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By labsai

EDDI

Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus.

Filed under Workflow & Agent Orchestration. Status: Published

GitHub stats not yet collected ; check back after the next weekly refresh.

On the maker

Use cases

Data Pipelines, Multi-Agent, Production-Grade, RAG, Tool Use / Function Calling.

  • Data PipelinesTools for building, scheduling, and monitoring batch or streaming data workflows.
  • Multi-AgentTools that coordinate two or more agents, support delegation, or implement agent-as-tool patterns.
  • Production-GradeTools proven in production at scale — not prototypes or research previews.
  • RAGTools purpose-built for retrieval-augmented generation patterns.
  • Tool Use / Function CallingTools that support OpenAI-style function calling, MCP tool use, or structured tool dispatch.

Pricing

Not yet curated

Field notes

No field notes yet.

Field notes for EDDI will land here when sources support a confident take ; synthesized from postmortems, vendor retros, dev-team blogs, deeply-engaged GitHub issues, and our own builds.

Coverage isn’t promised on every tool ; empty sections are honest. Field notes are curated, not generated from vendor copy.

Benchmarks

Scores aren’t in yet.

We’re wiring up SWE-bench, Aider Polyglot, and a custom dev-task suite next. Methodology will be public; vendor pre-notification is 48 hours.

View benchmarks

How we make money

This directory is supported by display advertising. Advertisers do not influence editorial rankings, benchmark scoring, or which tools are featured. Tools are ordered by data.

Editorial independence policy →

Last verified · 2026-05-09

We refresh GitHub stats weekly and pricing daily. Significant changes auto-banner the page; corrections to hello@vybing.dev.

Methodology