Self-Healing Operations | AIOps | Autonomous Remediation
Stop Responding to Incidents. Stop Having Them.
Downtime is a systems problem, not a ticket-routing problem.
QyrusAI continuously observes your IT estate, understands how failures propagate through dependencies, and resolves incidents autonomously — so resilience is built in, not bolted on.
CORE FEATURES
Built to Turn Incident Response Into
Autonomous Resilience.
Every feature here exists to close the gap between “something is wrong” and “it’s already fixed.” Together they replace human-dependent triage with a system that understands context, acts on it, and gets sharper with every incident.
Live Enterprise Knowledge Graph
Continuously maps interdependencies between applications, infrastructure, and configurations — training the platform to detect assignment groups, ticket priority, and intent without SME input.
Digital Twin & Chaos Engineering
Mirrors your IT ecosystem in a safe, virtual environment, running simulations and controlled failure experiments to harden the real environment before incidents occur.
Agentic Auto-Heal
Perceives signals, plans a diagnostic or remediation path, and executes it autonomously — validating the fix and feeding results back into the system to keep improving.
Agentic Cost Optimization
Detects idle resources and inefficiencies continuously and remediates them through governed, human-in-the-loop AI workflows.
Cloud Migration Intelligence
Sequences cloud migration waves from observed dependency data. Prevents cascade failures from undiscovered cross-system connections.
Intelligent Twin
Simulates the impact of any planned change in a digital twin before it runs in production. The blast-radius check that prevents go-live incidents.
Legacy Code Conversion
Converts legacy code in the optimal sequence determined by the dependency map. Context-aware conversion that understands what the code does, not just what it says.
Knowledge Graph (shared layer)
A continuously-observed model of every application, dependency, business service, and cost line in your estate. Every pillar reads from it. Every action writes back to it.
HOW IT WORKS
See the Signal. Diagnose the Cause.
Resolve Autonomously.
Optimize Continuously.
Self-healing isn’t one capability — it’s a closed loop. Each stage feeds the next, turning raw telemetry into diagnosed problems, diagnosed problems into autonomous fixes, and every incident into a lesson the system retains.
Continuously map the IT and application landscape — automatically.
QyrusAI builds a Live Enterprise Knowledge Graph of your environment in real time — servers, VMs, networks, applications, and their interdependencies. Fragile and “noisy” components are identified automatically, and ticket trends and customer sentiment are analyzed to prioritize what to automate first. No manual CMDB upkeep — the estate is observed, not surveyed.
Understand what's actually breaking — before a human ever looks.
Anomalies are detected and root causes identified in real time, using the dependency graph to trace how issues propagate across applications, services, and infrastructure. QyrusAI turns a raw alert into a diagnosed, prioritized problem — collapsing the investigation phase that traditionally consumes the majority of an engineer’s time.
Fix the incident autonomously — in minutes, not hours.
QyrusAI executes “Auto Heal” workflows through agentic AI, with human-in-the-loop control where it matters. What typically takes 1–10 hours of manual triage and escalation is resolved in under 30 minutes, with automated validation confirming the fix held.
Prevent the next incident, not just fix the last one.
The platform forecasts capacity and availability needs, tunes resources continuously, and uses Chaos Engineering — running controlled experiments against a Digital Twin — to find and harden vulnerabilities before they ever reach production.
Challenges
The Incident Response Problem
Every Enterprise Knows.
Alerts Without Answers
Monitoring tools tell you something broke, not why. Signals are surfaced without understanding the application and service dependencies that actually explain how the failure happened.
Fragmented Context Across Teams
SMEs, ops, and engineering each hold a partial picture of the environment, so every resolution depends on the right expert being available at the right time.
Resolution That Depends on People
Traditional workflows — ticket creation, routing, escalation, multi-level support — consume 1 to 10 hours per incident, because root-cause analysis still runs through a human connecting the dots.
Fixes That Don't Prevent Recurrence
Static runbooks and rule-based automation can't keep pace with dynamic infrastructure — the same class of incident keeps coming back because nothing learns from it.
A GLIMPSE ON THE NUMBERS
Resolve Faster. Stay in Control. Prove the Resilience.
These aren’t projections — they’re the measurable result of moving root-cause analysis and remediation out of manual workflows and into a governed, autonomous loop. The numbers hold up whether you’re modernizing legacy AMS or scaling a mature AIOps practice.
reduction in MTTR & time-to-diagnose
reduction in operational costs
legacy application rationalization
Uptime
Continuous testing. Continuous learning. Continuous value.
