Self-building knowledge graphs that keep AI agents and teams working from traceable facts.
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1 / 2Overview
What is yggy?
The AI knowledge graph that builds itself.
yggy is a knowledge graph that builds itself, aimed at developers and AI teams.
Instead of throwing text chunks at a model, yggy turns your documents and connected systems into a real knowledge graph with no schema to design and no pipeline to run. Every fact keeps its source, duplicates merge themselves (and merges can be undone), and the graph stays up to date automatically as sources change. One graph then serves everyone: your team in the app, your code through the API, your agents through MCP. The ontology is standards-compatible (RDF-based, OWL 2 RL export), and hosting is in the EU with GDPR compliance, SSO, scoped API tokens and audit logs.
Pricing starts free: the Free plan is €0 forever (up to 10 members, monthly credits, 1 GB storage). Pro is €20 per member per month, and Enterprise is custom. Agents connect via API key or MCP and do not take seats.
Platforms and languages
yggy Availability
Platforms
Languages
Capabilities
yggy Key Features
Automatic graph building
Turns cluttered documents, tables and connected systems into typed entities and relationships with no schema to design and no pipeline to run.
Self-updating graphs
The graph syncs automatically when sources change, keeping earlier states as history.
Traceable facts
Every fact keeps its source document and date; ambiguous or conflicting cases go to a human review queue and merges can be undone.
Developer-first access
Connect through MCP, CLI, REST API and SDKs; works with Claude Code, Codex, Cursor and other agents. Hosted in the EU with GDPR compliance.
Best for
Who uses yggy?
Developers and AI teams that need reliable knowledge for agents
Turn company documents and systems into a self-updating knowledge graph agents can query.
Plans and access
yggy Pricing
Freemium
Free €0 plan; Pro €20/member/mo; Enterprise custom.
Common questions
yggy FAQs
What is knowledge graph as a service?
A hosted knowledge graph you can query without building your own pipelines; yggy builds and continuously updates the graph for people and agents to use.
Is a knowledge graph better than RAG?
They solve different problems. RAG retrieves similar text chunks; GraphRAG first builds an entity-relationship graph and answers from it. yggy builds the graph, then chat and agents answer from it.
How much does GraphRAG cost?
There is no fixed price; it depends on corpus size, model choice and data change frequency. yggy keeps indexing costs predictable by reading structured files and prose differently.
Do agents need seats?
No. Agents connect via API key or MCP; only humans are billed per seat. Reads are unlimited and overage is billed per call.
What happens if a payment fails?
Pro stays active during a 14-day retry period, and admins are notified by email and on the billing page.
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