UST CauseIQ - AI-Powered Multi-Domain Network RCA Engine

CauseIQ applies AI-driven correlation and causal-chain analysis across multi-domain network data to identify the true root cause of incidents in near real time. Instead of analysts manually cross-referencing dashboards from RAN, core, transport, and cloud teams, CauseIQ fuses these signals automatically and presents a single, ranked root cause with supporting evidence.

By replacing reactive, siloed investigation with automated cross-domain reasoning, CauseIQ shortens war-room cycles, reduces escalations, and gives NOC teams a defensible, evidence-backed answer to "what broke and why" within seconds of an incident.

CauseIQ leverages AWS services including Amazon CloudWatch for cloud-layer telemetry ingestion and Amazon SageMaker for model training and inference, enabling seamless deployment within your existing AWS environment.

• Cross-domain signal fusion across RAN, core, transport, and cloud
• Automated causal-chain mapping and fault-path visualization
• Confidence-scored root cause recommendations with supporting evidence
• Natural-language query interface for ad-hoc investigations
• Historical root-cause library for recurring fault patterns

• Reduces MTTR by up to 41%, minimizing customer-facing downtime
• Frees senior engineers from manual multi-team correlation work
• Improves first-time-right resolution, cutting repeat tickets
• Provides audit-ready evidence for SLA and vendor disputes
• Scales root-cause expertise across junior NOC staff

UST delivers CauseIQ through a structured, phased engagement:

1. Discovery and Scoping (2-3 weeks): UST conducts a data readiness assessment to identify available telemetry feeds across your RAN, core, transport, and cloud domains. Deliverable: scoping document with integration plan and success criteria.
2. Data Integration and Onboarding (3-4 weeks): UST engineers connect CauseIQ to your alarm, log, and performance data sources. Buyer responsibilities include providing API access or data export feeds from network management systems.
3. Model Tuning and Validation (2-3 weeks): CauseIQ's AI models are calibrated against your network topology and historical incident data. Deliverable: validation report with accuracy benchmarks.
4. Go-Live and Knowledge Transfer (1-2 weeks): Production deployment with NOC staff training and operational runbook handoff.

• Tier-1 mobile operator major incidents: When a fiber cut triggers 200+ RAN alarms across multiple regions, CauseIQ correlates transport layer loss-of-signal events with affected cell sites within 30 seconds and surfaces the single fiber span at fault.
• War-room incident bridges: Provides a single source of truth during multi-vendor, multi-domain outages, eliminating finger-pointing between RAN, transport, and core teams.
• SLA breach root-cause reporting: Generates evidence-backed root cause reports for enterprise customers, documenting the fault path from origin to service impact.
• Recurring fault pattern detection: Identifies chronic issues across network domains that drive repeat tickets, enabling proactive remediation.

• Minimum requirement: access to alarm and performance telemetry from at least two network domains (RAN, core, transport, or cloud)
• Supported data formats: SNMP traps, syslog, streaming KPIs, and REST API exports
• AWS account with appropriate IAM permissions for service deployment
• NOC staff availability for UAT and knowledge transfer sessions

Contact UST through AWS Marketplace messaging to schedule a 30-minute discovery call. Our solutions team will assess your network data landscape and outline a tailored engagement plan for your environment.