The Sentenai Sensor Data Cloud: How We’re Helping Businesses Unlock Actionable Intelligence with Machine Data

Today we’re excited to announce the launch of our flagship product, the Sentenai Sensor Data Cloud, which automates data engineering for data science and machine learning applications. By going beyond simply harnessing machine data and understanding the information that data provides, organizations can gain access to real-time, industrial intelligence that can improve service levels, reduce costs, mitigate security risks, maintain compliance and drive better business decisions.

With the growth of Industrial IoT, machine data is constantly being produced by nearly every application and device in an organization. This data contains definitive, time-stamped records of activities such as sensor readings, maintenance statuses, condition and state information, alarm flags and user activities, however the high variety and overwhelming volume of this data can be difficult to overcome. Designed for the realities of modern sensor data, the Sentenai Sensor Data Cloud is built for high variety time-series data, continuously optimizing sensor data, indexing and storage by predicting each data stream schema and learning over time as more data and streams are introduced. By ensuring data scientists have continuous, real-time access to holistic data intelligence, the cloud service frees data science teams from managing data infrastructure and enables organizations to gain new insights from their data that drive better business decisions.

Brendan and I met through a mutual friend while I was serving as director at Techstars Boston and Brendan was serving as partner at Hyperplane Venture Capital, a seed-stage machine intelligence fund he co-founded. We instantly found mutual interest in building infrastructure for sensor data based on our shared experiences in working with sensors: for me, my experience at the IoT startup Ember, and for Brendan, through his experiences as part of a Yale Industrial IoT spinout. Together we recognized that tomorrow’s challenges around sensors would be related to scaling the use and storage of data for data science applications and that a new company needed to make solving those challenges its mission.

After more than two years of research and development and working closely with incredible advisors like Julia Austin, Ellen Rubin, Yoav Shapira and Richard Tibbetts, and our great investors, we’re thrilled to share the Sentenai Sensor Data Cloud with any organization committed to understanding the value in their machine data. Here’s what makes the Sensor Data Cloud unique:

• Secure and scalable storage of sensor data. The cloud service provides a fast, flexible way to store a multitude of streams of sensor data for later data science and machine learning use, and its sensor-focused time series database preserves original data without sacrificing scalability, reliability or query performance.
• On-demand ETL pipeline for data science. By providing a powerful query engine that allows data scientists to perform ETL on-demand — without writing code or waiting hours for results — the Sensor Data Cloud simplifies the process of data preparation, automatically filtering noise from streams of sensor data, reshaping complex data to fit specific machine learning models, filling in missing data and normalizing data for sensor fusion.
• Seamless workflow integration. Designed specifically for data scientists, the Sentenai Sensor Data Cloud can be implemented within existing workflows, including sophisticated open source data science toolkits such as Pandas, Tensor Flow, pyTorch, and scikit-learn.

Whether you’re a large-scale manufacturer, an IoT solutions provider, or you’re developing data science applications with sensor data, we’d love to talk with you and learn more — contact me at rgupta@sentenai.com or sign up directly at sentenai.com.