Join leading enterprises
driving the loop forward.
Integration
Works With Your Existing Enterprise Stack.
QyrusAI Modernize connects to your existing tools — CMDBs, ITSM platforms, cloud providers, and enterprise architecture repositories — so discovery enriches the tools you already use rather than replacing them.
CUSTOMER TESTIMONIALS
Enterprises running the loop
in their own words.
Real Teams. Real Outcomes. Real Confidence in what ships next.
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Qyrus not only supports the testing of our Web, Mobile, and API components as part of our CI/CD processes, but also in ongoing regression-testing across our partner ecosystem. The real power of Qyrus is that we have this extremely broad testing capability in one tool, run in the cloud, and reusable across all our development teams.
The transition to Qyrus has marked a significant turning point for us. By embracing automation, we not only streamlined our SAP test automation process but also achieved a remarkable reduction in overall project testing time by 40%.
... the Qyrus platform have been a great addition to Monument's product delivery capabilities. Within a few months, we have been able to create a comprehensive test suite of complex end-to-end test scenarios spanning multiple platforms and channels. The Quinnox team has helped us embed the Qyrus solution, and the supporting processes around it, into our agile delivery methodology.
Resources
From architecture deep-dives to analyst recognition, explore how the same Knowledge Graph and agentic framework powering self-healing extends across the rest of the QyrusAI platform.
Blog
August 19, 2026 | 
18 min
User Acceptance Testing Best Practices: A Complete UAT Strategy Guide for SAP Teams
Read More
August 13, 2026 | 2 min
Qyrus Named in Gartner’s Market Overview for API and MCP Testing Tools
Read More
August 13, 2026 | 2 min
Qyrus Named in Gartner’s Market Overview for API and MCP Testing Tools
Read More
Blog
August 19, 2026 | 18 min
User Acceptance Testing Best Practices: A Complete UAT Strategy Guide for SAP Teams
Read More
Case Study
Events
Reports
August 13, 2026 | 2 min
Qyrus Named in Gartner’s Market Overview for API and MCP Testing Tools
Read More
Whitepaper
August 13, 2026 | 2 min
Qyrus Named in Gartner’s Market Overview for API and MCP Testing Tools
Read More
FREQUENTLY ASKED QUESTIONS
Common Questions About QyrusAI Modernization
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How is this different from a CMDB or an EA repository like LeanIX?
Does Qyrus Modernize work with SAP S/4HANA migrations?
Yes — and SAP migrations are one of the highest-urgency use cases. QyrusAI reads your SAP environment in read-only mode, inventories all RFCs, IDocs, OData services, SOAP connections, CPI integrations, background jobs, and Z-objects, and produces a blast-radius score for every proposed S/4HANA change. The Estate X-Ray and Phase Zero governance workflow are specifically designed for ECC-to-S/4HANA programmes with fixed cutover dates.
How long does the initial discovery scan take?
The first scan of a mid-market estate (200–400 applications) typically produces an initial topology map within 48–72 hours. The map enriches continuously from that point — adding confidence detail, business-service attribution, and dependency validation as more signals are observed. A Phase Zero engagement (discovery, dependency mapping, and modernization prioritization) is typically scoped at 4–6 weeks.
Does it require agent installation on every system?
No. QyrusAI reads from APIs, connectors, log streams, and cloud provider metadata — it does not require an agent on every application or server. For some legacy on-premise environments a lightweight collector may be deployed, but this is scoped per engagement and never required across the full estate before value is delivered.
What happens to the modernization plan if the estate changes while the programme is running?
The Knowledge Graph is continuously updated. If a new application is deployed, a dependency changes, or a system is decommissioned mid-programme, the change is reflected in the graph and the modernization wave plan is re-scored automatically. Your transformation plan is always based on the current estate, not the estate as it was when the programme started.
Does Qyrus Modernize integrate with Assure for testing?
Yes — this is the core joint value of the two pillars. Every modernization slice Modernize produces is automatically handed to Assure for equivalence testing. Assure generates test cases from the code analysis output, runs them against the modernized slice, and produces an evidence record before any release decision is made. The conversion is never marked complete until Assure has proved it works.
STAY AHEAD, STAY IN THE LOOP
Move From Incident Response to
Autonomous Resilience.
30-minute walkthrough with a solutions architect — we’ll show you where your environment is most exposed to recurring incidents, and how QyrusAI would resolve them autonomously today.
