Working with sensor data is hard. Sentenai makes it simple.
Sentenai is a Boston startup providing sensor data infrastructure for machine learning and predictive applications. Sentenai automates the process of ingesting and organizing sensor data so that data science teams and automation engineers can search for historical patterns and behaviors without the need for manual preparation or integration projects. We enable data scientists to explore and operationalize their data in real-time applications in the languages and toolkits they already use. Our customers are solving bleeding edge industrial IoT problems in complex and large-scale environments.
Traditional approaches to storing structured and unstructured time series treat data organization as a problem best
solved by teams of data engineering experts. This approach succeeds when data exhibits “low variety” in kinds of
variables, collection rate and labels, but in sensor-driven environments, the inherent “high variety” of data requires a new approach.
Sentenai’s sensor data cloud automatically organizes sensor data (structured and unstructured) to unlock
its usefulness in machine learning applications. Sentenai provides ingestion, storage and data querying capabilities in a single, automated platform.