🌊 RuFlo v3.5: Enterprise AI Orchestration Platform

Multi-agent AI orchestration for Claude Code

Deploy 16 specialized agent roles + custom types in coordinated swarms with self-learning capabilities, fault-tolerant consensus, and enterprise-grade security.

Why Ruflo? Claude Flow is now Ruflo — named by Ruv, who loves Rust, flow states, and building things that feel inevitable. The "Ru" is the Ruv. The "flo" is the flow. Underneath, WASM kernels written in Rust power the policy engine, embeddings, and proof system. 6,000+ commits later, this is v3.5.

Getting into the Flow

Ruflo is a comprehensive AI agent orchestration framework that transforms Claude Code into a powerful multi-agent development platform. It enables teams to deploy, coordinate, and optimize specialized AI agents working together on complex software engineering tasks.

Self-Learning/Self-Optimizing Agent Architecture

User → Ruflo (CLI/MCP) → Router → Swarm → Agents → Memory → LLM Providers
                       ↑                          ↓
                       └──── Learning Loop ←──────┘

flowchart TB
    subgraph USER["👤 User Layer"]
        U[User]
    end

    subgraph ENTRY["🚪 Entry Layer"]
        CLI[CLI / MCP Server]
        AID[AIDefence Security]
    end

    subgraph ROUTING["🧭 Routing Layer"]
        QL[Q-Learning Router]
        MOE[MoE - 8 Experts]
        SK[Skills - 130+]
        HK[Hooks - 27]
    end

    subgraph SWARM["🐝 Swarm Coordination"]
        TOPO[Topologiesmesh/hier/ring/star]
        CONS[ConsensusRaft/BFT/Gossip]
        CLM[ClaimsHuman-Agent Coord]
    end

    subgraph AGENTS["🤖 100+ Agents"]
        AG1[coder]
        AG2[tester]
        AG3[reviewer]
        AG4[architect]
        AG5[security]
        AG6[...]
    end

    subgraph RESOURCES["📦 Resources"]
        MEM[(MemoryAgentDB)]
        PROV[ProvidersClaude/GPT/Gemini/Ollama]
        WORK[Workers - 12ultralearn/audit/optimize]
    end

    subgraph RUVECTOR["🧠 RuVector Intelligence Layer"]
        direction TB
        subgraph ROW1[" "]
            SONA[SONASelf-Optimize<0.05ms]
            EWC[EWC++No Forgetting]
            FLASH[Flash Attention2.49-7.47x]
        end
        subgraph ROW2[" "]
            HNSW[HNSWHNSW-indexed]
            RB[ReasoningBankPattern Store]
            HYP[HyperbolicPoincaré]
        end
        subgraph ROW3[" "]
            LORA[LoRA/Microlow-rank adaptation]
            QUANT[Int8 Quant3.92x memory]
            RL[9 RL AlgosQ/SARSA/PPO/DQN]
        end
    end

    subgraph LEARNING["🔄 Learning Loop"]
        L1[RETRIEVE] --> L2[JUDGE] --> L3[DISTILL] --> L4[CONSOLIDATE] --> L5[ROUTE]
    end

    U --> CLI
    CLI --> AID
    AID --> QL & MOE & SK & HK
    QL & MOE & SK & HK --> TOPO & CONS & CLM
    TOPO & CONS & CLM --> AG1 & AG2 & AG3 & AG4 & AG5 & AG6
    AG1 & AG2 & AG3 & AG4 & AG5 & AG6 --> MEM & PROV & WORK
    MEM --> SONA & EWC & FLASH
    SONA & EWC & FLASH --> HNSW & RB & HYP
    HNSW & RB & HYP --> LORA & QUANT & RL
    LORA & QUANT & RL --> L1
    L5 -.->|loops back| QL

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*[GitHub에서 전체 내용 보기](https://github.com/ruvnet/ruflo)*