Deerflow provides a visual interface where users can assemble AI workflows from modular components—input processors, LLM or model executors, conditional logic, and output handlers. Out of the box connectors allow you to pull data from databases, APIs, or document stores, then pass results through one or more AI models in sequence. Built-in tools handle logging, error recovery, and metric tracking. Once configured, workflows can be tested interactively and deployed as REST endpoints or event-driven triggers. A dashboard gives real-time insights, version history, alerts, and team collaboration features, making it simple to iterate, scale, and maintain AI agents in production.

AI Foundry offers a comprehensive no-code environment to construct custom AI agents that autonomously perform complex tasks. Users create workflows using a visual builder, chaining language models, REST APIs, database connectors and memory stores. Each agent can be configured with event triggers, scheduling options, execution logs and collaboration features. Test agents interactively before deploying them as API endpoints or embedding them into applications. Built-in monitoring and analytics provide real-time insights into performance and usage. AI Foundry scales horizontally, supports role-based access controls for teams, and ensures secure data handling, enabling businesses and developers to automate processes such as customer support automation, research assistance, report generation or lead qualification quickly and reliably.