White Papers & Research
Sprinklenet publishes the thinking behind Knowledge Spaces: how to run AI on sensitive data without giving up control of it. These papers are written for the security, compliance, and standards audiences who need the architecture, not the pitch.
White Papers
Knowledge Spaces
Running AI on Regulated Data
How Knowledge Spaces keeps regulated data, including PHI, inside a governed boundary and sends the model only the minimum it needs. Written for CISOs and compliance teams who have to answer for where the data goes.
Knowledge Spaces White Paper 2026
The foundational overview of Knowledge Spaces: what the control layer is, how it governs AI access to your data, and where it fits in your stack.
Public Research
Contributing to AI Standards
AI Agent Identity and Authorization
Sprinklenet’s public comment to NIST NCCoE on how AI agents should prove identity and earn authorization. Submitted March 2026 as part of the open standards process, not marketing collateral.
More research is in progress.
If there is a topic you want covered, tell us at [email protected].
