Databricks Acquires Quotient AI to Help Enterprises Evaluate and Fix AI Agents
The team behind Quotient includes engineers who previously worked on improving quality for GitHub Copilot, one of the most widely used AI coding assistants.
Topics
Databricks has acquired Quotient AI, a startup focused on evaluating and improving the performance of AI agents once they are deployed in real-world systems.
The deal comes as enterprises move AI agents beyond experiments and pilots into everyday business workflows, a shift that has exposed a new problem: how to measure whether these systems are actually working reliably in production.
AI agents are not single models but complex systems made up of multiple components, including models, memory, tools and reasoning steps. When something goes wrong, identifying the root cause can be difficult. Without clear evaluation tools, companies often struggle to debug failures or improve performance, slowing down deployments.
Quotient AI was built to address this gap. The startup’s platform analyzes the full execution traces of AI agents running in production environments to identify issues such as hallucinations, reasoning mistakes, or incorrect tool usage. It then converts those signals into structured evaluation datasets and reinforcement learning signals that can help improve agent performance over time.
The team behind Quotient includes engineers who previously worked on improving quality for GitHub Copilot, one of the most widely used AI coding assistants.
Alongside the acquisition, Databricks also introduced Genie Code, an autonomous AI agent designed to handle complex data-related tasks such as building data pipelines, debugging system failures, shipping dashboards and maintaining production systems.
The company said internal testing on real-world data science tasks showed the system more than doubled the success rate of leading coding agents.
Genie Code expands on Databricks’ existing AI agent, Genie, which allows employees to interact with enterprise data through conversational queries. While Genie focuses on helping knowledge workers retrieve insights from data, Genie Code is aimed at data engineers, data scientists, and analytics teams by automating the technical work required to move projects from idea to production.
The company says the new system is built around what it describes as “agentic data work”, where AI systems plan multi-step tasks, write and validate production-grade code, and manage ongoing operations while humans oversee key decisions.
“Software development has shifted from code-assistance to full agentic engineering in the past six months,” said Ali Ghodsi, co-founder and CEO of Databricks. “Genie Code brings this revolution to data teams. We’re moving from a world where data professionals are assisted by AI to one where AI agents do the work, guided by humans. We are calling this Agentic Data Work. It will fundamentally change how enterprises make decisions.”
Quotient’s technology will be integrated into Databricks’ platform to add a continuous evaluation layer for these agents. The integration is expected to help organizations monitor agent behavior, detect failures early, and use real-world feedback to improve system performance over time.
Databricks did not disclose the financial terms of the deal.
