In this session, we will show how to leverage Aiven for Dragonfly and Aiven for AI. First, we’ll discuss how to increase your throughput and reduce memory usage by 25% compared to open-source Redis. Then explore scalability, efficiency, and advanced capabilities ideal for caching, gaming leaderboards, messaging, AI applications, and more. After that, we’ll jump into Aiven’s latest AI use cases and cover.

In this workshop we’ll work together to generate embeddings for podcast transcriptions and load that data into OpenSearch. Then we’ll search the documents using similarity search and use those results to improve our responses from an LLM (Large Language Model). Along the way we’ll explain the Retrieval Augmented Generation (RAG) pattern and show how it’s possible to try different LLMs without having to completely rewrite your code.

Learn how to identify a data collection strategy that best fits your environment and implement best practices around data collection using Sumo Logic.