# Upcoming Webinar: Production-ready Distributed Inference with Ray…

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## Email content

Hi there,

In this session, Marwan Sarieddine, AI Engineer at Anyscale, will walk through:

Building Ray Serve applications with deployments, composition, and load-aware request routing

Deploying and scaling LLM endpoints with Ray Serve LLM on engines like vLLM and SGLang

Optimizing the inference engine with the KV cache, paged attention, prefix caching, and continuous batching

Scaling frontier models with KV-cache-aware routing, prefill/decode disaggregation, and wide expert parallelism for mixture-of-experts (MoE) models

Deploying Custom LLMs on Anyscale and Integrating Them with Agentic Platforms (Claude Code, Cursor, Codex)

Comparing costs across self-hosted GPUs, subscriptions, and token-based API billing.

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Advance your AI Platform with Anyscale.

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Anyscale, Inc., 600 Harrison St, San Francisco, CA 94107, USA

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