• Splunk AIOps: It is a cloud-based AIOps platform that helps organizations to automate IT operations. It uses machine learning to detect anomalies, identify root causes, and recommend remediation actions.
• Dynatrace AIOps: It is an AIOps platform that helps organizations to predict and prevent problems. It uses machine learning to analyze telemetry data from applications, infrastructure, and users to identify potential problems before they cause outages.
• New Relic AIOps: It is an AIOps platform that helps organizations to improve their IT operations by automating tasks, identifying problems, and resolving incidents faster. It uses machine learning to analyze data from applications, infrastructure, and users to identify potential problems and recommend remediation actions.
• IBM Watson AIOps: It is an AIOps platform that helps organizations to improve their IT operations by automating tasks, identifying problems, and resolving incidents faster. It uses machine learning to analyze data from applications, infrastructure, and users to identify potential problems and recommend remediation actions.
• Google Cloud AIOps: It is an AIOps platform that helps organizations to improve their IT operations by automating tasks, identifying problems, and resolving incidents faster. It uses machine learning to analyze data from applications, infrastructure, and users to identify potential problems and recommend remediation actions.

There are many AIOPS (Artificial Intelligence for IT Operations) tools available, here are a few examples:

1. ynatrace: Dynatrace is an AIOps platform that focuses on application performance monitoring and management. It uses AI to automate and optimize various aspects of application monitoring, including performance analysis, root cause identification, and real-time insights.
2. Splunk IT Service Intelligence (ITSI): Splunk ITSI is part of the Splunk platform and offers AI-driven insights for IT operations. It combines machine learning and event correlation to provide real-time visibility into the health of IT services, predict and prevent issues, and automate incident response.
3. Moogsoft AIOps: Moogsoft AIOps is designed to help IT teams detect and resolve incidents more effectively. It uses machine learning to identify anomalies, provide context to alerts, and facilitate collaboration among IT personnel for faster problem resolution.
4. AppDynamics: AppDynamics, now a part of Cisco, provides AIOps capabilities for application performance monitoring. It uses AI and machine learning to analyze application data, detect anomalies, and provide insights into performance bottlenecks and user experiences.
5. PagerDuty: PagerDuty offers an incident management platform with AIOps features. It uses AI to help teams identify, prioritize, and respond to incidents by providing real-time insights, automatic alerts, and on-call management.
6. OpsRamp: OpsRamp provides an AIOps platform for hybrid infrastructure management. It combines infrastructure monitoring, event management, and service desk capabilities with AI-driven insights for proactive IT operations.
7. IBM Watson AIOps: IBM Watson AIOps leverages AI and machine learning to automate IT operations. It helps detect, diagnose, and resolve incidents by analyzing data from multiple sources and predicting potential issues.
8. BigPanda: BigPanda is an AIOps platform that focuses on consolidating and correlating alerts from various monitoring tools. It uses machine learning to prioritize alerts, group related incidents, and provide context for efficient incident resolution.
9. LogicMonitor: LogicMonitor is an AIOps platform that specializes in infrastructure monitoring and observability. It uses AI to analyze performance data, predict trends, and identify anomalies in cloud, on-premises, and hybrid environments.
10. ScienceLogic: ScienceLogic provides an AIOps platform for hybrid cloud and IT operations management. It offers automated discovery, monitoring, and troubleshooting with AI-driven insights for improved visibility and proactive incident resolution.