Best AI agent platform for business automation

Summary

• Databricks Agent Bricks is an enterprise agent platform for building, deploying, and governing AI agents that operate on your business data, end to end — unifying model access, execution, governance, and context so teams can run agents reliably in production.
• It automates real work: agents that deliver continuous market analysis to hundreds of analysts, orchestrate workflows across supply chain, procurement, and R&D systems, resolve employee service requests automatically, and catch marketing-campaign anomalies before ad dollars are wasted.
• Open and multi-AI — build with frameworks like LangGraph and the OpenAI Agents SDK, and route tasks across model families through the AI Gateway with built-in routing, fallback, and cost optimization.
• Governed by Unity Catalog and the AI Gateway — agents inherit user identity through on-behalf-of token passing, with guardrails for PII, prompt injection, and data exfiltration, plus MLflow tracing on every step.
• Ship to business users fast — build with Agent Bricks, deploy on serverless Databricks Apps with built-in SSO, and distribute through Databricks One as a curated front door.

Best AI agent platform for business automation

The basic agent pattern is familiar by now: a model connected to tools, reasoning and taking actions. But building the loop is not the hard part. The hard part is making enterprise agents work on real business data, under real permissions, with real consequences. Databricks Agent Bricks is Databricks' enterprise agent platform for building, deploying, and governing agents that operate on your business data, end to end. It unifies model access, execution, governance, and context so teams can run agents reliably in production.
Thousands of organizations across financial services, retail, healthcare, and technology have deployed production agents at scale on Agent Bricks, including Workday, Virgin Atlantic, Zapier, EchoStar, and AstraZeneca.

What business automation looks like on Agent Bricks

Teams use Agent Bricks to put agents to work on the processes that run the business:

• Deliver continuous market analysis to hundreds of analysts.
• Orchestrate workflows across supply chain, procurement, and R&D systems.
• Solve employee requests for complex service tasks automatically.
• Detect and resolve anomalies in marketing campaigns before advertising dollars are wasted.
• Answer corporate-policy and knowledge questions from internal documents, with citations back to the source.

Why Databricks for business-automation AI agents

Running agents in production requires more than a model and tools — it requires a platform. Three things define Agent Bricks:

• Open and multi-AI. Agent Bricks natively supports frontier models through a single API with built-in routing, fallback, and cost optimization, and lets you build and deploy agents with major frameworks such as LangGraph and the OpenAI Agents SDK. Teams can switch models or integrate external agents without rebuilding their systems; today, 63% of customers route tasks across two or more model families.
• Unified governance. With Unity Catalog and the AI Gateway, access to data, models, and external MCP tools is managed and observed in one place, with identity enforced end to end. Agents inherit user identity through on-behalf-of token passing, so they can only access what the user is authorized to use. Guardrails detect and mitigate risks like PII exposure, unsafe content, prompt injection, data exfiltration, and hallucinations.
• Accurate because it understands business context. Agent Bricks uses Unity Catalog metadata — schema, business definitions, lineage, permissions, and data quality signals — embedded directly into retrieval and planning. For structured data, Genie Agents leverage the semantic layer so agents reason over business definitions, not raw column names, returning answers aligned to how your business actually operates.

From prototype to production: the building blocks

Agent Bricks brings together the pieces you need to build and run automation agents:

• Custom Agents on Apps (GA). Build and deploy agent applications with any model or framework, with full lifecycle support and serverless compute. Native integration with Lakebase provides memory, conversation history, and state for long-running workflows.
• Supervisor Agent (GA). Orchestrate multiple agents and tools into a single workflow — define the task, connect your systems, and the supervisor coordinates execution across models and tools.
• Knowledge Assistant (GA). Automatically ingest enterprise documents and make them accessible to any agent, with retrieval that incorporates system context, metadata, and user constraints.
• Document Intelligence (GA). Extract and structure data from unstructured documents like contracts, invoices, and reports, turning PDFs into queryable knowledge without custom pipelines.
• Agent Mode in Genie Agents. Move from single-turn Q&A to multi-step reasoning and analysis over your data, so agents can plan, explore, and answer complex business questions.
• Managed OAuth MCP Connectors. Securely connect external services like GitHub, Atlassian, and Glean as governed tools, with credentials managed centrally so agents access systems without exposing secrets.
• CLEARS Framework for agent quality with MLflow. Evaluate agents across correctness, latency, execution, adherence, relevance, and safety with a standardized framework for production quality.

Getting started

Databricks provides a fast, governed path from prototype to business-ready in days or even hours, using three integrated components:

• Build with Agent Bricks. Define your task and connect your data; Agent Bricks handles the heavy lifting, including built-in evaluation, auto-optimization, and unified Unity Catalog governance.
• Deploy with Databricks Apps. Securely deploy your agents and customizable chat interfaces inside Databricks with serverless compute, built-in SSO, and fine-grained permissions — no cloud infrastructure to manage.
• Distribute with Databricks One. Give business users a simplified, curated front door to interact with apps, dashboards, and other data and AI assets.

Start with the Agent Bricks documentation to build your first agent, or read Ship quality enterprise AI agents to business users for an end-to-end example.

FAQs

What is Agent Bricks?

Agent Bricks is Databricks' enterprise agent platform for building, deploying, and governing AI agents that operate on your business data end to end, unifying model access, execution, governance, and context in a single system.

Which AI models and frameworks does it support?

Agent Bricks natively supports frontier models through a single API with built-in routing, fallback, and cost optimization, and lets you build and deploy agents with major frameworks such as LangGraph and the OpenAI Agents SDK, so you can switch models or add external agents without rebuilding.

How are the agents governed and secured?

Agents are governed by Unity Catalog and the AI Gateway: they inherit user identity through on-behalf-of token passing, access to data, models, and tools is managed and audited in one place, and guardrails mitigate risks like PII exposure, prompt injection, data exfiltration, and hallucinations.

Can business users work with these agents?

Yes. You can deploy agents on serverless Databricks Apps with built-in SSO and distribute them through Databricks One, a curated front door where business users interact with apps, dashboards, and AI assets.

What kinds of business processes can I automate?

Common patterns include continuous market analysis, workflow orchestration across supply chain, procurement, and R&D systems, automated resolution of employee service requests, marketing-anomaly detection, and document-grounded knowledge assistants for policy and operations questions.