Author: Arun Sathyamurthy, Oracle Database Engineering Team
Oracle AI Database recently introduced the Private Agent Factory to help build agents. A clear definition of agents is – turn data into action – and the Agent Factory takes trusted business data in the Oracle Database to turn it into trusted action, by integrating data with a agent builder that includes tools like MCP, connectors like REST APIs, and access to any LLM. The Agent Factory can run in a customer tenancy on any IaaS of a cloud provider, or run on-premises to keep all data and access to LLMs private. I decided to use the Agent Factory for a work project and this blog shares my experience.
The tech industry is currently obsessed with AI agents. Terms like autonomy, reasoning, orchestration, and tool use show up everywhere. But anyone who has tried to build an agent for a real enterprise use case knows how quickly the complexity adds up.
That’s exactly why my recent experience with Oracle AI Database Private Agent Factory stood out.
One realization came almost immediately: you don’t build everything from scratch. You assemble it.
Traditionally, building an AI agent that can reliably interact with enterprise systems is a heavy lift. It often means writing complex orchestration logic, managing API routing, handling dynamic tool selection, and debugging execution flows. You spend a lot of time building backend plumbing before you ever see real business value.
Oracle AI Database Private Agent Factory’s approach genuinely surprised me. Instead of wrestling with glue code, I was connecting building blocks. Using the platform’s visual builder, I defined the agent’s goal, attached the required tools through an MCP server, and layered in custom instructions and reasoning steps. I didn’t need to worry about how tools were discovered or how context moved between them. That abstraction made iteration fast and intuitive, and it kept the focus on outcomes.
What stood out just as much was how naturally the platform fits into an enterprise environment.
The agent runs securely within the organization’s own tenancy and connects only to trusted data sources and approved systems. Security and compliance are part of the design, not something added later. Even getting started felt easier than expected. Instead of beginning with a blank and intimidating slate, the platform provides strong foundations that help you move quickly from an idea to a working agent. The path from concept to something functional is noticeably shorter.
The Private Agent Factory is available with the Oracle AI Database, and you can experience it with a hands-on-lab here. The front screen shows the pre-built agents, custom templates available, and an agent builder flow that lets you build any agent in a canvas.
Overall, working with Oracle AI Database Private Agent Factory felt fundamentally different. It felt less like engineering infrastructure and more like designing a structured, secure, and truly enterprise-ready workflow.
Below is the experience of visually creating agentic flows with the Private Agent Factory.
You can try out the Agent Factory on the OCI Marketplace at https://marketplace.oracle.com/app/agentfactory