Agentic AIOps Platform

AGENTIC AIOPS PLATFORM

Stop Reacting,
Start Innovating with
Agentic AIOps

Using specialized AI agents to help teams cut through complexity, prioritize what matters, and take guided action before small issues become major incidents.

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POWERING AI FOR LEADING BRANDS AROUND THE WORLD

Why Agentic AIOps matters

Act before incidents escalate

Agentic AIOps gives IT teams the context to understand what’s happening, focus on the issues that matter, and take action before service disruptions spread.

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Reduce alert noise

Group related alerts and events into meaningful insights so teams focus on the signals that indicate real risk, not every threshold breach or duplicate notification.

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Prioritize what matters

Use topology and service context to deeply investigate blast radius, business impact, and which incidents need attention first.

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Preserve team knowledge

Surface public documentation, private knowledge articles, runbooks, and previous incident history so every responder can benefit from proven fixes and expert context.

Take action faster

Put specialized AI agents to work in the background to gather context, recommend next steps, and surface the right automation path while teams stay focused on resolution.

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Automate with control

Discover existing playbooks, generate new workflows, and execute remediation with approvals, RBAC, audit trails, and rollback paths built into the process.

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Track operational trends

Monitor incident, insight, event, and alert trends in one view, then review automation runs and execution history to understand what changed across day-to-day operations.

What You Can Do with Agentic AIOps

Go From Signal To
Resolution Faster

Combines cross-domain observability, AI agents, contextual investigation, and governed automation to help teams detect, understand, act, and learn from every incident.

Detect

Correlate

Investigate

Understand

Act

Identify early warning signals

Agentic AIOps continuously analyzes operational signals across hybrid environments to detect abnormal behavior, recurring patterns, and service risk before issues escalate.

Analyze metrics, logs, traces, events, tickets, topology, and more.
Detect anomalies and early warning signals across domains.
Identify recurring patterns that point to chronic operational risk.
Filter noise so teams see the signals most likely to matter.

Turn alerts into insights

Event Intelligence groups related alerts and events into actionable insights enriched with topology, metadata, and service context. Teams get a clearer view of what is happening and where to focus first.

Deduplicate alert storms and related event streams.
Correlate events across infrastructure, applications, cloud, and ITSM.
Enrich incidents with topology, CMDB, and business context.
Explain why signals were grouped together.

Find root cause with evidence

AI Investigation organizes complex incidents into readable sections that explain what happened, what changed, and what likely caused the issue. Edwin AI grounds answers in logs, metrics, changes, topology, and past fixes.

Generate plain-language incident summaries.
Surface likely root cause with supporting evidence.
Highlight relevant logs, changes, timelines, and impact.
Push selected investigation details into ITSM records.

Ask questions in context

The agentic interface lets teams ask natural-language questions about alerts, events, insights, and resources. Edwin AI can break down complex questions into multi-step workflows and stream answers with source references.

Ask follow-up questions from the Agent homepage or inside an insight.
Query logs, metrics, changes, topology, and knowledge sources.
Show citations and reasoning steps to build trust.
Respect LogicMonitor RBAC so users only see authorized data.

Automate governed remediation

Agentic AIOps helps close the loop from detection to remediation by using specialized AI agents to find existing playbooks, generate new workflows, and execute actions through enterprise controls.

Discover and run relevant existing automations.
Generate context-aware playbooks for recurring issues.
Use approvals, change windows, RBAC, audit trails, and rollback controls.
Validate fixes before closing incidents or updating downstream workflows.

Schedule a demo to see how agentic AI will shift your team from reactive to proactive.

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GET ANSWERS

AIOps FAQs

Have more? Ask our experts

What is AIOps?

AIOps (Artificial Intelligence for IT Operations) is a method for analyzing IT data and identifying patterns, combining historical and real-time data to provide insights for IT teams. Traditional AIOps solutions rely on predefined rules and static thresholds that require manual adjustments, while also struggling to adapt to dynamic changes in IT environments.

What is agentic AIOps?

Agentic AIOps is an advanced approach to IT operations that combines generative AI, agentic AI, and cross-domain observability to automate problem-solving and decision-making. Unlike traditional AIOps, which depends on static rules and manual oversight, Agentic AIOps continuously learns, adapts, and takes real-time actions to prevent disruptions and optimize system performance.

By analyzing structured and unstructured data from across the IT ecosystem, agentic AIOps provides deeper context, enabling proactive issue resolution and reducing downtime. Generative AI powers insights, summaries, and recommendations in natural language, making troubleshooting more accessible. Agentic AI goes further by autonomously executing corrective actions, such as rolling back configurations or initiating failovers, without requiring human intervention. Cross-domain observability integrates disparate data sources, including applications, networks, and infrastructure, into a unified view, allowing IT teams to detect patterns, uncover root causes, and resolve issues faster with complete operational visibility.

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What is anomaly detection?

Anomaly detection is the identification and notification of outliers within gathered datapoints. An anomalous datapoint is something that significantly deviates from a normal data range without reason.

What is machine learning?

Machine learning is the use of algorithms that improve automatically through historical analysis and experience.

What is event correlation?

Event correlation automatically groups event alerts into their most succinct form, vastly reducing the time it takes for support teams to reason about the mass of alerts. Effective event clustering can reduce alerts by over 97%.

What is root cause analysis?

Root cause analysis is the process of finding the core of an issue that caused a chain reaction effect ending in problems.

What are dynamic thresholds?

Dynamic thresholds are data ranges that show an acceptable changing range of datapoints based on similar historical factors.

What is Edwin AI?

Edwin AI is the first AI agent for IT operations, built by LogicMonitor to move beyond traditional AIOps. It proactively predicts, prevents, and resolves issues by analyzing real-time data, filtering out noise, and automating incident response. Unlike conventional tools that only detect problems, Edwin AI understands root causes, recommends actions, and executes fixes autonomously.

With advanced AI reasoning, cross-domain observability, and IT-specific automation, Edwin AI helps IT teams reduce alert noise by 90%, boost productivity by 20%, and prevent outages before they happen—all within a single, intuitive platform.

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