QDXray provides an AI‑powered analytics platform that ingests real‑time telemetry from fiber OLTs, DOCSIS head‑ends, Wi‑Fi mesh nodes, and mobile back‑haul to detect outages and pinpoint fault locations across heterogeneous access networks. The solution offers role‑based dashboards, predictive component‑wear analytics, and REST/FHIR API integration, available as a cloud service or on‑premise appliance for broadband operators.
Funding
Funding not disclosed
Founders
Product
Problem
Telecommunication and MSO operators manage increasingly complex access networks—FTTx, DOCSIS/HFC, and WiFi—comprised of numerous passive components and distributed customer premises equipment. Fault isolation in these dense topologies is time‑consuming, leading to high mean‑time‑to‑diagnose (MTTD), frequent truck rolls, and SLA breaches that drive customer churn.
Solution
QDXray delivers an AI‑powered analytics platform that ingests streaming telemetry from OLTs, DOCSIS head‑ends, Wi‑Fi mesh nodes, and mobile back‑haul to generate actionable insights on network health. Advanced machine‑learning models automatically detect outages, degradation patterns, and RF interference, pinpointing the exact fault location across fiber, coax, and wireless segments. Operators access these insights through intuitive, role‑based dashboards that support both proactive maintenance and rapid reactive troubleshooting, reducing MTTD and associated operational costs. The solution is available as a cloud service for scalable TCO or as an on‑premise appliance for environments with strict security requirements. Integrated Wi‑Fi quality indicators complete the end‑to‑end QoE view, helping providers address the dominant source of customer‑premises complaints.
Target Audience
Primary customers are broadband service providers, cable operators, and MSOs that manage large‑scale FTTx, DOCSIS/HFC, and Wi‑Fi infrastructures and need to improve fault detection, reduce operational expenses, and enhance subscriber QoE.
Features
- Real‑time telemetry aggregation from fiber OLTs, DOCSIS CMTS, Wi‑Fi mesh controllers, and mobile back‑haul devices via streaming APIs
- AI/ML outage detection and root‑cause classification models tailored for FTTx, DOCSIS/HFC, and Wi‑Fi layers
- Interactive, drill‑down dashboards with KPI visualizations, heat‑maps, and automated alerting for SLA violations
- Dual deployment options: SaaS cloud with multi‑tenant isolation or on‑premise virtual appliance behind corporate firewalls
- Predictive analytics for component wear (e.g., splitter connector degradation) and RF interference trends in HFC networks
- RESTful and FHIR‑compatible APIs for seamless integration with existing OSS/BSS and ticketing systems
- Role‑based access control and end‑to‑end encryption to meet industry security and compliance standards