Case Study: RapidSOS achieves real-time emergency data insights with Muttdata

RapidSOS cuts data lag 80% with Muttdata

RapidSOS, a safety platform that connects data from over 540 million devices to emergency services, faced a critical challenge with its outdated data backbone. Their system relied on over 20 fragmented pipelines, which caused data to be delayed by 24 to 72 hours and created operational risks. To modernize their emergency response capabilities, RapidSOS partnered with Muttdata to build a single, governed ingestion layer for low-latency processing.

Muttdata rebuilt the data backbone using Databricks Workflows, Auto Loader, and Delta Lake to consolidate pipelines and ensure data consistency. This solution cut data lag by 80%, reducing calls table update time from one day to under four hours. The improvements also enhanced orchestration resilience, improved data governance, and reduced processing costs by 5-15%. Muttdata provided RapidSOS with a reliable, real-time data foundation that is now positioned to support future AI initiatives.

RapidSOS