RAG and Voice Agent Applications

From Resumes to Conversations: Building Production RAG Systems for Voice-Driven Talent Matching

Discover how to build sophisticated RAG systems that go beyond simple document search to power intelligent voice agents. This session explores real-world challenges and solutions in creating production-grade RAG architectures for complex domains like talent recruitment.

What You’ll Learn:

Multi-stage RAG architecture: Moving from basic vector similarity to intelligent, domain-aware search with hard constraints, semantic matching, and business logic validation and graph databases

Voice-first data processing: Transforming conversational interviews into structured, searchable knowledge using advanced chunking strategies and multi-modal embeddings

Hybrid search patterns: Combining vector similarity, keyword matching, and structured data filtering for precision at scale

Production challenges: Handling 180k+ profiles with 8 types of embeddings, managing costs, and optimizing for real-time performance

Speaker: Tony Xavier

Resources:
Get Started with Aura – https://bit.ly/3LOLrjh
Deployment Center – https://bit.ly/4jOelM3
Ground AI Systems and Agents with Neo4j – https://bit.ly/4oVsnyb

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