MYSAE
The MYSAE product layer for privacy-safe workforce signals.
Worker-controlled check-ins, privacy gates, aggregate leader dashboards, action records, and optional Vault evidence depth without exposing raw private worker content.
One public product flow, four protected boundaries
The four protected boundaries are worker check-in flow, identity separation, privacy threshold and suppression, and aggregate leader visibility / Vault separation where applicable.
Workers complete a short check-in. MYSAE separates signal from identity context, applies privacy gates, and prepares aggregate workforce signals for leader views.
Worker view vs leader view comparison
Workers see a simple check-in and privacy cues. Leaders see aggregate trends and suppressed states. Organisation views see governance and evidence context only where privacy conditions allow it.
No raw worker rows, raw check-ins, tokens, private Vault records, customer data, or sub-threshold slices appear in leader view.
Threshold and AI clarity
If a crew is too small, leaders see not enough data instead of a breakdown. If privacy conditions are met, leaders see aggregate trends, not worker rows.
AI only works from aggregated, thresholded cohort context where enabled. AI does not access identity, raw check-ins, worker rows, check-in tokens, private Vault records, customer data, or sub-threshold slices.
Designed for procurement, integration, and privacy review before scale
MYSAE can be scoped for pilots, multi-site rollout, reporting hierarchy, integration review, security review, and evidence governance.
Vault Plus or Enterprise evidence depth is added only where protected records, permissioning, or governance depth is needed.
Compact trust boundary
Public demo only. No raw check-ins, private Vault records, tokens, customer records, or sub-threshold slices exposed.