You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
🚀 MassGen is an open-source multi-agent scaling system that runs in your terminal, autonomously orchestrating frontier models and agents to collaborate, reason, and produce high-quality results. | Join us on Discord: discord.massgen.ai
Mimir - Fully open and customizable memory bank with semantic vector search capabilities for locally indexed files (Code Intelligence) and stored memories that are shared across sessions and chat contexts allowing worker agent to learn from errors in past runs. Includes Drag and Drop multi-agent orchestration
Fractalic: Build and version-control AI systems using Markdown & YAML. Combine LLM calls, shell commands, and modular workflows in a human-readable format. Docker-first installation, Git-native tracking.
AI that thinks in layers, not just tokens. Intent-based processing through 15 dimensional analysis. Anti-manipulation through understanding context. Built with Rust + Go.
🐙 Meta-AI Orchestrator unifies multiple LLMs with dynamic routing, RAG search, and DAG pipelines for enterprise AI workloads across providers, with observability and QA.
An AI Email Intelligence Platform Real-time email intelligence with multi-provider AI fallback, semantic search, OAuth integration. Handles incremental sync and streaming with 70% cold start reduction.
An extensible multi-agent Research Assistant that uses Gemini-powered subagents (Researcher, Analyst, Formatter) with ArXiv and custom tools to search, analyze, format, and persist academic findings, and can run locally (Flask) or be deployed to Vertex AI.
Gen AI Framework and Orchestration Engine. GenAI Goos.Flock emerges as a groundbreaking framework and orchestration engine, designed to seamlessly integrate and manage complex AI workflows. This innovative platform is the ultimate solution for organizations seeking to harness the full potential of Generative AI, Large Language Models (LLMs)