Participant context
Frames follow-up, cohort support, and workshop interpretation without turning identity into public analysis input.
Example Correlation Engine
The audit is the input.
The engine is the interpretation layer behind the workshop audit. It connects participant context, tool behavior, data concerns, cost pressure, and support needs into visible tags, routing choices, evidence needs, and next actions. Nothing here saves participant data.
Audit to engine
Every recommendation should point back to what was entered.
The point is not to flatten different truths into one answer. The engine preserves context first, then shows how the platform reached a recommendation.
Platform reality
Shows what people actually rely on, which privacy controls are known, and where enterprise or local alternatives matter.
Risk and trust pattern
Connects lived concern to routing rules, including what stays in the shared workspace or local knowledge layer.
Action readiness
Turns the audit into a participant action list, organization guidance, and six-month go/no-go/adjust evidence.
Select example inputs
Nothing is selected until you choose the example evidence to compare.
Contextual correlation trail
No sources selected. Choose one or more inputs to see the interpretation and action trail.
Names lived experience, context, risk, and judgment.
Help summarize, compare, draft, and research when content is safe to route out.
Work against local knowledge, sensitive materials, and coalition memory.
Ontology v0
The categories being woven.
Tools used, account type, settings checked, costs, and data categories.
Real use cases, privacy assumptions, support needs, and workshop notes.
Race bias, surveillance, privacy, ownership, misinformation, lock-in, and trust.
Participant guidance, organization next steps, evidence needs, and launch guardrails.
Use the Sweetgrass Workspace or shared Drive for the controlled pilot.
Define folders, access, retention, consent language, and what cannot leave that space.
Move approved patterns into a local knowledge layer and route AI use by sensitivity.
At six months, use evidence to go, stop, or adjust the Sweetgrass platform path.