We’re also exploring additional features such as predictive analytics to anticipate emergency outcomes based on incoming data and providing more tailored support for operators. Lastly, expanding post-call monitoring capabilities to offer longer-term support for critical cases is on our roadmap.

Built With

• cohere
• deepgram
• hume
• python
• vite