Forrester Total Economic Impact™ study finds Edwin AI delivered a 313% ROI for composite organization.

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Forrester Total Economic Impact™ study finds Edwin AI delivered a 313% ROI for composite organization.

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ITOps Context Graph

Turn operational data into AI-ready context

Connect topology, telemetry, incidents, changes, runbooks, and knowledge into a shared context graph that helps Edwin AI investigate, explain, and act faster.

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Edwin AI has the context behind every incident

Connected operational data

Unify alerts, metrics, logs, topology, tickets, changes, runbooks, knowledge articles, and digital experience signals into one operational context layer.

Evidence-backed RCA

Help Edwin AI connect symptoms, dependencies, historical incidents, and recent changes to explain likely root cause with supporting evidence.

Live topology intelligence

Map impacted infrastructure, applications, services, dependencies, and ownership so teams understand blast radius faster.

Incident memory

Preserve what happened, what changed, what actions were taken, and what resolved the issue so future investigations start smarter.

Better agent reasoning

Give Edwin AI structured ITOps context so it can move beyond generic chatbot answers and deliver operationally useful recommendations.

Automation-ready context

Package the right evidence, scope, dependencies, and next steps so teams can move from investigation to approved remediation faster.

CONTEXT ACROSS THE INCIDENT LIFECYCLE

Build the context layer for agentic ITOps

The ITOps Context Graph connects fragmented operational data into a durable intelligence layer for Edwin AI. It helps agents understand what changed, what is affected, what likely caused the issue, and what action should happen next.

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Detect
Investigate
Diagnose
Remediate
Collaborate
Learn

Connect every signal to operational context

The ITOps Context Graph links alerts, metrics, logs, traces, synthetic tests, topology, and ownership data so Edwin AI can understand the full operational picture before investigation begins.

  • Connects real-time signals with affected infrastructure, applications, and services.
  • Reduces noise by grouping related symptoms around shared dependencies and business impact.

Start every investigation with the right context

Edwin AI uses the context graph to assemble incident scope, severity, affected services, related alerts, dependencies, recent changes, and known fixes.

  • Surfaces likely impact, blast radius, and next investigative steps.
  • Reduces manual dashboard-hopping across monitoring, ITSM, logs, and knowledge systems.

Find root cause with connected evidence

The context graph helps Edwin AI compare current symptoms against historical incidents, topology, changes, dependencies, logs, and runbooks to identify likely root cause.

  • Maps upstream dependencies, downstream impact, and related CIs.
  • Uses historical patterns and current signals to validate likely causes.

Turn context into recommended action

Edwin AI can use graph context to recommend runbooks, remediation steps, escalation paths, and automation workflows based on the affected service, dependency, and known fix history.

  • Connects findings to approved runbooks, ITSM workflows, and automation tools.
  • Keeps actions grounded in incident scope, evidence, and operational constraints.

Keep responders aligned with shared context

The context graph gives teams a common source of operational truth across war rooms, tickets, dashboards, and incident reviews.

  • Helps identify relevant SMEs, owners, escalation paths, and related incidents.
  • Keeps Slack, Teams, ServiceNow, and Edwin AI workflows grounded in the same incident context.

Make every incident improve the next one

The context graph preserves incident evidence, actions, outcomes, and prevention notes so Edwin AI can improve future investigations and recommendations.

  • Captures resolved incident patterns, known fixes, and recurrence signals.
  • Supports post-incident reporting, problem management, and proactive remediation.

CONNECTED OPERATIONAL INTELLIGENCE

Make every signal more useful

The ITOps Context Graph connects Edwin AI to the systems your teams already use across observability, ITSM, automation, knowledge, cloud, and digital experience. It turns data from every integration into shared context Edwin AI can use to understand relationships, dependencies, impact, and history.

See integrations

3,000+

pre-built integrations across your full tech stack

100%

bi-directional sync with ITSM platforms like ServiceNow

Domain-specific AI

AI built on real ITOps context

Generic AI tools lack the operational context needed for reliable incident response. Edwin AI uses the ITOps Context Graph to understand what changed, what is affected, likely cause, and next action.

67%

ITSM incident reduction

STRATEGIC AI ECOSYSTEM

Context that powers agentic ITOps

Agentic ITOps need durable operational context that agents can use to investigate, reason, collaborate, and act. The ITOps Context Graph gives Edwin AI the structured intelligence needed to support deeper investigations, smarter automation, and better operational decisions.

