- Have multiple steps,
- Make decisions based on model outputs,
- Spawn parallel branches,
- Use lots of tools, and
- Run for a long time.
Imagine you want to build an AI agent that can do more than just answer simple questions — it needs to handle complex tasks, remember past interactions, and maybe even use other tools or APIs.
Core Features
Persistent AI Agents
Create agents that maintain context and remember information across multiple interactions. Agents can learn from past conversations and apply that knowledge to future tasks.
Stateful Sessions
Keep track of conversation history and context across multiple interactions. Sessions can be paused, resumed, and maintain their state indefinitely.
Multi-Step Tasks
Build complex workflows with decision-making capabilities, loops, and conditional logic. Tasks can be as simple or as sophisticated as needed.
Task Management
Handle long-running tasks that can run indefinitely. Tasks are automatically managed, with built-in support for retries and error handling.
Advanced Capabilities
Built-in Tools
Built-in Tools
Self-Healing
Self-Healing
RAG Support
RAG Support
Easy Integration
Easy Integration
Exploring the Documentation
Depending on your use case, here are different ways to explore our documentation:For AI Developers
Start with the Quick Start guide, then dive into Core Concepts and Task Management to build AI-powered applications.
For Enterprise Solutions
Focus on Architecture Deep Dive, Security Features, and Integration Guides to understand enterprise-grade deployment.
For Researchers & Experimenters
Explore our Model Configuration, RAG Implementation, and Advanced Features sections to experiment with AI capabilities.
For System Integrators
Check out our API Reference, SDK Documentation, and Integration Tutorials to connect Julep with existing systems.