Ingest, Store, Visualize, Analyze, and Learn From all of your sensor data at any resolution.

All of your sensor data, at your fingertips, instantaneously. No more getting coffee or lunch while your historian labors to complete a simple data query.

The unaltered video above shows a 120Hz signal with 1 billion measurements covering more than 3 months as a user zooms in and locates a voltage sag comprised of 7 measurements (50 milliseconds) in real time.

State of the Art

Platform Features

The best and only scalable analytics platform for high resolution utility sensor data.

Any Sensor

Supports PMU, DFR, PQ, and more with nanosecond time resolution.

Real time or Historical

Ingests both real-time, streaming data and massive historical archives, fast.


Scales easily to support millions of sensors with petabyte or larger data sets.

Instantaneous Visualization

Interactive visualization with <250ms queries at any scale.

Data Versioning!

Your code is versioned, why not your sensor data and analytic results? Ours are.


Never lose data again; automatic data replication and self-healing for system resiliency.


Native Appication Programming Interfaces (APIs) for most languages.

Real-Time Analytics

Purpose built for both ad-hoc and real-time analytics.

Artificial Intelligence

Uses best-of-breed machine learning and deep learning to enable AI out of the box.

Platform Deployment Options

Deploy the PredictiveGrid™ in the way that best suits your organization's needs.


Deploy on site in your own data center on a custom built, highly-optimized appliance or on your own hardware.


Deploy in any major cloud provider including AWS GovCloud.

"Utilities today are increasingly seeking ways to manage, process, and act on the massive influx of data streaming in from meters, sensors, voltage monitors, and other devices deployed across the network. The need to manage and make optimal use of this data—to filter out the noise, analyze the value, and translate insight into automated decision-making and real-time problem solving—makes the integration of analytics into utility operations an almost foregone conclusion."

-From Smart Grid to Neural Grid, Navigant 2018

About PingThings

PingThings partners with forward thinking utilities to take advantage of a structural shift to artificial intelligence in the energy industry driven by the grid's growing complexity.

DOE and McKinsey estimates show predictive analytics can save utilities ~17-31% annually on maintenance costs. Further, unplanned outages are growing 10% every year, costing $189B annually. Big data is key, but utilities use only 2% of their massive datasets. Existing software is designed for archiving, not analysis and is even worse for high data rate sensors.

PingThings solves these issues with the PredictiveGrid™, a purpose built platform for ingesting, storing, accessing, visualizing, analyzing, and training machine- and deep-learning models with data from large numbers of sensors. The platform is offered as an on-premise appliance, and in either a public or private cloud. Benchmarks indicate that we are at least two orders of magnitude faster than competitors.

For businesses, PredictiveGrid™ is designed to be easy to adopt and deploy. For end users, we integrate with industry standard open source tools for data science and machine learning. PredictiveGrid™ solves problems at every step of the data analysis pipeline to make employees more productive, reduce the cost of analysis, and expand what's possible with your data.