88%

alert volume reduction

Real Agentic ITOps ROI

313% ROI achieved with LogicMonitor Edwin AI

A commissioned study conducted by Forrester Consulting on behalf of LogicMonitor found that a composite organization achieved 313% ROI over with a 6 month or less payback with LogicMonitor Edwin AI.

Read the study

<6

months payback period

313%

ROI

Trusted by IT leaders

Leading companies don’t just monitor—they Envision peak performance

See how IT teams big and small cut alert noise, resolve issues faster, and keep networks running at full speed.

See their success

“Edwin AI helps us analyze data, reduces alerts, and will self-heal issues before they escalate”

Peter Bethel
Infrastructure Manager of Nine Entertainment Co.
Nine Entertainment Co.

“Edwin AI delivered value within an hour of implementation.”

Kris Manning
Global Head of IT Networks of Syngenta
Syngenta

“Capital Group has 1,000+ alerts/ day. LogicMonitor will eliminate that noise.”

Shawn Landreth
VP of Networking and Reliability Engineering of Capital Group
Capital Group

“LogicMonitor is a valuable partner, constantly innovating and adapting to our business needs.”

Rafik Hanna
SVP, Topgolf Technologies of Topgolf
Topgolf

“Edwin AI is not another AI tool, but an essential part of our IT team.”

Jesse Cardinale
IT Infrastructure Lead of Chemists Warehouse
Chemists Warehouse

“Switching from SolarWinds to LogicMonitor showed us how much we were missing.”

Scott LaPaglia
Senior Systems Administrator of Hain Celestial
Hain Celestial

“Edwin AI will be 100x faster than a human and able to manage complex problems.”

Gaël Grootaert
Group Director, Managed Services of Devoteam
Devoteam

“LogicMonitor tells you what’s happening in the environment.”

Rich Johnston
Director, Hosting Platforms of Carrier
Carrier

“The sheer power of LogicMonitor’s monitoring capability is amazing.”

John Burriss
Senior IT Solutions Engineer of RaySearch Laboratories
RaySearch Laboratories

“Edwin AI cut noise by 90% & ITSM incidents by 76%, enabling better customer service.”

Joshua Powell
Managed Services Lead of Nexon
Nexon

“The single pane of glass across all of our regions enables us to act more proactively.”

Dominik Hunn
Systems Engineer of Franke Group
Franke Group

BY THE NUMBERS

Edwin AI: Built to deliver impact

0 %
less incident workload
0 hrs
saved per incident
0 %
eduction in MTTR

GET ANSWERS

FAQs

Get answers to common questions about Edwin AI’s Context Graph.

Have more? Ask our experts

What is an ITOps Context Graph?

An ITOps Context Graph is a connected intelligence layer that links operational data across alerts, metrics, logs, topology, tickets, changes, runbooks, knowledge articles, and incident history. It helps Edwin AI understand relationships between systems, symptoms, dependencies, and outcomes so investigations are grounded in real operational context.

How is a context graph different from a CMDB?

A CMDB records configuration items and relationships. The ITOps Context Graph extends that idea with live operational signals, topology, incidents, changes, alerts, logs, ownership, and historical resolution patterns. It is designed for AI-driven investigation, not just asset inventory or service mapping.

How does the context graph help Edwin AI?

The context graph gives Edwin AI the information needed to reason about incidents. It helps Edwin AI connect symptoms to dependencies, identify affected services, compare current issues against historical patterns, explain likely root cause, and recommend the next best action.

Can the context graph reduce manual investigation?

Yes. Teams often lose time moving between dashboards, logs, tickets, topology maps, change records, runbooks, and chat history. The ITOps Context Graph helps Edwin AI assemble that context automatically, so responders can start with a clearer view of scope, impact, probable cause, and next steps.

Does the context graph support automation?

Yes. The context graph helps package the evidence, affected services, dependencies, owners, runbooks, and operational constraints needed for safer remediation. Teams can start with recommendations and progressively connect approved automations, workflows, and runbooks as trust and governance mature.

Can the context graph help prevent future incidents?

Yes. By preserving incident patterns, known fixes, recurrence signals, change history, and resolution outcomes, the ITOps Context Graph helps Edwin AI identify repeat issues and recommend proactive remediation. It turns incident history into reusable operational intelligence.

How quickly can teams get value from a context graph?

Teams can start with read-only use cases such as incident enrichment, AI investigation, root cause analysis, dashboard generation, and post-incident reporting. Automation and self-healing can be added progressively as operational context, governance, and trust mature.

Your path to self-healing IT starts with Edwin AI

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