PingThings
PingThings provides PredictiveGrid, an enterprise time-series data management platform that ingests, preserves, and analyzes high-frequency sensor data for North American utilities, grid operators (ISOs/RTOs), national laboratories, and adjacent physical-system sectors including data centers, renewables, transportation, and aerospace.
- Company typePrivate
- Founded2017
- HeadquartersAnaheim, United States
- Headcount1–10
- GTM typeB2B
- OfferingSoftware
What PingThings does
PingThings is a Delaware C-Corp founded in 2017 that commercializes PredictiveGrid, an end-to-end time-series data management platform for physical-system observability originally developed at UC Berkeley under a 2012 ARPA-E Open Innovation project. The platform comprises three core technologies: the BTrDB storage engine (peer-reviewed at USENIX FAST '16) for lossless high-frequency sensor data storage, the DISTIL analytics framework (peer-reviewed at SIGMOD '18) for distributed real-time processing, and a High-Performance Query API with REST/gRPC interfaces for enterprise integration. PredictiveGrid ingests, preserves, queries, contextualizes, visualizes, and analyzes sensor data across six orders of magnitude in sample rate (0.001 Hz to 1 MHz+) from any sensor, vendor, or protocol (40+ supported natively), preserving raw waveforms without downsampling.
The company's primary customers are major North American transmission, distribution, and generation utilities, Independent System Operators (ISOs) and Regional Transmission Organizations (RTOs), U.S. national laboratories, and university research consortia in power systems and grid AI. PingThings operates as a fully managed, turnkey platform-as-a-service delivered via direct enterprise field sales, with single-tenant cluster isolation designed to operate inside customer NERC-CIP compliance perimeters and deployments available on AWS, AWS GovCloud, Microsoft Azure, or on-premises configurations. The platform is SOC 2 Type 2 certified and runs multi-million-channel deployments with multi-year analytics horizons; one disclosed customer has operated the platform continuously at more than 2 million measurements per second for over five years.
PingThings has received more than $8M in research and development grants from the U.S. Department of Energy, ARPA-E, EPRI, and the National Science Foundation, and was profitable prior to its 2020 Series A. Its board includes representatives from Denham Capital (via Three Curve Capital LP, the family office of the $9.5B+ energy and resources investment advisor) and Micron's AI Fund / Comet Labs. The company operates with approximately two dozen engineers, data scientists, and domain experts under a fully remote model, with its registered mailing address in Anaheim, California.
PingThings firmographics
Firmographics- Name
- PingThings
- Legal name
- PingThings, Inc.
- Website
- https://pingthings.io
- Company type
- Private
- Founded year
- 2017
- Operating status
- Operating
- Headcount range
- 1–10 employees
- Short description
- PingThings provides PredictiveGrid, an enterprise time-series data management platform that ingests, preserves, and analyzes high-frequency sensor data for North American utilities, grid operators (ISOs/RTOs), national laboratories, and adjacent physical-system sectors including data centers, renewables, transportation, and aerospace.
- Ownership category
- akta.pro rank
PingThings industry classification
Industry- Product category
- Time-Series Data Management Platform for Physical System Observability
- NAICS
- Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821), Computer Systems Design and Related Services (54151), Electric Power Generation, Transmission and Distribution (2211)
- SIC
- Services-Computer Integrated Systems Design (7373), Services-Prepackaged Software (7372), Services-Computer Processing & Data Preparation (7374)
- akta.pro primary industry
- Grid Data & Analytics Enablement (MDM, Data Integration, Hosting) (EUAEANAI)
- akta.pro secondary industries
- Grid Analytics, Forecasting & Decision Support (Load/DER/Outage) (EUADAEAI), Data Lake Platforms (HDAEABAC)
Keywords
Where PingThings is headquartered
LocationHeadquarters
- HQ city
- Anaheim
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
PingThings business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Infrastructure, Operations, Marketing or Sales
Revenue model
- PredictiveGrid Platform Subscription: Fully managed, turnkey platform-as-a-service with concierge-level support, embedded analytics, and lifecycle stewardship. Deployment model is collaborative rather than transactional, designed for long-term alignment with operational objectives. Per-deployment tailoring based on signal volume, data types, ingest patterns, retention policy, security requirements, user authentication model, and compliance constraints.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Subscription | Multi-year contract | Enterprise platform-as-a-service with fully managed deployment |
Go-to-market motion2 records
Distribution channels2 records
Marketing channels4 records
PingThings product offering
Product offeringCore offering
PingThings builds and operates PredictiveGrid, an end-to-end time-series data management platform purpose-built for physical-system observability. The platform ingests, preserves, contextualizes, queries, visualizes, analyzes, and exposes high-fidelity sensor data spanning six orders of magnitude in sample rate (0.001 Hz to 1 MHz+) from any sensor, any vendor, any frequency in a single unified substrate. Delivered as a fully managed, turnkey platform-as-a-service with concierge-level support, embedded analytics, and lifecycle stewardship for utilities, grid operators, data centers, and industrial teams managing real-world infrastructure.
