VibeGraph · Knowledge graph data layers
VibeGraph builds living knowledge graphs of a vertical. Every entity, every relationship, every market signal, reconciled into one structured layer your team and your AI agents query over app, API, and MCP.
What we do
We map the messy reality of a vertical into canonical entities and the typed relationships between them, so the whole market reads as one queryable structure.
Your agents reach the graph over MCP and REST and answer from verified, structured data instead of scraping pages and guessing.
The graph is refreshed from primary sources on a schedule, so it reflects the market as it is today, with every claim traceable to where it came from.
How it works
We pull the scattered, unstructured sources of a niche: listings, menus, filings, reviews, signals.
We dedupe and reconcile everything into one canonical record per entity, with AI handling the same-or-different judgment calls.
We connect entities with a typed relationship grammar: who sells what, who supplies whom, who competes with whom, who sits near whom.
You query the result through a web app, a REST API, or an MCP endpoint your agents call directly.
Instances
Who works from it
AI agents call the graph for clean, structured ground truth instead of scraping the open web and hallucinating.
Find, score, and prioritize accounts in a vertical with data that is already reconciled and current.
Map an entire vertical in one place, with a source attached to every entity and relationship.
If your vertical has scattered, messy, valuable data, it can become a graph your team and your agents work from every day. Let’s scope it.
Email hendrik@vibelab.be