Real-time crime intelligence platform combining cameras, sensors, and ML for public safety
Flock Safety operates a cloud-native platform for crime prevention across cities, law enforcement, and schools using cameras, sensors, and privacy-first machine learning. The tech stack spans embedded systems (ARM, STM32, FreeRTOS, Zephyr) through cloud infrastructure (AWS, Kubernetes, PostgreSQL, OpenSearch), revealing a hardware-to-cloud integration challenge — compounded by hiring velocity concentrated in engineering (29 roles) and active projects around device installation, retrieval scaling, and manufacturing expansion. Pain points around device performance, manufacturing scale, and field labor compliance signal growth friction as they move from software-first to hardware-inclusive operations.
Flock Safety builds public safety infrastructure that combines stationary and mobile cameras with sensors, real-time data processing, and machine learning to help law enforcement agencies and municipalities identify crime faster and with less investigative overhead. The platform is cloud-native and deployed across thousands of jurisdictions. Operations span manufacturing (camera and solar hardware), field installation, software development, and sales into public-sector buyers. The company hires across seven countries and is actively scaling engineering, sales, and operations teams.
Embedded systems (ARM Cortex, STM32, FreeRTOS, Zephyr, CAN, I2C, UART), cloud infrastructure (AWS, Kubernetes, Lambda), backend (Go, TypeScript, PostgreSQL, OpenSearch, Redis), data processing (Apache Airflow, Prefect, Python), and DevOps (Git, Gerrit, Docker). Adopting Rust and VWO.
Hardware expansion (camera and solar infrastructure installation), a unified investigator dashboard ('single pane of glass'), scaling retrieval systems for real-time queries, public-sector sales acceleration, community partnerships, and drone-based first responder programs.
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