Scenario rail
Choose the story
Python guard
Drop NORNR into an existing Python agent
Wrap an existing client, send business context with the intent, and let the control layer decide whether the call should move spend now.
Guided scenario lab
Step through the decision layer before money moves.
Walk through MCP-controlled local agents, browser checkout guard, replay-ready traces, finance-close workflows, and proof-backed agent-to-agent escrow in a single controlled NORNR environment.
Scenario stage
What NORNR sees
Walkthrough
Step 1 of 3
Control surfaces
Artifacts
What will land in NORNR
Operator reading
Why this matters
Next surface
Continue the flow
Open the control room to see the decision inbox, replay viewer and evidence chain rendered against a live workspace.