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Important: Register on the event website is required for admission.

Welcome to the AI meetup in Austin. Join us for deep dive tech talks on AI, GenAI, LLMs and Agents, hands-on experiences on code labs, workshops, and networking with speakers and fellow developers.

Tech Talk: The Convergence of Real-Time Data and AI
Speaker: Garrett Raska (Redpanda)
Abstract: The world of AI has its origins in batch processing of large data sets. In more recent years it has had to accelerate to faster and faster development cycles — feedback from real-time usage, RAG and MCP architectures for live data lookups. What's driving the convergence of AI and real-time data? And how can you ride the wave?

Tech Talk: GraphRAG in Action
Speaker: Shishir Tewari (Procore)
Abstract: Discover how GraphRAG transforms chaotic, disjointed corporate data into actionable natural language insights. This session explores a three-phase architecture offline entity resolution, Neo4j knowledge graphs, and local LLMs that eliminates hallucinations and securely bridges the gap between raw data and business intelligence.

Topics/Speakers:
Check the event website for speakers and topics.
If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors:
We are actively seeking sponsors to support AI developers community. Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 8,000+ AI developers in Austin and 500K+ worldwide.

Venue Sponsors:
Thank you to Station Austin for sponsoring Austin AI Developers Group. Station Austin is the center of gravity for entrepreneurs in Texas. They bring together the best entrepreneurs in the state and connect them with their first investors, employees, mentors, and customers. To sign up for a Station Austin membership, click here.

Related topics

Events in Austin, TX
Artificial Intelligence
Deep Learning
Machine Learning
Natural Language Processing
Big Data

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