Julep AI is an open-source platform designed to help data science teams quickly build, iterate on, and deploy multi-step AI workflows. With Julep, you can create scalable, durable, and long-running AI pipelines using agents, tasks, and tools. The platform's YAML-based configuration simplifies complex AI processes and ensures production-ready workflows. It supports rapid prototyping, modular design, and seamless integration with existing systems, making it ideal for handling millions of concurrent users while providing full visibility into AI operations.

Agentic Workflow is a declarative framework enabling developers to define complex AI workflows by chaining multiple LLM-based agents, each with customizable roles, prompts, and execution logic. It provides built-in support for task orchestration, state management, error handling, and plugin integrations, allowing seamless interaction between agents and external tools. The library uses Python and YAML-based configurations to abstract agent definitions, supports asynchronous execution flows, and offers extensibility through custom connectors and plugins. As an open-source project, it includes detailed examples, templates, and documentation to help teams accelerate development and maintain complex AI agent ecosystems.