Agentic RAG In Telecom
From Retrieval to Autonomous Intelligence
LLMs have moved beyond experimentation, but naive deployments are no longer sufficient for production of telecom use cases. Organizations must now make deliberate architectural choices between RAG and fine-tuning, while recognizing that real value lies in operational impact - not just better user interactions. As systems evolve toward agentic autonomy, the challenge shifts from generating answers to executing reliable, governed actions, making control, cost, and accountability central to any deployment strategy.
Key Takeaways
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Naive LLMs are not enough anymore
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Fine-tuning vs RAG and what route to take
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The true cost of agentic systems
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Autonomy requires governance
This is the first session in a two-part live webinar series. Register for the second webinar, planned for June 4th, Time Series Forecasting for Capacity Management
Webinar Speakers
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Mohammad ShaheenHead of AI Solutions at Polystar
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Mohamed TarekSenior AI Engineer at Polystar
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Guy RedmillModerator