- Revenue
- $174.3M
- Customers
- 300
- Year founded
- 2007
- Funding
- $54.4M
- Team size
- 361
- Growth
- -15.6%
Top 467 IoT Analytics Platforms SaaS Companies in May 2026
As of May 2026, there are 467 SaaS companies in IoT Analytics Platforms. They have combined revenues of $3.3B and employ 19.7K people. They have raised $3.5B and serve 536.1M customers combined.
IoT Analytics Platforms facilitate the collection, processing, and analysis of data generated by Internet of Things (IoT) devices. They enable organizations to turn vast amounts of sensor and device data into actionable insights, supporting decision-making processes across various industries. Common use cases include predictive maintenance, operational efficiency optimization, and enhanced customer experiences through personalized services. These platforms typically feature capabilities such as data integration, real-time analytics, advanced visualization tools, and machine learning algorithms. Buyers of IoT analytics solutions often come from IT departments, data analytics teams, and operational roles that seek to derive value from IoT data to improve processes, enhance product offerings, and drive strategic initiatives.
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Sorting: Highest -> Lowest
Top IoT Analytics Platforms Companies
Showing 10 of 7 companies ranked by annual revenue.
- Revenue
- $155.8M
- Customers
- 4K
- Year founded
- 2011
- Funding
- $38M
- Team size
- 156
- Growth
- 39.18%
3
Augury
New York, New York, United States
Augury provides insights into the health of machines and processes, helping manufacturers increase production, improve quality and reduce costs and waste. It specializes in AI-driven solutions for monitoring machine health and process efficiency in industrial operations.
- Revenue
- $155M
- Customers
- -
- Year founded
- 2011
- Funding
- $155M
- Team size
- 357
- Growth
- 106.67%
4
G7 Networks
Beijing, China
G7 Networks is a fleet management service provider in China that offers IoT/AI services to over 800,000 vehicles, serving sectors within the logistics and transportation industry.
- Revenue
- $150M
- Customers
- -
- Year founded
- 2016
- Funding
- $710M
- Team size
- 1K
- Growth
- -
5
Cognite
Tempe, Arizona, United States
Cognite is a Norwegian software company that provides an industrial data operations platform designed to help industrial companies transform their operations with data. The platform provides a range of tools and services for collecting, integrating, and managing large-scale industrial data, as well as advanced analytics, artificial intelligence, and machine learning capabilities for optimizing industrial processes and reducing operational costs. The company was founded in 2017 and is headquartered in Oslo, Norway, with additional offices in the United States and Europe. Cognite has received significant funding from investors, including Accel, Battery Ventures, and Point72 Ventures, and has established partnerships with major industrial companies, including Aker BP, Siemens, and Equinor.
- Revenue
- $117M
- Customers
- -
- Year founded
- 2016
- Funding
- $225.2M
- Team size
- 795
- Growth
- -
6
Infinite Uptime
Alpharetta, Georgia, United States
Infinite Uptime is an Industrial AI pioneer delivering Production Outcomes to manufacturers globally. By helping them drive Prescriptive Maintenance and offering predictive maintenance platforms, the company assists in managing operational risks and minimizing downtime.
- Revenue
- $113.1M
- Customers
- -
- Year founded
- 2015
- Funding
- -
- Team size
- 314
- Growth
- -
7
WakeData
China
Provider of one stop smart store management and big data services for offline companies. The company collect data through WiFi probes, camera face recognition, user online behavior and combines it with the store member system enabling offline companies to improve operational efficiency and achieve data-driven solutions.
- Revenue
- $101M
- Customers
- -
- Year founded
- 2018
- Funding
- $39.7M
- Team size
- 13
- Growth
- -
Inclusion Criteria
- The platform must support data collection from a variety of IoT devices and sensors. - It should offer real-time data processing and analytics functionalities. - Advanced analytics capabilities, like machine learning or predictive modeling, are necessary. - The solution must include visualization tools for presenting data insights effectively. - Must provide integration with existing business systems and data lakes. - Not just focused on data storage; must also facilitate actionable insights generation.