yggy

yggy is a knowledge graph platform that automatically builds and updates graphs from enterprise data sources.

yggy is a knowledge graph platform designed for developers and AI teams to automate the recurring work of data extraction, modeling, entity matching, and updates. It runs on top of existing enterprise systems, reading ERP exports, QMS records, PIM data, SharePoint, OneDrive, and Google Drive without replacing current infrastructure. Domain experts define meaning and handle unclear cases, while every answer cites its original document and date. The platform integrates with AI agents via Model Context Protocol (MCP), CLI, and API, supporting tools like Claude Code, Codex, and Cursor. It is available via managed EU cloud, private cloud, or on-premise deployment, and maintains complete historical states for auditing and traceability.

yggy at a glance

Best for: Researcher, Product manager
Runs on: Web, CLI, API, Self-hosted
Pricing: Freemium
Released: October 2026
Category: AI research tool
Website: yggy.tech

Key features

Automatic knowledge graph building
Source and time citation for every fact
Entity matching across multiple systems
MCP, CLI, and API integration
Historical state tracking
Human-in-the-loop exception handling
EU cloud, private cloud, or on-prem deployment

Use it for

Resolving customer complaints with traceable data
Tracking product specification changes across documents
Managing master data and fitment
Retrieving product knowledge and contract obligations

Alternatives to yggy

WeKnora — Combines RAG, multi-step agents, and automatic Wiki generation in one platform.
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GraphRAG — Enhances LLM reasoning over private data using knowledge graph structures.
Jonex — Provides traceable, agent-ready knowledge from diverse enterprise data sources.
LightRAG — It uses a dual-layer architecture to reduce LLM calls and retrieval latency.
Hyper-Extract — Extracts complex knowledge graphs and hypergraphs from documents with one command.
SAG — It combines model routing, knowledge management, and agent orchestration in private.
UltraRAG — Build complex RAG workflows using modular MCP components and YAML configuration.
edgextract — Runs entirely in the browser with local model execution and strict data privacy.
LLM Wiki Research — Compiles parallel agent research into source-backed markdown knowledge bases.
Keryx — Compensates verified creators directly in USDC for cited sources
Lune — Accesses trusted knowledge from top conference papers for AI agents.

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