Sift, a hardware observability platform designed to unify complex sensor and telemetry data for physical systems, announced a $42 million Series B led by StepStone Group, with GV (Google Ventures) as the largest investor, bringing total funding to $67 million.
Hardware Observability for Complex Physical Data
Engineering teams working on rockets, satellites and autonomous systems rely on fragmented telemetry, scripts and manual analysis. Sift provides a unified data layer that ingests multi-modal sensor data, aligns timestamps, and enables real-time querying across test and operational environments. The platform supports high-frequency data, large-scale historical storage and structured schemas designed for both engineers and AI models.
Unified Data Infrastructure for AI-Driven Engineering
Sift aggregates sensor streams, audio, video and logs into a single structured system, enabling rapid investigations and long-term data accessibility. The architecture decouples compute and storage, allowing historical data to remain queryable for the life of a program while supporting AI-assisted anomaly detection and validation workflows.
Adoption Across Space and Hardware Programs
Organizations including Astranis, Impulse Space, K2 Space, CX2 and Parallel Systems use Sift to centralize data operations, automate alerting and accelerate testing cycles. The platform reduces analysis time, enables smaller operations teams and supports real-time monitoring across mission-critical systems.