Curious about how to systematically evaluate and improve the trustworthiness of your LLM applications? 🤔 Check out how Cleanlab's Trustworthy Language Models (TLM) integrates with #MLflow! TLM analyzes both prompts and responses to flag potentially untrustworthy outputs-no

📢 Reminder: the next #MLflow Community Meetup is THIS Wednesday, May 21 @ 4PM PT! 👉 Register now: lu.ma/mlflow521 What to Expect: 🔹 𝐌𝐋𝐟𝐥𝐨𝐰 𝟑 𝐌𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐟𝐨𝐫 𝐎𝐒𝐒 𝐔𝐬𝐞𝐫𝐬: Learn how to smoothly upgrade to MLflow 3.0 and leverage new

🚀 Catch this session at #DataAISummit! Learn how Petrobras leveraged #MLflow to transform their #MLOps—automating model validation, accelerating deployment from days to hours, and achieving robust governance and reproducibility with @Databricks Asset Bundles and #UnityCatalog.

MLflow Prompt Registry is a powerful tool that streamlines prompt engineering and management. You can version, track, and reuse prompts seamlessly across your organization - helping maintain consistency and making collaboration easier for your teams. ✅ 🎥 Check out this

🎥 The recording for "Building Reliable AI Systems with MLflow" is now available! Watch the full session ➡️ maven.com/p/af7339 In this webinar, Maria Vechtomova, Başak Tuğçe Eskili, and Daniel Liden showcase a practical MLflow use case, including how to: ✅ Use MLflow

Did you know you can now try out MLflow for free using a managed, hosted option? We’ve heard from a lot of you that getting started with MLOps tools easily is key, especially as more engineers dive into #GenAI. To make it simpler to explore MLflow for GenAI, there’s a hosted

🚀 Advanced Tracing & Evaluation of Generative AI Agents with LangChain, Amazon SageMaker AI, and #MLflow Developing and deploying generative AI agents requires robust experimentation, detailed evaluation, and strong governance. With LangChain's LangGraph, Amazon SageMaker

🔥 Deal extended! Get 50% OFF your #DataAISummit ticket - now through Mon, June 3! Join the global data & AI community in SF, June 9–12, for the world’s largest conference on data, analytics, & AI. Dive into: 🔹700+ sessions (MLflow, GenAI, & more) 🔹Demos & real-world use

🚀 What’s the real advantage of using MLflow in a managed setting vs. self-hosting? Check out this clip from last week’s MLflow Community Meetup, where Mikhail Rozhkov, Technical Product Manager at Nebius, explains how using MLflow in a managed setting (like Nebius AI Cloud) gets

#DennysPick 🌟 If you’re building GenAI applications with DSPy and want full observability, seamless debugging, and true MLOps best practices, this session is a must-see at #DataAISummit! I’m excited to recommend “Streamlining DSPy Development: Track, Debug, and Deploy With

Have you heard the news? MLflow now supports tracking for DSPy optimization workflows—just like it does for #PyTorch training! With DSPy, you can automatically optimize your #LLM prompts using powerful optimizers, and now #MLflow is the first and only framework to bring full

📣 The wait is over! Data+AI Summit kicks off this week. 🎉 Ready to supercharge your machine learning workflow? Join us for “MLflow 3.0: AI and MLOps on @Databricks” and see how MLflow 3.0 streamlines everything from experiment tracking to deploying ML and generative AI models.

🎉 We're excited to see the global data and AI community come together in San Francisco this week! If you’re passionate about open source, make sure to check out the MLflow sessions. You’ll get to explore MLflow 3.0, learn about MLOps best practices, and discover how open

📣 After months of collaboration across the open source community, we’re thrilled to announce the release of 𝗠𝗟𝗳𝗹𝗼𝘄 𝟯.𝟬! 🎉 𝘞𝘩𝘺 𝘵𝘩𝘪𝘴 𝘮𝘢𝘵𝘵𝘦𝘳𝘴: GenAI has changed the game, introducing complex execution flows, subjective output quality, and new challenges for

Have You Heard the News? MLflow 3 is Here! 🎉 𝗠𝗟𝗳𝗹𝗼𝘄 𝟯 is now available to everyone, marking the biggest evolution in open-source MLOps history and transforming how millions of developers build, deploy, and monitor AI applications. While earlier versions focused on

Join us for the next 𝗠𝗟𝗳𝗹𝗼𝘄 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗠𝗲𝗲𝘁𝘂𝗽 on Wednesday, June 25! 🎉 This month’s meetup features a deep dive into how Amazon SageMaker integrates with MLflow to streamline the machine learning lifecycle at scale. 🚀 Discover how MLflow is natively