Open-source, self-improving autonomous agent swarm🐇

Multi-agent orchestration for OllamaJS. Includes TTS synthesis and speech recognition for simplified testing. Connected to telegram bot which support multiple chat sessions

A lightweight framework for parallel development with multiple AI agents. Provides structured memory management, specialized agent roles, and workflow guidance to maximize development velocity. Runic enhances Large Language Models (LLMs) with Long-Term Memory (LTM) capabilities and structured knowledge retention.

A specialized CLI tool for atomically claiming "ready" issues from Beads, designed specifically for multi-agent local swarms to prevent race conditions and duplicate work.

This project implements an innovative agent-based system for automated financial transaction classification and revenue recognition.

Multi-agent orchestration for OllamaJS. Includes TTS synthesis and speech recognition for simplified testing and interaction.

Real-time blockchain fraud detection using autonomous multi-agent AI swarms. Detect fraud in <2s with 150x faster vector search (HNSW), 84.8% accuracy, and 73% cost reduction. Features ERC-1155 trust scores, MCP integration, and reflexion learning.

Command your agent swarm: Agent Mail + Beads + 28 tools + 10 commands. Full multi-agent orchestration transcending context windows and project boundaries. Continuous flow, seamless handoffs, conflict-free coordination. 32,000+ token savings vs MCP.

A React-based tool for constructing fine-tuning datasets with list and grid forms, featuring the ability to download and upload data as JSONL files. This project leverages the react-declarative library to create dynamic, interactive forms for defining user inputs, preferred outputs, and non-preferred outputs, along with associated tools

A self-learning, multi-agent AI for accelerating Alzheimer’s research. From data to insights—fully autonomous and open-source.