Architecture / AIGIS resources
Enterprise AI needs more than a chat surface. It needs a runtime path that can enforce permissions before work reaches a model or execution surface.
Executive read
Governance belongs in the request path.
The runtime should separate model choice from permission enforcement.
Evidence should be produced for included and excluded context.
Salesforce is the strongest first runtime proof path for AIGIS.
Analysis
The runtime maps identity, routes intent, checks permissions, strips inaccessible fields, selects the execution path, and records provenance.
That is different from a policy document or dashboard that only observes after the fact.
Model routing should happen after governance has shaped the allowed context.
That keeps governance stable even as model quality, price, and availability change.
Resource packet
Evidence packet
Capture user context, system of record, enforcement tier, stripped fields, model route, response, hash marker, and fallback notes.
Salesforce is the production proof path. ServiceNow and SAP are design-partner co-development paths with asymmetric enforcement that must be disclosed in diligence.
Keep reading
Architecture
A practical architecture for enterprise AI governance middleware: identity resolution, live record checks, field stripping, model routing, write approvals, and audit provenance.
Architecture
Why enterprises should keep permission enforcement stable while model routing remains flexible.
Architecture
Why enterprise AI governance should check permissions and remove inaccessible context before any model call.