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Top 39 AIOps Tools SaaS Companies in May 2026

As of May 2026, there are 39 SaaS companies in AIOps Tools. They have combined revenues of $338.3M and employ 2.1K people. They have raised $411.9M and serve 3.8K customers combined.

AIOps tools utilize artificial intelligence to enhance IT operations by automating and optimizing workflows. These tools analyze vast amounts of data from various IT systems to generate insights, enabling organizations to identify patterns, predict issues, and respond to incidents more effectively. Primary use cases include anomaly detection, performance monitoring, root cause analysis, and incident management, helping organizations to maintain optimal system performance and user experience. The typical features of AIOps tools include machine learning capabilities, data ingestion from multiple sources, real-time analytics, and advanced visualization. End-users of AIOps span various roles, predominantly within IT operations and DevOps teams, but also extend to IT management and business analysts who rely on insights for decision-making. As IT environments become increasingly complex, AIOps is becoming a critical component for organizations aiming to leverage data-driven approaches to manage their IT operations efficiently.

Companies
39
Revenue
$338.3M
Funding
$411.9M
Employees
2.1K

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Top AIOps Tools Companies

Showing 10 of 1 companies ranked by annual revenue.

1
ScienceLogic

Reston, Virginia, United States

ScienceLogic is the global leader in hybrid IT service assurance. Over 50,000 global service providers, enterprises, and government organizations rely on ScienceLogic to significantly enhance IT efficiency, optimize operations, and ensure business continuity. ScienceLogic is the first monitoring solution to provide a comprehensive, real-time view of all IT components, whether they reside in a public cloud environment or on-premises. With hundreds of packaged management apps and custom automation capabilities, we deliver the global scale, resiliency, and automation needed to simplify the constantly evolving task of managing IT infrastructure, applications, and services.

Revenue
$100.3M
Customers
1K
Year founded
2003
Funding
$235.2M
Team size
593
Growth
44.63%

Inclusion Criteria

- Must leverage artificial intelligence and machine learning to analyze IT data - Should provide functionalities for anomaly detection and performance monitoring - Must integrate data from multiple sources to generate actionable insights - Should facilitate incident management through automated root cause analysis - Not just alerting; must also enable proactive problem solving and predictive maintenance - Must support real-time analytics to assist with immediate decision-making - Should offer visualization tools for better data representation and understanding