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.
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Showing 10 of 1 companies ranked by annual revenue.
St. Louis, Missouri, United States
The Climate Corporation is a digital agriculture company that examines weather, soil and field data to help farmers determine potential yield-limiting factors in their fields.
- 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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