Models may be global. Execution authority must remain sovereign.

Nations investing in AI infrastructure need more than compute. They need governed execution β€” where institutional policy controls what autonomous systems may do, and every consequential action leaves a verifiable evidence trail.

Strategic positioning

Why PDDS?

Classical distributed systems focused on networks, timing, and failures while assuming deterministic participants. PDDS extends distributed systems theory to environments where participants may be adaptive, autonomous, probabilistic, or otherwise non-deterministic.

Research Foundations

Research Foundations

The OpenKedge research program develops the theory, assurance primitives, and implementation patterns behind PDDS and sovereign AI infrastructure.

Risk scenario

A direct AI action can become an outage.

The demo shows why PDDS needs an execution control plane: an AI system proposes a cloud change, and OpenKedge keeps the action inside policy, context, and evidence boundaries.

AI Attempt

Shut Down Cloud Capacity

Intent received
Context snapshot recorded
Policy evaluated
Execution contract denied or constrained
Evidence chain created
Replay available
OpenKedge Evidence Record (Before Action)
Click "Run Scenario" to start...

PDDS defines the paradigm.
OpenKedge makes it operational.

Explore the research program, inspect the reference implementation, and evaluate sovereign AI deployment patterns that preserve execution authority.