Exo is an open-source AI agent framework designed to help developers build conversational bots that can integrate with external tools, maintain memory, and manage complex workflows. It offers modular architecture with plugin support, TypeScript compatibility, and easy deployment. With Exo, users can rapidly prototype digital assistants, customer support bots, or automation agents by defining tools, actions, and conversation logic in a declarative manner.
Exo is an open-source AI agent framework designed to help developers build conversational bots that can integrate with external tools, maintain memory, and manage complex workflows. It offers modular architecture with plugin support, TypeScript compatibility, and easy deployment. With Exo, users can rapidly prototype digital assistants, customer support bots, or automation agents by defining tools, actions, and conversation logic in a declarative manner.
Exo is a developer-centric framework enabling the creation of AI-driven agents capable of communicating with users, invoking external APIs, and preserving conversational context. At its core, Exo uses TypeScript definitions to describe tools, memory layers, and dialogue management. Users can register custom actions for tasks like data retrieval, scheduling, or API orchestration. The framework automatically handles prompt templates, message routing, and error handling. Exo’s memory module can store and recall user-specific information across sessions. Developers deploy agents in Node.js or serverless environments with minimal configuration. Exo also supports middleware for logging, authentication, and metrics. Its modular design ensures components can be reused across multiple agents, accelerating development and reducing redundancy.
Who will use Exo?
Software developers
AI researchers
Startups building chatbots
Enterprises needing automation
How to use the Exo?
Step1: Install Exo via npm or yarn (npm install @exo/core)
Step2: Define Tools and Actions using TypeScript interfaces
Step3: Configure the Agent with memory and tool settings
Step4: Write conversation handlers and prompt templates
Step5: Initialize and run the agent in a Node.js environment