Case Study: Numenta achieves faster, more accurate anomaly detection with Domino Data Lab

Delivering Better, Faster Anomaly Detection

Numenta is a research-driven company that applies neuroscience-inspired machine learning to streaming anomaly detection for use cases like data center monitoring, traffic analysis, social media, and predictive maintenance. The team struggled with fragmented workflows—researchers ran work locally or in ad-hoc AWS environments, lacked standardized experiment documentation and reproducibility, and spent undue time managing infrastructure instead of modeling.

To solve this, Numenta adopted the Domino Data Lab platform (integrated with Jupyter and AWS) to standardize environments, automate experiment tracking, and scale cloud compute with minimal overhead. The platform enabled parallel, reproducible experimentation (pay-by-the-minute execution), accelerated development from weeks to hours, allowed testing of more than twice as many algorithms, helped produce the NAB anomaly-detection benchmark, and positioned Numenta to run much larger, thousands-of-experiments studies.

Numenta

Subutai Ahmad

VP of Research