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🚀 EDDI 6.4.0

Per-user workspaces, Connections for governed outbound access, and a Red Hat certified UBI 10 image Release notes

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The Enterprise
AI Orchestrator

The open-source platform for deploying governed, multi-agent AI systems: self-hosted, configuration-driven, and compliance-ready. Now in v6.

EDDI AI Orchestrator

The Problem

Enterprise AI orchestration is fragmented and painful. Teams are stuck in a broken lifecycle:

The Prototype Trap

Teams prototype with Flowise, n8n, or scripts, then rewrite everything from scratch for production. Visual prototypes are discarded entirely.

Boilerplate Fatigue

Using AI libraries means building REST controllers, auth layers, and state management from scratch. Every prompt tweak requires redeployment.

BPMN Friction

Forcing non-deterministic AI agents into deterministic Camunda/Temporal workflows creates severe impedance mismatches and brittle architectures.

The Solution

EDDI is a deployable AI orchestration platform, not a library. Visual management, config-as-code, and enterprise security, out of the box:

01

Configuration-as-Code

Agent logic, pipelines, and tool definitions are JSON configurations, not compiled code. Prompt engineers iterate instantly via the React UI or REST API, without redeployment.

02

84 MCP Tools

EDDI exposes its capabilities via the Model Context Protocol, enabling Claude Desktop to interact. Agents can also consume external MCP tools.

03

Security-First

No eval(), no escapes. Vault integration, URL validation, and cryptographic audit trails are architectural foundations.

04

Observability

Every pipeline step is logged with an immutable audit trail: tokens, cost, timing, tool calls. Full CQRS telemetry ledger.

05

Enterprise Concurrency

Built on an enterprise-grade runtime with millions of lightweight threads for I/O-bound LLM workloads. No event loop blocking, no single-threaded bottlenecks.

06

Multi-Agent Orchestration

Intent-based agent discovery, managed conversations, and group collaboration: agents deliberate in seven styles, vote, co-edit shared work products, and give humans a seat at the table.

"The engine is strict so the AI can be creative."
Project Philosophy
UNIDO Recognition

UNIDO Trusted Partner for Industrial AI

LABS.AI has been selected by the United Nations Industrial Development Organization (UNIDO) as a Trusted Partner for Industrial AI for the Global South.

Learn more about the partnership →

Trusted & Certified

Red Hat Certified Container Certified image, published in the Red Hat catalog
Apache 2.0 Licensed 100% open-source & enterprise-ready
20,000+ Tests · 0 Failures Rigorous CI/CD & >90% code coverage
OpenSSF Gold Highest tier of Linux Foundation security & quality certification
OpenSSF Best Practices
Docker Hub Hundreds of thousands of production pulls
Docker Pulls
CI Passing · CodeQL Clean Automated builds, security scanning & code analysis
CICodeQL

Built on Proven Technology

Java 25 Enterprise runtime
Quarkus Cloud-native, fast
LangChain4j Multi-provider LLM support
MongoDB Document store
PostgreSQL Relational store
Docker Container-ready
Kubernetes Orchestration
OpenShift Red Hat certified

Next Steps

Frequently Asked Questions

What is EDDI?

EDDI is an open-source, enterprise-grade AI orchestration platform. It enables teams to build, configure, and deploy AI-powered agents using JSON configuration rather than compiled code. EDDI provides a complete platform with a production-ready React management UI (the EDDI Manager), built-in REST APIs, conversation state management, security (OIDC/Keycloak), immutable audit trails, and 84 MCP tools, all deployable via Docker or Kubernetes.

How is EDDI different from AI libraries and frameworks?

AI libraries like LangChain, Spring AI, and LangChain4j give you building blocks, but you still need to build REST controllers, authentication, conversation state management, audit logging, and management UIs yourself. EDDI is a deployable middleware platform, not a library. It provides all of this out of the box, ready to deploy via Docker.

Is EDDI production-ready for enterprise use?

Yes. EDDI is built on an enterprise-grade runtime with lightweight virtual threads for massive I/O-bound concurrency. It supports MongoDB and PostgreSQL, includes built-in OIDC/Keycloak authentication and per-user workspaces with resource sharing, provides immutable cryptographic audit trails for compliance (including EU AI Act), and scales horizontally via NATS JetStream.

What is the Model Context Protocol (MCP)?

The Model Context Protocol (MCP) is an open standard that allows AI assistants like Claude Desktop, IDE plugins, and custom clients to interact with external tools programmatically. EDDI exposes 84 MCP tools spanning conversation management, agent administration, group discussions, human approvals, setup automation, schedule management, and diagnostics.

Can EDDI replace Flowise or n8n for production workloads?

EDDI serves a similar visual-building purpose but with enterprise-grade architecture. Unlike Flowise and n8n, EDDI uses no eval() or code blocks, runs millions of lightweight virtual threads for enterprise-grade concurrency, supports OIDC/Keycloak authentication, and stores data in MongoDB or PostgreSQL. It is designed for regulated industries.

Is EDDI related to "Eddie AI" or other products named "Eddy"?

No. EDDI (by LABS.AI) is a self-hosted enterprise AI agent orchestration platform built on Java/Quarkus. It is not related to consumer video editing tools, HR software, chatbot builders, or other products that share similar names. EDDI is designed for enterprise teams deploying governed, multi-agent AI systems in production.

How does EDDI compare to cloud AI platforms like AWS Bedrock or Azure AI Studio?

Cloud AI platforms offer managed infrastructure but create vendor lock-in. EDDI runs anywhere Docker runs, on-premises, any cloud, or in air-gapped environments. It supports 12 LLM providers and any OpenAI-compatible endpoint, providing full model portability and data sovereignty. See our detailed comparison.

Does EDDI work with Open WebUI and other OpenAI-compatible clients?

Yes. EDDI includes an OpenAI-compatible /v1 API that presents deployed agents as models, so Open WebUI, the openai SDK, LangChain, and LiteLLM can talk to them directly. It supports streaming and token usage reporting, keeps each chat in its own conversation, and the agent's approval gates still apply. The API is disabled by default and has its own API-key authentication.

Can multiple users and teams share one EDDI deployment?

Yes. Per-user workspaces give every agent and configuration an owner, a personal or team space mapped to Keycloak groups, and explicit sharing at use, view, edit, or own level. Connections let agents call external systems with an organization-wide key, a service account, or each user's own OAuth account, so an agent can be held to what the person using it may do. Workspaces are opt-in, and existing resources are backfilled so nothing disappears when you turn them on.