local_only_v1
v1.2- L-1Inference must run on GW_Edge local.allow
- L-2No cloud egress for this data class.deny
- L-3Outbound DNS limited to allowlist.allow
- L-4Receipt sealed on each material step.allow
Running inference locally reduces some exposure. It does not, on its own, create trust. A local workflow still needs policy enforcement, identity, human approval, egress controls, outcome grading, and receipts that prove what ran, what was touched, why it was allowed, and what changed.
What local trust requires
local_only_v1
v1.2Egress controls have to be enforced and proven.
Brand binding is a policy property, independent of where the model runs.
Approval lives on the workflow.
Receipts are what make a local run reviewable.
Local model + GW Slate sealed against unauthorized changes.
Outbound traffic policy is enforced and tested.
Short-lived identity rotated for each run.
Human approval when policy requires, even on local runs.
Grades produced locally without leaking content.
Receipts signed on your own hardware, verifiable by the parties you share them with.
A controller they command: custom rails over the estate they already run, policy gates on every route, and Actuality Receipts that prove the work. Human-at-the-Control stays in the architecture, so engineering authority scales with the estate.
Canonical pieces on this rail. Each magazine URL is the home; Substack is distribution.
We run one workflow on a sealed local stack with egress fences and a receipt packet.