Project Name
Cognitive AI for Proactive Network Reliability and Autonomous Support
A US-based telecom operator, managing an extensive network of modems connected via central hubs, partnered with Ksolves to enhance its Proactive Network Maintenance and customer support systems. The client aimed to adopt secure, domain-specific Generative AI to streamline fault detection and provide instant, contextual technician support, thereby reducing resolution time and improving service reliability.
The solution integrates Generative AI, retrieval-augmented generation (RAG), and agentic AI into a robust, secure architecture that accelerates diagnostics and eliminates manual troubleshooting bottlenecks.
- Manual and Time-Consuming Fault Diagnosis: Field engineers relied on manual interpretation of raw network data, making it challenging to identify and correlate faults across devices and network segments quickly.
- Security & Privacy in AI Adoption: Handling sensitive subscriber and network data required an AI framework that prevented leakage while still delivering high-quality results.
- Fragmented Technician Support Tools: Existing systems lacked a unified interface for fault detection and guidance on resolution. This created delays and inconsistencies in troubleshooting, with no single platform combining anomaly detection, contextual reference, and remediation steps.
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Smart Button for Real-Time Anomaly Detection
We developed a Smart Button that automatically detects power issues, spectral impairments, and FM ingress by validating network thresholds in real-time. This reduces manual effort and speeds up the identification of faults.
It integrates RAG-based retrieval to instantly provide SCTE-compliant remediation steps, enabling technicians to act with confidence and speed. With a one-click interface, technicians can access real-time insights and recommended actions, eliminating the need for manual data analysis. -
AI Helpdesk Powered by Retrieval-Augmented Generation
Our AI Helpdesk indexes SCTE documentation using LLMSherpa and FAISS for precise, domain-specific search and guidance. Semantic chunking ensures AI responses maintain context and clarity, even for complex queries. The helpdesk provides cable-specific answers, filtering out generic or irrelevant content to deliver more reliable technician support. -
Robust Guardrails and Security Layers
We implemented prompt-based and system-level guardrails to restrict AI outputs strictly to the PNM domain. Security features include dynamic data masking, in-house model hosting, and reverse proxy access control, ensuring zero data exposure. Langsmith observability provides complete monitoring and governance of all AI interactions for compliance and transparency.
- Faster fault resolution through automated anomaly detection and one-click remediation suggestions.
- Eliminated generic AI responses, ensuring all outputs are aligned with cable network standards.
- Zero external data exposure via in-house AI hosting and masking strategies.
- Scalable architecture ready for expansion to additional AI agents for other operational areas.
Ksolves’ AI-powered PNM platform showcases how domain-tuned Generative AI and agentic automation can transform telecom operations. With real-time anomaly detection, secure RAG-based support, and scalable architecture, the solution empowers technicians with immediate, context-aware insights, streamlining network diagnostics and improving customer satisfaction.
Enhance Your Telecom Operations with AI-Powered Network Reliability.
