The questions we get asked
Straight answers about the platform, how it is rolled out and how it is secured. If yours is missing, write to us.
Do we have to replace our current tools?
No. The graph plugs into what you already have (ETL, CSV, data lakes, BI tools) and adds a layer of meaning on top. Nothing to migrate.
Can we start with a single building block?
Yes, and it is the recommended way: structure a narrow scope with GraphForge, then add exploration, the copilot and the KPIs when you are ready.
How is this different from a relational database?
A graph treats relationships as first-class objects: you name them, walk them and query them. Where a relational schema hides them inside joins, the graph makes them explicit.
How long before we see a first result?
The first modelled scope is visible in weeks rather than quarters, which is the point of starting small.
Do you need technical skills to model?
No. The ontology editor is visual and code-free: business teams model, data teams connect the sources.
Who owns the project on our side?
Usually a business and data pair. We work with them on the first scope, then your teams become self-sufficient.
Where is our data hosted?
It depends on your constraints: hosting is discussed during scoping, including for the most sensitive environments.
How are access rights managed?
Rules are defined once at concept level, in the ontology, and then apply to exploration, KPIs, copilot answers and exports alike.
Can AI answers be audited?
Yes: every answer shows the path it took through the graph, and access is logged.
Question not answered here?
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