Elastic x Apache Kafka® Meetup

IMPORTANT: PLEASE RSVP @ https://www.meetup.com/elastic-kansas-city-user-group/events/312356340/?slug=elastic-kansas-city-user-group&eventId=312356340

🎤 Talk 1: Elastic Agent Builder & Context Engineering
Justin Higdon from Elastic, will walk through how to design and build intelligent agents using Elastic Agent Builder, with a focus on context engineering and real-world patterns.

🎤 Talk 2: Building a Real-Time AI Chatbot with Confluent Flink, Elastic, and OpenAI
Daniel Green from Confluent will demonstrate how to combine streaming data with search and AI to build a real-time chatbot using Confluent Flink, Elastic, and OpenAI.

📅 Date and Time:
Wednesday, January 28th from 5:30-7:30 pm

📍Location:
Goodwill's AI Lab - 800 E. 18th St. Kansas City, MO 64108
Enter throughKeystone CoLab, proceed to the back double-doors, and into the AI Lab. The AI Lab is situated in the hallway behind Keystone's CoLab.

🚗 Parking:
- 5x reserved spots in parking lot (says Reserved)
- Street parking along 18th
- Street parking along Campbell
- Street parking along Charlotte
- parking area at corner of Campbell & 18th Street

🗓 Agenda:

• 5:30 pm: Doors open; say hi, grab a seat, and eat some food.
• 6:00 pm: Agent Builder & Context Engineering - Justin Higdon (Principal Solutions Architect at Elastic)
• 6:30 pm: Building a Real-time AI Chatbot with Confluent Flink, Elastic and OpenAI - Daniel Green (Customer Success Technical Architect at Confluent)
• 7:00-7:30 pm: Networking, refreshments & pizza

Talk Abstracts:
Building a Real-time AI Chatbot with Confluent Flink, Elastic and OpenAI - Daniel Green (Customer Success Technical Architect at Confluent)
Abstract: How to build a real-time AI chatbot using Apache Flink, Confluent’s data streaming platform, Elastic, and OpenAI. The presentation covers the need for a modern streaming architecture for generative AI. The example provided outlines the use of a Kafka-based data streaming platform to provide a scalable, decoupled backbone for continuously ingesting, processing, and enriching enterprise data to power AI applications. The application is decomposed into four key stages — data augmentation, inference, workflows, and post‑processing — and show how Confluent and Flink enable real-time contextual knowledge bases, low-latency prompt enrichment, and composable multi-step reasoning. Elastic serves as the vector database and semantic search engine, combining hybrid (text + vector) retrieval, filtering, and relevance ranking to ground LLM responses in business data. Finally, an end-to-end AI chatbot architecture is demonstrated along with review of common production use cases, such as customer service, semantic search, recommendations, and task automation, illustrating how Confluent and Elastic together unlock real-time, governed, and AI-ready data for next-generation applications.
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If you are interested in speaking at/hosting a meetup, please email community@confluent.io