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CortexON

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Basic Information

CortexON is an open-source generalized multi-agent AI system designed to automate complex research and business process workflows. The repository provides a coordinated platform of specialized agents including a Web Agent for real-time internet search and web interactions, a File Agent for file operations and data extraction, a Coder Agent for code generation and debugging, an Executor Agent to orchestrate tasks and inter-agent communication, and an API Agent to integrate external services. The project is aimed at advanced research automation, technical operations, and business process automation and is inspired by Manus and OpenAI DeepResearch. The README includes deployment guidance, required environment variables for language models, headless browsing and search, optional HashiCorp Vault integration for secrets management, and Docker instructions to run frontend, backend and an agentic browser locally.

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App URL
https://github.com/TheAgenticAI/CortexON
Github Repository
https://github.com/TheAgenticAI/CortexON/blob/main/README.md

App Details

Features
CortexON offers dynamic multi-agent orchestration that composes agent capabilities to solve user-defined objectives. It supports advanced context-aware research automation and examples such as travel planning, market analysis, educational content creation and business intelligence. The technical stack includes a PydanticAI multi-agent framework, a headless Browserbase-based Web Agent, Google SERP for search, Pydantic Logfire for logging and observability, FastAPI backend, and a React/TypeScript frontend with TailwindCSS and Shadcn. Feature highlights include seamless third-party API integration, code generation and execution via the Coder Agent, efficient file and data management, WebSocket support for live updates, Docker-based deployment, and optional HashiCorp Cloud Platform Vault for secure secrets.
Use Cases
CortexON helps researchers, developers and businesses automate multi-step workflows that would otherwise require manual coordination across tools. By combining web retrieval, file handling, code generation and execution, and API integration into orchestrated agent pipelines, it accelerates research tasks, technical operations and business processes while providing observability and secure secret handling options. The project supplies environment variable configuration for Anthropic, Browserbase and Google Custom Search, Docker-compose instructions for local deployment, and service endpoints including frontend, backend and agentic browser with API docs. Developers can extend or customize agents and integrate the platform into existing automation or research pipelines.

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