Product overview
PingThings offers PredictiveGrid as its flagship platform—a unified time-series data management system for physical infrastructure observability. The platform consists of three core components: the BTrDB storage engine (UC Berkeley, FAST '16) for lossless high-frequency data storage, the DISTIL analytics framework (SIGMOD '18) for distributed real-time processing, and a High-Performance Query API for application integration. PredictiveGrid is deployed as a fully managed, turnkey platform-as-a-service with concierge-level support, embedded analytics, and lifecycle stewardship. The platform is engineered for physical systems in the energy sector (utilities, ISOs, grid operators) and adjacent markets (data centers, renewables, transportation, aerospace), handling multi-million-channel deployments with multi-year analytics horizons.
Differentiator
Problem solved
Functional benefit
Brands
- PredictiveGrid: End-to-end time-series data management platform for physical-system observability. Ingests both low- and high-frequency physical-system data, preserves it without downsampling, adds operational context, and exposes it to analytics, applications, and AI.
- BTrDB
- DISTIL
Products and services
- PredictiveGrid Platform End-to-end time-series data management platform purpose-built for physical-system observability. Ingests, preserves, queries, contextualizes, visualizes, analyzes, and learns from high-fidelity sensor data across sample rates spanning six orders of magnitude, supporting any sensor, any vendor, any frequency, real-time or historical, continuous or discrete data in one unified substrate. Targeted at utilities, grid operators, data centers, and industrial teams managing real-world infrastructure.
- BTrDB Storage Engine General-purpose time-series storage engine developed at UC Berkeley with ARPA-E funding, designed for high-frequency sensor data with lossless compression across six orders of magnitude in sample rate (0.001 Hz to 1 MHz+) without segmenting workloads. Powers the storage layer of PredictiveGrid.
- DISTIL Analytics Framework Distributed analytics framework published at SIGMOD '18 providing time-series operators that run at native sample rate across petabytes of data in real time, enabling distributed query without data movement. Powers the analytics layer of PredictiveGrid.
- High-Performance Query API REST and gRPC-based application programming interfaces exposing high-performance query capabilities for integrating PredictiveGrid data with enterprise applications, dashboards, Jupyter/Python/R notebooks, and custom analytics workflows. Supports Apache Arrow on the wire, Parquet for bulk export, and webhooks for pushing data to external systems.
Quantifiable outcome
- One customer running >2M measurements/second, 24/7/365 for 5+ years
- +4 more outcomes
Companies that use PingThings
Customer profileNamed customers5 records
Segments7 records
Ideal customer profiles4 records
PingThings technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration9 records
AI capability6 records
Feature6 records
PingThings partnerships and signals
Strategic signalPartnerships
One partnership is on record.
- UC BerkeleyfoundationalPredictiveGrid's core technologies originated from research at UC Berkeley under the 2012 ARPA-E Open Innovation project that produced the microPMU. BTrDB storage engine and DISTIL analytics framework were developed as academic research artifacts, then commercialized by PingThings in 2017. PingThings operates an enterprise-grade implementation of BTrDB that has been tuned, hardened, and extended through years of production deployment.
Scale indicators8 records
Recent moves6 records
Expansion highlights6 records
PingThings competitors and assessment
Company assessmentBroad incumbents
- OSIsoft (AVEVA PI): OSIsoft's PI System is the dominant operational historian across global utilities, oil & gas, and manufacturing. It is the closest direct functional competitor to PredictiveGrid, with deep incumbency in PingThings' target accounts and explicit coexistence integrations.
