As of May 2026, there are 130 SaaS companies in Time Series Intelligence Software. They have combined revenues of $945M and employ 5.5K people. They have raised $1B and serve 47.4K customers combined.
Time Series Intelligence Software facilitates the analysis and interpretation of time-ordered data points, enabling businesses to discern patterns, trends, and anomalies over specific periods. This category of software is integral in various applications, including financial forecasting, stock market analysis, and monitoring sensor data from IoT devices. By processing sequential data, these tools empower users to make informed decisions based on historical trends and predictive insights. Key features of time series intelligence software often include advanced analytics capabilities, visualization tools, anomaly detection, and forecasting models. These functionalities streamline workflows for domains like finance, operations, and IT, where professionals require a reliable understanding of trends over time. Typical users of these tools include data analysts, financial officers, and business intelligence professionals who need to convert complex datasets into actionable insights. Ultimately, time series intelligence software serves as a critical resource for organizations looking to leverage historical data for strategic planning and operational improvements, enabling them to stay ahead in a competitive environment.
Sorting: Highest -> Lowest
Showing 10 of 17 companies ranked by annual revenue.
Utrecht, Netherlands
Withthegrid is a Dutch company that connects and empowers infrastructure assets, grid operators, energy producers and users through monitoring and flexibility solutions.
Warwick, England, United Kingdom
Eatron is a fast-growing technology company dedicated to unlocking the full potential of batteries with intelligent software for all vehicle and battery manufacturers worldwide. We develop AI-powered edge-to-cloud connected software platform for better, safer, durable and greener batteries in automotive, mobility and beyond. Each Eatron software function at the edge (i.e. in the BMS), such as advanced SoX or RUL, is designed to have a cloud counterpart with integrated connectivity and analytics. These enable OTA updates to unlock regular software improvements to achieve superior performance, safety and reliability over the lifetime of the batteries and EVs.
Singapore, Singapore
Provider of a cloud energy management system designed to create smart and connected eco-systems through disruptive innovation. The company's system provides real time energy intelligence and intelligent controls for energy optimization, enabling people to do things better and more efficiently.
Palo Alto, California, United States
A climate and weather intelligence company offering end-to-end weather intelligence and AI-based global forecasts.
Salt Lake City, Utah, United States
Databento is a licensed distributor of market data from over 60 trading venues. It offers market data APIs for real-time and historical data.
Berlin, Germany
Solytic is one of Europe's leading independent energy-IoT-data platforms, connecting production data from different energy technologies and manufacturers, enabling the digital transition towards a renewable electricity grid of decentralized stakeholders.
United States
Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all physical & virtual servers, cloud deployments, Kubernetes clusters & IoT devices, to monitor systems, containers & apps. It scales nicely from a single server to thousands of servers, even in complex multi/mixed/hybrid cloud environments. Given enough disk space it can keep your metrics for years. KEY FEATURES: 💥 Collects metrics from 800+ integrations OS metrics, container metrics, VMs, hardware sensors, applications metrics, OpenMetrics exporters, StatsD, and logs 💪 Real-Time, Low-Latency, High-Resolution All metrics are collected per second & are on the dashboard immediately after data collection 😶🌫️ Unsupervised Anomaly Detection Trains multiple Machine-Learning models for each metric collected and detects anomalies based on the past behavior of each metric individually 🔥 Powerful Visualization Clear and precise visualization that allows you to quickly understand any dataset, but also to filter, slice and dice the data directly on the dashboard, without the need to learn any query language 🔔 Out of box Alerts Hundreds of alerts out of the box to detect common issues and pitfalls, revealing issues that can easily go unnoticed. It supports several notification methods to let you know when your attention is needed 📖 systemd Journal Logs Explorer (beta) systemd journal logs explorer, to view, filter & analyze system & apps logs by directly accessing systemd journal files on individual hosts & infrastructure-wide logs centralization servers 😎 Low Maintenance Fully automated: automated dashboards, out-of-the-box alerts, auto-detection & discovery of metrics, zero-touch ML, easy scalability & CI/CD friendly ⭐ Open & Extensible Netdata is a modular platform that can be extended in all possible ways and it also integrates nicely with other monitoring solutions
Atlanta, Georgia, United States
Developer of a real-time financial data platform that displays stocks, forex and cryptocurrency data, enabling clients to build APIs efficiently.
Nottingham, Nottinghamshire, United Kingdom
Designed to continuously monitor, plan and optimize data center performance, EkkoSense keeps your data center finely tuned and operating at peak performance. A machine learning platform built by PhD-level thermodynamic experts, it uses advanced sensing and software tools, data analytics and expert services to: ➤ Reduce thermal risk and maintain 100% data center cooling compliance ➤ Release (M&E) capacity thanks to real-time thermal insights, so instead of adding more cooling systems, you can keep existing systems on standby and release capacity ➤ Cut cooling costs. Data centre rooms that have been thermally optimized by EkkoSense typically saves up to 30% on data centre cooling costs. Cooling savings alone pays for the platform very quickly – typically in less than a year Plus, it’s extremely intuitive, immersive, easy to use and can be self-installed. How does it work? The EkkoSense platform includes: ➤ Cooling Advisor – to give you daily, actionable advice on how to optimize your data halls ➤ Zones of Influence – using machine learning to show you which cooling units are predominantly serving which racks ➤ Capacity planning – plan future power, cooling and space capacity with simple drag and drop and manage current capacity much more accurately and effectively ➤ Power management - visualise power schematics from site incomer to rack. Manage current power demands and reserve future capacity. Rapid go/no go decisions on additional loads EkkoSense is currently deployed at 300+ datacenter sites including Digital Realty, Telefonica, Bloomberg, Santander, VISA, and many other large corporations. To see how EkkoSense works watch this short video: https://youtu.be/fxg7WpzPk1s or request an online demo at www.ekkosense.com/demo
San Francisco, California, United States
AppOptics combines all the great features of Librato with new, additional functionality including host maps, distributed transaction tracing, 150+ cloud-ready integrations, and affordable pricing.
- Must analyze time-ordered data to identify trends and patterns - Should provide forecasting capabilities to predict future outcomes based on historical data - Must include visualization tools to present data analyses clearly - Should enable anomaly detection to highlight significant deviations in datasets - Target users typically include data analysts, financial professionals, and business intelligence teams - Not limited to just basic data processing; must also offer advanced analytical features
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