Q-Assure
A hybrid engine, LLM reasoning plus domain rules and graph-based topology analysis, that reconstructs the chain of events behind any incident, identifies the primary root cause, assesses impact and generates a natural-language diagnosis within minutes. Every diagnosis carries a full evidence chain with confidence scores, ready for audit.
What it does.
Incident-chain reconstruction
Builds a directed graph of related events, changes and dependencies to reconstruct the full sequence, work that would take engineers hours, done automatically.
Hybrid diagnosis engine
Codified domain rules handle known patterns at speed; LLM reasoning interprets novel, cross-domain incidents that rules alone cannot diagnose.
Natural-language reports
Plain-English diagnosis reports any operator can act on, with evidence citations, confidence levels, remediation steps and escalation guidance.
Change correlation
Correlates incident onset with recent system changes, deployments and configuration updates, identifying change-induced issues and accelerating rollback decisions.
Self-learning knowledge base
Every resolved incident enriches a knowledge base specific to your environment, so diagnosis accuracy improves continuously over time.
Explore the rest of the platform.
TelioQuantAI Predictive Analytics
Predict. Prevent. Perform.
Service Orchestration
Zero-touch. Zero-wait. Zero-error.
Workforce Management
Right resource. Right place. Right time.
Service Assurance & Fault Management
Always on. Always aware.
See RCA Automation on your operations.
Book a working session and we’ll show this running on your data, not slideware.
