Whether you’re building AI agents to drive your most critical business processes, or creating retrieval-augmented generation (RAG) apps for targeted use cases, accuracy is a critical ingredient in the success of your apps. We’ve helped the world’s largest companies as well as emerging startups quickly get up to speed and into production with applications that meet their AI ambitions.
There are four pillars of AI accuracy: Data preparation, data ingestion and embedding; retrieval; monitoring and evaluation; and reranking and optimization. Next week, we’ll dive into each and show you what accuracy in production looks like.
We’ll share expert tips and code that makes it easy to understand the recipe required to exceed your accuracy goals: from when and how to use graph RAG, fine tuning, chunking and reranking, to what contextual data you need to get the best results.
Here are the core areas we’ll dive into next week (April 28):
- Monday - Data prep, ingestion, and embedding
- Tuesday - Retrieval
- Wednesday - Monitoring and evaluation
- Thursday - Reranking and optimization
- Friday - Accuracy in production
Each day delivers practical guidance—hands-on tutorials, real-world examples, and expert tips—that breaks down a key part of the accuracy stack. You’ll learn how to avoid hallucinations, reduce drift, and build AI that gets it right, every time.
Visit our Accuracy Week page and follow along on LinkedIn and X to get the latest daily drops and learn how to build accurate AI apps. We hope you tune in next week—we think the knowledge we’ll share will go a long way to improving your production generative AI applications.
Get ready for one of next week’s highlights: register for the April 30 livestream, “Build More Accurate AI Apps with Langflow and Arize,” when we'll be joined by Rich Young, Partner Solutions Architect at Arize.
