RAG, LLMs & RAGAS: Making AI Answers Make Sense - 4th Houston Meet


Details
GenAI is powerful. But how do you know it’s right?
As developers and testers work with Retrieval-Augmented Generation (RAG) systems and LLM-powered applications, one big question keeps popping up: how do we evaluate the quality of these AI responses—at scale, and with context? At our 4th Houston Meetup, we’re diving deep into RAGAS, an open-source framework that is reshaping how teams assess and improve their AI applications with clarity, structure, and precision.
Date: July 17, 2025
Time: 6:00 PM – 8:00 PM CDT
Venue: Improving Office
Maps Link: https://maps.app.goo.gl/iNMML6Rg1kMm8F6m7
Talk Title: RAG and LLM Evaluation with RAGAS
Retrieval-Augmented Generation (RAG) is driving the next generation of GenAI systems—but evaluating them remains a complex challenge. In this talk, Prabhat Singh and Alessandro De La Garza from Slalom Consulting will introduce RAGAS, an open-source evaluation framework that helps teams automate the assessment of RAG systems and LLM-generated content.
You’ll discover how RAGAS goes beyond traditional NLP metrics to measure accuracy, relevance, and completeness, offering a structured workflow to improve the quality and reliability of GenAI applications.
Whether you're building RAG-based pipelines or testing LLM outputs, this session will equip you with tools and insights to make evaluation measurable—and meaningful.
Key Takeaways:
- Understand what RAGAS is and how it works
- Learn how to evaluate GenAI responses with actionable metrics
- Discover techniques for automating LLM and RAG evaluations
- Gain real-world insights into AI quality engineering workflows
Speakers:
Prabhat Singh – Architect, Quality Engineering, Slalom Consulting
With over 20 years of experience across domains, Prabhat is passionate about building future-ready QA strategies. He’s currently exploring LLMs, RAG, and GenAI testing—and helping the QE community do the same.
Alessandro De La Garza – Engineer, Quality Engineering, Slalom Consulting
Alessandro has worked in industries ranging from energy to telecom, with a strong focus on data-rich projects. He’s now on a mission to demystify AI-accelerated engineering for fellow testers and developers.
Why Attend?
- You want to evaluate GenAI systems like a pro
- You work with LLMs, RAG pipelines, or AI-powered applications
- You’re exploring AI testing tools and frameworks
- You want to connect with others on the same path
About The Test Tribe
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Test smarter. Evaluate deeper. Join us in Houston!

RAG, LLMs & RAGAS: Making AI Answers Make Sense - 4th Houston Meet