Ruflo

Ruflo (by Cognitum.One) is an agent meta-harness for deploying AI-powered multi-agent swarms. It enables developers to coordinate autonomous workflows, build conversational AI systems, and manage complex multi-player interactions. The platform features adaptive memory, self-learning intelligence, RAG (Retrieval-Augmented Generation) integration, and native support for models like Claude Code, Codex, and Hermes. Designed for teams building production-grade agentic applications, Ruflo abstracts away orchestration complexity so you can focus on logic and behavior. Ruflo’s architecture revolves around a meta-harness that manages agent lifecycles, task delegation, and inter-agent communication. Adaptive memory lets agents retain context across sessions, while self-learning capabilities allow them to improve from feedback. The built-in RAG pipeline grounds responses in your own data, and the platform supports multiple LLM backends out of the box. What sets Ruflo apart is its focus on multi-agent coordination: you can spawn swarms of heterogeneous agents that work together toward a goal. It also offers a no-code-like setup for defining agent roles and workflows, though advanced users can customize via API. Pricing is currently not publicly listed; you need to contact sales for details.