Retrieval-augmented generation: considerations for GenAI platform vendors targeting telecoms operators

26 July 2024 | Research

Joseph Attwood

Strategy report | PPTX and PDF (7 slides) | AI and Data Platforms


"Operators hope to apply RAG to a broad range of use cases, but most operators are ill-equipped with the skills and tools needed to develop these applications."

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Using retrieval-augmented generation (RAG) to ground the outputs of large language models (LLMs) is proving to be extremely useful but operators face challenges with implementing and optimising RAG-based applications. GenAI platforms vendors must aim to address these challenges and help operators to accelerate time to value for their RAG use cases.

Information included in this report

  • Analysis of the challenges faced by operators when implementing and optimising RAG-based applications
  • Insights into how GenAI platform providers can support operators to overcome challenges relating to RAG
  • Strategies for GenAI platform providers that want to enhance the value proposition of their platforms for operators developing RAG-based applications

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Author

Joseph Attwood

Analyst