TelcoAI: A new approach to 3GPP documentation

The 3rd Generation Partnership Project (3GPP) produces complex technical specifications essential to global telecommunications. However, their hierarchical structure, dense formatting, and multi-modal content make processing these documents difficult.

TelcoAI is an agentic, multi-modal Retrieval-Augmented Generation (RAG) system specifically developed for 3GPP documentation. It introduces advanced techniques such as section-aware chunking, structured query planning, metadata-guided retrieval, and multi-modal fusion of text and diagrams.

Performance and results

Evaluated on multiple benchmarks, including expert-curated queries, TelcoAI achieved 87% recall, 83% claim recall, and 92% faithfulness. This represents a 16% improvement over state-of-the-art baselines. The results demonstrate the effectiveness of agentic and multi-modal reasoning in technical document understanding, offering practical solutions for research and engineering in the telecommunications sector.

For those evaluating on-premise deployments of similar solutions, AI-RADAR offers analytical frameworks on /llm-onpremise to assess the trade-offs between different architectures and implementation options.