Corellis is an agent framework that scales OpenClaw from a single AI assistant into a coordinated fleet of agents with shared knowledge, collective memory, and distributed goals.
The tool addresses the challenge of managing multiple AI agents that need to work together effectively. Rather than running isolated assistants, Corellis enables agents to share information, maintain collective state, and coordinate toward common objectives. The framework is built on OpenClaw and designed for self-hosted deployment using Docker, allowing teams to run their multi-agent systems on their own infrastructure.
Corellis suits organizations that need multiple AI agents to function as a cohesive team rather than independently. It is particularly relevant for projects where agents must access shared knowledge bases, maintain synchronized state across the fleet, and work toward distributed goals that require coordination. The self-hosted Docker-based approach makes it suitable for teams with infrastructure control requirements or data privacy concerns.
The project shows active development with regular commits across its codebase. The repository maintains a clear focus on the multi-agent coordination problem, with consistent updates to core functionality. Documentation and configuration examples are kept current alongside code changes. The project demonstrates sustained attention to both the framework's core capabilities and its operational deployment model.
