Multiple sessions can work on the same graph.
Independent conversations and users can operate concurrently over shared knowledge without turning the graph into separate copies.
WeKnowDB is a graph-native knowledge system for applications and agents that need more than document retrieval. Relationships, evidence, permissions and time remain part of the knowledge structure itself, so different users and sessions can work against the same connected context.
Applications interact with it through conversational sessions and APIs. Results can remain graph-shaped or continue into structured outputs such as DataFrames and charts when the task calls for them.
Explore the capabilities behind collaborative knowledge, provenance, structured data and graph-native operations.
Independent conversations and users can operate concurrently over shared knowledge without turning the graph into separate copies.
Different users can work against the same knowledge structure while only reaching the branches available to them.
Attachments can be processed into the graph instead of remaining detached from the knowledge they contribute.
Sources and reliability can travel with the facts they support, so answers do not lose where they came from.
Temporal provenance lets the system reason over knowledge that changes instead of flattening every update into a single present state.
Queries can continue into tabular and chart-oriented outputs when the answer is better represented as structured data than prose.
API interactions can sit alongside knowledge operations when an application needs live data or an external action.
The graph can remain common while sessions carry their own conversational and operational context.
Separate knowledge spaces can be connected through higher-level graph structures without collapsing them into one monolith.
We can walk through the architecture, deployment model and current product surface.