E.D.D.I
✨Production-grade, config-driven multi-agent orchestration middleware for conversational AI, featuring group debates, intelligent routing, MCP/A2A protocol interoperability, and enterprise security compliance.
Production-grade, config-driven multi-agent orchestration middleware for conversational AI, featuring group debates, intelligent routing, MCP/A2A protocol interoperability, and enterprise security compliance.
The Enterprise-Grade Production-Ready Multi-Agent Orchestration Framework.
The agent engineering platform for building context-aware reasoning applications.
A low-level orchestration framework and runtime for building, managing, and deploying long-running, stateful AI Agents.
A Kubernetes-based AI Agent runtime platform released by McKinsey, codifying patterns for deploying, orchestrating, and evaluating agentic resources via CRDs, providing production-grade infrastructure for multi-agent systems. Currently in Technical Preview.
An open-source framework simplifying LLM integration in Java apps, supporting RAG, tool calling, and agents. Provides a unified API for major models like OpenAI and Gemini, with deep integration for Spring Boot and Quarkus.
A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Open-source self-hosted AI Agent platform featuring voice-driven workflows, episodic memory, multi-view orchestration, and enterprise-grade integrations. Users can drive complex automation via natural language while keeping data entirely in local environments.
PentAGI is a fully autonomous AI Agents system capable of performing complex penetration testing tasks in isolated Docker container environments. It features multi-agent collaboration, supports multiple LLM providers, integrates knowledge graphs for experience accumulation, includes 20+ professional security tools, and generates comprehensive security assessment reports.
An AI-powered data science team of agents that automates data loading, cleaning, feature engineering, EDA, visualization, and machine learning modeling (H2O + MLflow) through specialized agent collaboration, featuring a Streamlit visual pipeline studio to perform common data science tasks 10X faster.
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