- GE Digital (GridOS / Predix): GE Digital offers industrial data and analytics platforms serving utilities and grid operators. It competes for the same enterprise utility data infrastructure budgets as PingThings, though with a broader software portfolio rather than a focused time-series platform.
- Aspen Technology: AspenTech provides industrial AI and asset performance software to utilities, chemicals, and energy customers. It competes for utility analytics and asset health budgets where PingThings targets predictive maintenance and grid analytics use cases.
- Hitachi Lumada: Hitachi's Lumada platform combines OT/IT data management, analytics, and AI for industrial and energy customers. It targets similar physical-system observability use cases as PingThings at large utility and industrial accounts.
- AWS IoT SiteWise / Timestream: AWS IoT SiteWise and Timestream provide managed cloud time-series services for industrial data. As managed alternatives to custom platforms, they compete for utility and data center customers evaluating cloud-native time-series infrastructure.
- Schneider Electric (EcoStruxure): Schneider Electric's EcoStruxure platform combines grid and energy management software with industrial IoT data infrastructure. It competes for utility operational technology and data platform budgets at major North American utilities.
Emerging players
- Databricks: Databricks is increasingly used by utilities for data lakehouse and ML workloads, including time-series analytics. PingThings explicitly positions as 'the missing historian for Databricks,' indicating both partnership and competitive overlap for high-frequency sensor data workloads.
- InfluxData (InfluxDB): InfluxData provides a general-purpose time-series database platform used across industrial IoT and operational monitoring. It competes for time-series storage and analytics workloads in utilities and adjacent physical-system markets.
- GridPoint: GridPoint provides energy data management and analytics for utilities and commercial customers. It is a more focused competitor in distributed energy and substation analytics use cases where PingThings also targets distribution utilities.
- Uplight: Uplight provides energy data analytics and customer engagement platforms for utilities, including AMI data management. It competes in adjacent data infrastructure layers serving North American investor-owned utilities.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights7 records
Customer concentration
PingThings social profiles
Digital presencePingThings compliance and trust
Trust signalCompliance1 record
PingThings financial estimates
Financial estimateRevenue estimate
Valuation estimate
PingThings leadership team
Management profileNumber of profiles
Profiles4 records
PingThings funding detail
Funding detailFunding overview
Funding rounds6 records
Investors4 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
PingThings M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about PingThings
What does PingThings do?
PingThings builds and operates PredictiveGrid, an end-to-end time-series data management platform purpose-built for physical-system observability. The platform ingests, preserves, contextualizes, queries, visualizes, analyzes, and exposes high-fidelity sensor data spanning six orders of magnitude in sample rate (0.001 Hz to 1 MHz+) from any sensor, any vendor, any frequency in a single unified substrate. Delivered as a fully managed, turnkey platform-as-a-service with concierge-level support, embedded analytics, and lifecycle stewardship for utilities, grid operators, data centers, and industrial teams managing real-world infrastructure.
Is PingThings a public or private company?
PingThings is a private company. It is classified as venture growth investor backed and is currently operating.
When was PingThings founded?
PingThings was founded in 2017. It employs 1 to 10 people.
Where is PingThings based?
PingThings is headquartered in Anaheim, United States, in the North America region.
How does PingThings make money?
One revenue line is on record: predictiveGrid Platform Subscription.
Who are PingThings's main competitors?
Broad incumbents on record are OSIsoft (AVEVA PI), GE Digital (GridOS / Predix), Aspen Technology, Hitachi Lumada, AWS IoT SiteWise / Timestream and Schneider Electric (EcoStruxure). Emerging players are Databricks, InfluxData (InfluxDB), GridPoint and Uplight.
Does PingThings have an API?
Yes. PredictiveGrid provides a High-Performance Query API alongside REST and gRPC interfaces for integration with enterprise systems and applications. The platform exposes query, analysis, and application layers that enable engineers to build custom applications, dashboards, and integrations. Native notebook integration with Jupyter, Python, and R is supported for distributed querying through DISTIL. Developer documentation is at pingthings.io/platform.
What industry is PingThings in?
PingThings's product category is Time-Series Data Management Platform for Physical System Observability. Its primary akta.pro industry code is EUAEANAI, Grid Data & Analytics Enablement (MDM, Data Integration, Hosting), with a secondary code of EUADAEAI, Grid Analytics, Forecasting & Decision Support (Load/DER/Outage). Its NAICS code is 51821 and its SIC code is 7373.