Application Discovery · Dependency Mapping · Legacy Modernization
Stop Staffing Tickets. Start Preventing Them.
Most L1/L2 effort goes into triage, not resolution. QyrusAI reads every ticket, log, and signal in context, diagnoses root cause in minutes, and resolves routine incidents autonomously — turning your support layer from a cost center into a funding source for modernization.
Challenges
The L1/L2 Problem
Every Enterprise Knows.
Support tiers are drowning in volume they shouldn't have to touch. Discover how replacing manual triage and SME-dependent diagnosis with a knowledge-graph-driven agentic layer turns L1/L2 from a headcount problem into a self-resolving system.
Triage Without Context
Tickets are routed on keywords and gut feel, not on how the underlying applications and infrastructure actually connect - so the wrong team ends up owning the wrong problem.
The Same Tickets, Over and Over
Without a system that learns from resolutions, L1/L2 keeps re-solving the same class of incident — ticket volume never actually shrinks.
Diagnosis That Depends on People
Root cause analysis relies on fragmented historical tickets and SME memory, consuming 1 to 10 hours per incident before a fix is even attempted.
Escalation as the Default
When L1 can't resolve it, it moves to L2, then L3 — not because the issue is complex, but because no one has the context to stop the handoff.
How it works
Discover the Estate. Detect the Signal.
Diagnose the Cause. Remediate Autonomously.
Explore how QyrusAI compresses the ticket lifecycle — from first alert to validated fix — using a live Knowledge Graph and agentic AI workflows that operate with intent, not just instructions.
Continuously map infrastructure, applications, and ticket patterns — automatically.
QyrusAI builds a real-time inventory of VMs, networks, and applications alongside historical ticket trends, clustering repeated incidents and service requests as they emerge. No manual inventory audits — the estate and its failure patterns are observed, not surveyed.
Separate the signal from the noise before an agent ever gets involved.
Anomaly detection, event correlation, and incident prediction filter out non-actionable alerts, so L1 agents only see what actually requires attention. This shifts the team from reactive alert-chasing to proactive, prioritized triage.
Identify root cause in minutes, not hours.
Using the Knowledge Graph, QyrusAI enriches each incident with dependency context and prescriptive solution paths – compressing a 1–10-hour manual RCA process to under 30 minutes and letting L1.5 agents resolve what used to require L2/L3 escalation.
Resolve routine incidents autonomously — with a human in the loop where it matters.
QyrusAI executes self-healing workflows generated and validated through Digital Twin simulation, closing the loop from detection to confirmed resolution — without waiting on a human to execute every step.
Core Features
Built to Turn Support Tiers Into
a Self-Resolving System.
Stop measuring L1/L2 by headcount and ticket backlog. Discover how a live Knowledge Graph, agentic remediation, and continuous learning turn routine support into an autonomous, self-improving layer.
Intelligent Ticket Triage
Automatically detects assignment group, priority, and intent for every incoming ticket - eliminating the manual "triage hop" and routing loss.
Knowledge-Graph RCA
Enriches every incident with dependency context, compressing root cause analysis from hours to minutes and reducing SME dependency.
Agentic Auto-Remediation
Executes governed, human-in-the-loop AI workflows to resolve L1/L1.5 incidents autonomously, validated against Digital Twin simulations.
Continuous Learning Loop
Feedback mechanisms like the KB Nudger and Incident Summarizer refine agent knowledge with every resolution — shifting the mission from ticket resolution to ticket prevention.
A GLIMPSE ON THE NUMBERS
Outcomes & Benefits
Rationalize Faster. Reduce Risk. Fund the Transformation.
Secure a resilient, future-proofed IT ecosystem capable of adapting instantly. Achieve rigorous performance benchmarks while drastically lowering operational overhead.
cost reduction in L1/L2 activities
Improvement in MTTR
reduction in routine operations effort
improvement in CSAT scores
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
Go Deeper on QyrusAI L1/L2 Automation
Dive into our latest research and implementation guides. See how a live Knowledge Graph paired with agentic remediation turns support-tier automation into a funding mechanism for broader modernization.
Blog
September 4, 2026 | 
14 min
How to Write Effective Test Scripts: A Straightforward Guide
Read More
September 4, 2026 | 12 min
SAP Test Automation: The Complete 2026 Guide
Read More
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
September 4, 2026 | 14 min
How to Write Effective Test Scripts: A Straightforward Guide
Read More
September 4, 2026 | 12 min
SAP Test Automation: The Complete 2026 Guide
Read More
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.
Move From Ticket Resolution to Ticket Prevention.
30-minute walkthrough with a solutions architect — we’ll show you where your L1/L2 volume is coming from, and how QyrusAI would resolve it autonomously today.
