Data and AI company Databricks launches Agent Bricks: A new approach to building AI Agents

Data and Artificial Intelligence (AI) company, Databricks have today introduced Agent Bricks, a new, automated way to create high-performing AI agents tailored to your business. Just provide a high-level description of the agent’s task, and connect your enterprise data — Agent Bricks handles the rest. Agent Bricks are optimized for common industry use cases, including structured information extraction, reliable knowledge assistance, custom text transformation and orchestrated multi-agent systems. Agent Bricks is available starting today in Beta.

Databricks made the announcement at their Data + AI Summit 2025 in San Francisco.

Agent Bricks uses novel research techniques developed by Mosaic AI Research to automatically generate domain-specific synthetic data and task-aware benchmarks. Based on these benchmarks, it automatically optimizes for cost and quality, saving enterprises from the tedious trial-and-error of current approaches. Now, teams can achieve production-level accuracy and cost efficiency right from the start. Built-in governance and enterprise controls let teams move from concept to production quickly, without stitching together separate tools.

Why a New Approach to Agents is Needed
Quality and cost are the main barriers keeping most agentic experiments from reaching production. Without high-quality evaluation, most teams are left to judge agents by gut checks, leading to inconsistent quality and costly experiments that are impossible to scale. The complexity of AI, with new models and techniques emerging constantly, only adds to the challenge. Customers need domain-specific, repeatable, objective and continuous evaluations to ship AI agents that they can trust and afford. And they need to be able to leverage the latest technology without breaking the bank and reskilling the team. Databricks built Agent Bricks to deliver on these important customer requirements that are currently unmet by the industry.

Agent Bricks: Instantly Build and Optimize AI Agents with Your Enterprise Data
First, Agent Bricks automatically generates the task-specific evaluations and LLM judges to assess quality. Next, synthetic data is created that looks like the customer’s data to substantially supplement the agent’s learning. Last, Agent Bricks searches across the full gamut of optimization techniques to refine the agent. At the end of this automated workflow, the customer simply needs to select the iteration that matches the balance of quality and cost that they want the agent to achieve. The result: a production-grade, domain-specific AI agent that delivers consistent, intelligent output — fast.

Agent Bricks addresses several common customer use cases across key industries:

• Information Extraction Agent turns documents, like emails, PDFs and reports into structured fields like names, dates and product details. Retail organizations can easily pull product details, prices and descriptions from supplier PDFs, even if the documents are complex or formatted differently.
• Knowledge Assistant Agent solves the issue of getting vague or flat-out wrong answers from chatbots, with fast, accurate answers grounded in your enterprise data. Manufacturing organizations can empower technicians to get instant, cited answers from SOPs and maintenance manuals without needing to dig through binders.
• Multi-Agent Supervisor enables you to build multi-agent systems that seamlessly stitch together agents across Genie spaces, other LLM agents and tools such as MCP. Financial Services organizations can orchestrate multiple agents to handle intent detection, document retrieval, and compliance checks, creating complete, personalized responses for advisors and clients.
• Custom LLM Agent transforms text for custom tasks such as content generation or custom chat, optimized for your industry. Marketing teams can build customized agents to generate marketing copy, blogs or press releases that respect their organization’s brand.

“Agent Bricks is a whole new way of building and deploying AI agents that can reason on your data,” said Ali Ghodsi, CEO and Co-Founder of Databricks. “For the first time, businesses can go from idea to production-grade AI on their own data with speed and confidence, with control over quality and cost tradeoffs. No manual tuning, no guesswork and all the security and governance Databricks has to offer. It’s the breakthrough that finally makes enterprise AI agents both practical and powerful.”