Role-based access
Planners, leaders, caregivers, clients, and family members get different views and permissions based on role and consent.
Caire handles sensitive operating data with clear permissions, traceability, data minimization, and controlled workflows. The goal is to make AI and planning audit-friendly for leadership, planners, and care teams.

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Security & compliance
Permissions, traceability, data protection, and controls.
Product trust
Caire Core connects data, recommendations, human decisions, and outcomes in a continuous learning loop where responsible users can review what changes and why.
Planners, leaders, caregivers, clients, and family members get different views and permissions based on role and consent.
Decisions, changes, publishing events, and mobile activity can be traced so the organization understands who did what.
Pages and flows show relevant information to the right role without unnecessarily spreading internal operating data.
AI recommendations remain decision support. Responsible users review, approve, and publish.
Responsible AI
AI in Caire is decision support for planning, not autonomous public authority decision-making. Recommendations should be transparent, human-in-the-loop, and reviewable after the fact.
AI creates candidates, but responsible planners review, adjust, and approve before a schedule is published.
Users should understand why a recommendation appears, which goals it affects, and what trade-offs it creates.
Recommendations, changes, and decisions are saved as operational traces for follow-up and internal control.
AI is used for planning and operational support with clear boundaries, responsibilities, and escalation paths.
Caire treats AI scheduling as operational decision support. The EU AI Act is considered through transparency, documented scope, human oversight, and risk-aware controls rather than unverified certification claims.
Customer operating data is handled for the organization’s workflow. Caire does not position public scheduling optimization as hidden generative-model training on customer records.
Constraint governance
Skills, no-overlap rules, time windows, permissions, pinned visits, and safety-critical limits are treated as rules the planning flow must respect.
Continuity, travel time, workload balance, unused hours, and preference goals are optimized transparently so planners can understand tradeoffs before publishing.
AI recommendations are transparent, planner-approved, and scoped to operational decisions. The product is designed so organizations can document controls and responsibilities.
The product is designed to help organizations explain data sources, human oversight, evaluation routines, and operational controls when they document their AI use.