Quotient AI (acquired by Databricks)

“Another challenge with autonomous AI systems is maintaining reliable performance in production environments over time, as agents often encounter unfamiliar scenarios that degrade performance. To address that issue, Databricks has acquired Quotient AI, a startup specializing in evaluation and reinforcement learning for AI agents. The company’s technology helps evaluate agent behavior, continuously measuring output quality and detecting regressions before they cause production failures. Quotient AI’s founders previously worked on improving the quality of GitHub Copilot, giving them deep expertise in evaluating AI coding systems.”

🚀 Databricks just made an exciting move in the AI agents space 🤖 Databricks has acquired Quotient AI, built by the engineers who helped drive quality for GitHub Copilot, to supercharge how we evaluate and improve AI agents to become experts in the real world. Quotient analyses full agent traces in production to spot hallucinations, reasoning issues, and bad tool use, then turns that into structured eval data and rewards for continuous learning. What this means: 🧠 AI agents that get better over time, not just deployed and forgotten 📈 Continuous, built-in evaluation and reinforcement learning on the Databricks platform ✅ More trustworthy AI for business-critical workflows where reliability really matters This will power: 💬 Genie - chat with your data, now with deeper quality monitoring behind the scenes 🛠️ Genie Code - an autonomous AI agent to help data teams build and run data/ML workflows more reliably 🧱 Agent Bricks - easier to build and scale high-quality agents on your own data, with evals baked in As AI agents take on more responsibility in the enterprise, robust evaluation isn’t optional anymore - it’s the foundation of safe, scalable AI. I am excited to see Databricks double down on making agents not just powerful, but measurable, debuggable, and continuously improving ✨ Learn more here: https://lnkd.in/gsEjrzeC

Databricks is acquiring Quotient AI to strengthen the agent evaluation and reinforcement learning capabilities in Genie, Genie Code, and Agent Bricks so customers get more reliable AI agents in production. Databricks already provides powerful tools for evaluating and improving AI agents. With Quotient, we're strengthening these capabilities across our platform with a continuous evaluation and improvement layer that monitors agent behavior in production, catches issues like hallucinations and broken reasoning before users do, and uses those signals to continuously improve performance over time. We're excited to welcome the Quotient AI team to Databricks as we continue building the most reliable platform for developing, deploying, and improving agentic systems at scale! https://lnkd.in/eNAV64TY

Congratulations to Julia Neagu, Freddie Vargus, and the entire Quotient AI team on their successful acquisition by Databricks! Great companies acquire great companies. Very excited for this combination and to see what comes next from Databricks. https://lnkd.in/gQrbTyrx

Databricks is acquiring Quotient AI to strengthen the agent evaluation and reinforcement learning capabilities in Genie, Genie Code, and Agent Bricks so customers get more reliable AI agents in production. Databricks already provides powerful tools for evaluating and improving AI agents. With Quotient, we're strengthening these capabilities across our platform with a continuous evaluation and improvement layer that monitors agent behavior in production, catches issues like hallucinations and broken reasoning before users do, and uses those signals to continuously improve performance over time. We're excited to welcome the Quotient AI team to Databricks as we continue building the most reliable platform for developing, deploying, and improving agentic systems at scale! https://lnkd.in/eNAV64TY

Quotient is joining Databricks! Freddie Vargus and myself started Quotient AI in 2023 with a dream and a hunch that the next era of AI will be unlocked by systems that can measure, evaluate, and improve AI in the real world. Over the past couple of years, we partnered with companies ranging from AI-first startups to Fortune 500 enterprises. They used Quotient to monitor AI systems in production, ensure their agents met strict enterprise policies, and reinforcement fine-tune agents to consistently achieve double-digit performance gains. We built it all at the bleeding edge, with a small team that started in Boston, Massachusetts. Joining Databricks gives us the scale and resources to take this much, much further. Very grateful to our team, investors, customers, and everyone who supported us along the way. We couldn’t be more excited for what’s next. Onwards!

When you talk about infra software and what's ahead...it's always 🙌 to team up with Will Lehmann from Step Function! We brought our respective communities together to talk about infrastructure software in 2025, what's ahead for 2026 at all layers of the stack, and a little bit of everything in between! Thanks to... -Jack O'Brien from Subconscious -Julia Neagu from Quotient AI -Pete Cheslock from Red Hat ...for dropping a ton of knowledge. What'd we learn? -All eyes on the foundation models: what pricing efficiencies will they deliver in the coming quarters? How much are they subsidizing token costs now? -Large language models are super powerful, but the nuance is in the specific "vertical" use cases and specialization is key to delivering value in the enterprise -It's very early in the world of agents. The infrastructure opportunities will expand as their adoption increases. If there's an "agent" for everything, that's orders of magnitudes larger than any employee footprint -Monitoring, reinforcement learning, and context are focus areas (and very competitive!) for new startups racing to deliver value -Shoutout to Claude Code as the current preferred weapon of choice for early stage startups! Great to see builders from the MGMT Boston Operators Club and the other builders from around Boston who joined us last night! See you in Feb!

We are pleased to share the recordings from the 2025 CODE@MIT event! Videos include plenary talks from: Iavor Bojinov – Associate Professor, Harvard Business School Emil Palikot – Assistant Professor, Northeastern University Ramesh Johari – Professor, Management Science and Engineering, Stanford University Hongseok Namkoong – Assistant Professor, Columbia University Yan Chen – Daniel Kahneman Collegiate Professor of Information, University of Michigan Sherry Jueyu Wu – Assistant Professor, UCLA Plus the Fireside Chat with panelists: Sean Taylor – Technical Staff, OpenAI Abhishek Nagaraj – Associate Professor, University of California, Berkeley, Haas School of Business Julia Neagu – CEO & Co-founder, Quotient AI Siddharth Suri – Senior Principal Researcher, Microsoft Research Moderated by David Holtz – Professor, Columbia University and CODE@MIT Organizer And the Practitioners Panel with panelists: Brent Cohn – Data Science and Machine Learning Manager, Stripe Thu Le – Senior Staff Data Scientist, Lyft Guillaume Saint-Jacques – Director, Roblox Bilal Zia – Head of Data Science & Analytics, Duolingo Moderated by Dean Eckles – Professor, MIT Sloan School of Management and CODE@MIT Organizer Thank you to everyone who joined us and we look forward to seeing you next fall! Access videos: https://lnkd.in/evBkTBcP