Relari

Thank you Qdrant for being a great partner! David and Thierry did a great job walking through how to use Relari for end-to-end RAG evaluation and optimization. This case study also includes a sneak peek to our latest feature: Auto Prompt Optimization (APO). Many companies using APO have seen significant improvement in prompt performance. Ping me if you'd like to give it a try! #RAG #PromptEngineering #LLM #EnterpriseAI

How do you measure the performance of a RAG app? We’ve been working with Relari to make that easier. In our latest blog, Thierry Damiba, David Myriel, and Yi Zhang show practical steps for: ✅ Adjusting 𝐓𝐨𝐩-𝐊 𝐩𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬 to return the right number of results ✅ Using 𝐀𝐮𝐭𝐨 𝐏𝐫𝐨𝐦𝐩𝐭 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 to refine chatbot responses ✅ Evaluating it all using the GitLab legal policies dataset as an example With this workflow, you can run fast, iterative tests, experiment with hybrid search, and access detailed metrics like precision, recall, and rank-based evaluations. Check out the full blog for code and implementation 👉 https://lnkd.in/dsw3BQrx

Building an LLM application? It's time to rethink how you approach evaluation. - "We’re too early for evaluation.” - "We don’t have enough resources to do this now." - "😅, I just eyeball it.” Too often I hear these comments in my conversation with LLM developers. But these are missed opportunities. Evaluation isn't just about avoiding mistakes—it’s a powerful tool to differentiate your product from the noise. We see it over and over again with our customers: AI teams/startups that embrace evaluation from the start don’t just catch errors—they learn, iterate, and build better products, faster. It’s not a luxury; it’s a necessity. “You can’t improve what you can’t measure.” A strong evaluation framework is more than a safety net; it’s your secret weapon to winning in a crowded market. So, what’s holding you back from running evaluation? Curious about how strong evaluation can elevate your product? Let’s discuss! #LLMEvaluation #EnterpriseAI #RAG #LLMAgents

Discover how Vanta's AI team launched multiple successful LLM products, leveraging Relari's data-driven evaluation and improvement toolkit!

Excited to collaborate with Qdrant on this webinar next week. We will walk through some of the best practices to build production-grade RAG systems.

Another exciting opportunity to learn advanced RAG testing methods! Yi Zhang from Relari will be joining Thierry Damiba to discuss how synthetic data can be used to create production-ready RAG applications. This is a great opportunity for data scientists, ML engineers and developers working on GenAI to calibrate and improve their projects. The webinar will be followed up by a Q&A session, so bring your best questions and topics to discuss. See you on July 31st!

"Is RAG all you need?" - check out this talk by Sara Zanzottera at EuroPython, where she highlighted our integration with Haystack, the popular LLM framework by deepset.   Some highlights: 1️⃣ How RAG works and how it fails 2️⃣ ChatGPT (without RAG) vs Perplexity (with RAG) 3️⃣ How to use continuous-eval by Relari to evaluate RAG performance objectively   Check out the presentation, slides, and example code in this link: https://lnkd.in/erqypcAr

Are you getting the most out of your LLMs and RAGs? In the latest episode of the ODSC Ai X Podcast, join Pasquale Antonante, PhD, Co-founder and CTO at Relari AI, to discuss innovative evaluation methods for LLM and RAG applications. Get ready to explore: ✅ Measuring LLM Performance: The different ways to evaluate LLM pipelines  ✅ Understanding RAGs: Key evaluation metrics and how to measure precision, recall, faithfulness, relevance, and correctness ✅ The Human in the Loop: The role human evaluation plays in assessing the quality of generated text ✅ The Role of Synthetic Data: Using synthetic data based evaluation for LLMs and RAG and leveraging synthetic data for LLM fine-tuning 🎧 Listen Now:  https://linktr.ee/odsc #AI #LargeLanguageModels #RAG  #Podcast #ODSC

I was inspired by the SF community breakfasts hosted by Inferless and started organizing "GenAI Developer Breakfast" at Harvard Square while we are in Boston. I find these intimate small-group conversations super fun and insightful. Thank you, everyone, for coming today and exchanging learnings on building LLM-powered applications across a variety of industries! Jon Duffy, Babak Kia, Chris Tierney, Axel Solano, umamaheswar E., Tyce Herrman, Gabor Soter

Earlier this month, I had a great conversation with Sheamus from Open Data Science Conference (ODSC). We discussed RAG evaluation, the challenges of evaluating complex pipelines and how to effectively leverage synthetic-data.  I also shared some of our latest learnings from working with top AI teams deploying LLMs in production. Our chat is out now in the latest Ai X podcast episode! Check it out here: 🍏 Apple Podcast (https://hubs.li/Q02Cvbdx0) 🎧 SoundCloud (https://hubs.li/Q02CvbXF0) 🎵 Spotify (https://hubs.li/Q02Cv9Wb0) 📦 Castbox (https://hubs.li/Q02CvcmW0) Reach out to me if you have any questions or want to learn more about our work at Relari. #AI #MachineLearning #DataScience #ODSC #AiX #RAG #Evaluation #LLM #GenAI #SyntheticData