Company's Platform Addresses Emerging Industrial IoT Market, Enabling Businesses to Scalably Leverage Machine-Based Data and Unlock Actionable Insights
CAMBRIDGE, MA–(Marketwired – November 16, 2017) – Sentenai, an emerging sensor data technology company, today announced the availability of its flagship product, the Sentenai Sensor Data Cloud. By going beyond the initial harnessing of machine-based data and understanding the information that data provides, organizations can streamline their operational processes and develop predictive maintenance solutions that decrease unplanned downtime. With its Sensor Data Cloud, Sentenai is empowering businesses and their data scientists to build on sensor-based applications by allowing them to access historical data in the tools they already use, without requiring any data engineering work.
Enterprise IoT devices, or the Industrial Internet of Things (IIoT), is gaining momentum at an exponential rate. Industrial sensor devices are fundamentally transforming the way organizations do business with other companies, with recent data indicating enterprise IoT spending could hit $1.477 trillion by 2020 with more than 7 billion enterprise IoT devices in use.
“The term IoT has become a part of the general vernacular, but the IIoT is the new frontier, and the foundation of modern industrial growth,” said Rohit Gupta, co-founder and CEO at Sentenai. “Industrial machine data is being produced by nearly every application and device in an organization, and it contains definitive, time-stamped records of activities such as sensor readings, maintenance statuses, condition and state information, alarm flags and user activities. Sentenai was created to help organizations capitalize on the power of their machine data, gaining access to real-time, industrial intelligence that can improve service levels, reduce costs, mitigate security risks, maintain compliance and drive better business decisions.”
The Sentenai Sensor Data Cloud provides the following key capabilities:
- 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.
At the core of Sentenai technology is revolutionary data engineering AI designed to continuously optimize database storage and indexing, thereby enabling users to rapidly mine historical data for complex patterns like operational anomalies and failure modes.
The Sentenai Sensor Data Cloud is available now to any organization committed to understanding the value within their machine data. For more information or to initiate the onboarding process, please visit www.sentenai.com.
Sentenai provides sensor data cloud infrastructure that automates data engineering for data science and machine learning applications. Designed for the realities of modern sensor data, the company's 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, Sentenai frees data science teams from managing data infrastructure and enables organizations to gain new insights from their data that drive better business decisions.
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