Audience
AI developers, researchers, and organizations seeking to optimize task automation through advanced multi-agent collaboration frameworks
About OWL
OWL (Optimized Workforce Learning) is an advanced framework designed for multi-agent collaboration in real-world task automation. Built on the CAMEL-AI platform, OWL aims to revolutionize AI agent interactions, enabling more efficient, natural, and resilient task automation across various industries. It achieves high performance, ranking #1 among open-source frameworks on the GAIA benchmark with a score of 58.18. OWL features real-time information sharing, dynamic task management, and integration with various tools and platforms, supporting collaborative AI agents in completing complex tasks.
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CAMEL-AI is the first LLM-based multi-agent framework and an open-source community dedicated to exploring the scaling laws of agents. It enables the creation of customizable agents using modular components tailored for specific tasks, facilitating the development of multi-agent systems that address challenges in autonomous cooperation. The framework serves as a generic infrastructure for various applications, including task automation, data generation, and world simulations. By studying agents on a large scale, CAMEL-AI.org aims to gain valuable insights into their behaviors, capabilities, and potential risks. The community emphasizes rigorous research, balancing urgency with patience, and encourages contributions that enhance infrastructure, improve documentation, and implement research ideas. The platform offers components such as models, tools, memory, and prompts to empower agents, and supports integrations with various external tools and services.
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Pricing
Starting Price:
Free
Pricing Details:
Open source
Free Version:
Free Version available.
Integrations
Company Information
CAMEL-AI
Founded: 2023
github.com/camel-ai/owl
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Product Details
Platforms Supported
Windows
Mac
Linux
On-Premises
Training
Documentation
