Best AIOps Tools for Microsoft Teams
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Compare the Top AIOps Tools that integrate with Microsoft Teams as of April 2026
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This a list of AIOps tools that integrate with Microsoft Teams. Use the filters on the left to add additional filters for products that have integrations with Microsoft Teams. View the products that work with Microsoft Teams in the table below.
What are AIOps Tools for Microsoft Teams?
AIOps tools combine artificial intelligence and machine learning to enhance IT operations by automating the detection and resolution of issues in complex IT environments. They analyze massive amounts of data from various sources—like logs, metrics, and events—to identify anomalies and predict potential outages before they impact business. These tools enable proactive incident management, reduce noise by correlating alerts, and provide actionable insights for faster troubleshooting. AIOps supports continuous monitoring and root cause analysis, helping teams improve system reliability and performance. By integrating with existing IT infrastructure and tools, AIOps enhances operational efficiency and enables smarter decision-making. Compare and read user reviews of the best AIOps tools for Microsoft Teams currently available using the table below. This list is updated regularly.
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1
Robin by Atera
Atera
Robin by Atera is an autonomous IT support agent designed to automatically diagnose and resolve technical issues across devices and cloud environments. The system acts as an AI-powered IT assistant that manages support requests from start to finish without human intervention. Robin receives requests from platforms such as Slack, Microsoft Teams, email, and IT service management tools, verifies the user’s identity, and gathers technical context to understand the problem. It can then perform approved actions on devices, networks, or cloud systems to resolve the issue. By automating troubleshooting and IT support workflows, Robin helps organizations reduce downtime and improve support efficiency. -
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Site24x7
ManageEngine
ManageEngine Site24x7 is a comprehensive observability and monitoring solution designed to help organizations effectively manage their IT environments. It offers monitoring for back-end IT infrastructure deployed on-premises, in the cloud, in containers, and on virtual machines. It ensures a superior digital experience for end users by tracking application performance and providing synthetic and real user insights. It also analyzes network performance, traffic flow, and configuration changes, troubleshoots application and server performance issues through log analysis, offers custom plugins for the entire tech stack, and evaluates real user usage. Whether you're an MSP or a business aiming to elevate performance, Site24x7 provides enhanced visibility, optimization of hybrid workloads, and proactive monitoring to preemptively identify workflow issues using AI-powered insights. Monitoring the end-user experience is done from more than 130 locations worldwide.Starting Price: $9.00/month -
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Edge Delta
Edge Delta
Edge Delta is a new way to do observability that helps developers and operations teams monitor datasets and create telemetry pipelines. We process your log data as it's created and give you the freedom to route it anywhere. Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source. We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost. By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment.Starting Price: $0.20 per GB -
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Sedai
Sedai
Sedai is an autonomous cloud management platform powered by AI/ML delivering continuous optimization for cloud operations teams to maximize cloud cost savings, performance and availability at scale. Sedai enables teams to shift from static rules and threshold-based automation to modern ML-based autonomous operations. Using Sedai, organizations can reduce cloud cost by up to 50%, improve performance by up to 75%, reduce failed customer interactions (FCIs) by 75% and multiply SRE productivity by up to 6X for their modern applications. Sedai can perform work equivalent to a team of cloud engineers working behind the scenes to optimize resources and remediate issues, so organizations can focus on innovation.Starting Price: $10 per month -
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Discover how to start your AIOps journey and transform your IT operations with IBM Cloud Pak for Watson AIOps. IBM Cloud Pak® for Watson AIOps is an AIOps platform that deploys advanced, explainable AI across the ITOps toolchain so you can confidently assess, diagnose and resolve incidents across mission-critical workloads. If you’re looking for IBM Netcool® Operations Insight or any previous IBM IT management offerings, IBM Cloud Pak for Watson AIOps is the evolution of your current entitlement. Correlate across all relevant data sources. Detect hidden anomalies, anticipate issues and resolve faster. Proactively avoid risks and automate runbooks for more efficient workflows. Correlate a vast amount of unstructured and structured data in real-time with AIOps tools. Keep teams focused, surfacing insights and recommendations into existing workflows. Build policy at the microservice level and automate across application components.
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6
Selector Analytics
Selector
Selector’s software-as-a-service employs machine learning and NLP-driven, self-serve analytics to provide instant access to actionable insights and reduce MTTR by up to 90%. Selector Analytics uses artificial intelligence and machine learning to conduct three essential functions and provide actionable insights to network, cloud, and application operators. Selector Analytics collects any data (including configurations, alerts, metrics, events, and logs), from various heterogeneous data sources. For example, Selector Analytics may harvest data from router logs, device or network metrics, or device configurations. Once collected, Selector Analytics normalizes, filters, clusters, and correlates metrics, events, and alarms using pre-built workflows to draw actionable insights. Selector Analytics then uses machine learning-based data analytics to compare metrics and events and conduct automated anomaly detection.
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