Automate and optimize your scheduling with advanced AI technology. Create efficient routes, ensure staff continuity and free up valuable time for your planners.
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AI scheduling
Plan, optimize, review, publish, and learn from outcomes.
AI scheduling in home care means that CAIRE proposes optimized schedules for visits, routes, continuity, and staffing while the planner reviews and approves every operational change before publication.
Our AI-driven scheduling solution automates and optimizes home care planning with advanced algorithms that balance efficiency, continuity, and quality. The system continuously adapts to handle dynamic changes in real time.
The calendar shows routes, visits, and replanning in one workspace.
Buyer workflow
AI scheduling in Caire is a controlled workflow where the team can plan, optimize, review, publish, and learn from outcomes in one process.
Caire Core keeps the scheduling architecture, rules, visit graph, route costs, and planner decisions in one explainable model.
AI creates candidate schedules, but planners review quality, constraints, and trade-offs before publishing to mobile apps.
Outcomes, changes, delays, and planner feedback improve the next planning cycle without turning the workflow into autopilot.
Migrated prototype flows
The old platform prototype pages are folded into the AI scheduling page as workflow guidance: create a visit, optimize the candidate, review with the coordinator, bring client preferences into the plan, and compare the resulting calendar timeline.
The system gathers information about staff, care recipients, visits, skill requirements, time windows, and other relevant parameters.
Advanced algorithms analyze millions of possible scheduling options to find the optimal solution based on your specific goals and rules.
Continuous rescheduling and fine-tuning as new data comes in, such as sick leave, new visits, or other changes that affect the schedule.
The system continuously learns from past schedules, feedback, and outcomes. Over time, the optimization keeps improving as the AI adapts to your operation's specific patterns and preferences.
Anticipates needs, traffic, delays, and other factors that may affect scheduling. This allows the system to plan proactively rather than reactively, minimizing disruptions to operations.
Advanced matching between staff and care recipients based on skills, preferences, personality, and previous interactions. This improves both quality of care and job satisfaction.
Contact us for a demonstration of how our AI-driven scheduling solution can transform your operation and free up time for what truly matters - delivering the best possible care.
Contact usLäs mer om hur AI-schemaläggning fungerar tekniskt och se CaireIndex – den nya branschstandarden.
See how ai-driven scheduling can improve your operations
Automatic scheduling that optimizes for both efficiency and quality
Minimize travel time and maximize care time with optimized routes
Handle changes and unexpected situations with automatic rescheduling
Deep dive
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One unified flow: import recurring visit templates (slingor), create a schedule from a service area, run Caire Core shift layer+Caire Core routing layer optimization (~35 min), review and edit in the Bryntum workspace, then publish. Achieve 50%+ scheduling time savings, 20% travel reduction, and 75–80% staff utilization through intelligent automation.
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Stop guessing how many employees you need. CAIRE automatically discovers the optimal staffing level and shift times based on your visit demand. No placeholders, no manual configuration—just select your visits and click optimize.
System calculates exactly how many employees you need and when they should work—no more guessing or over-staffing.
CAIRE's goal is to assign 100% of visits. If more staff is needed, you'll get a clear recommendation with cost analysis.
As your caregivers use the mobile app, CAIRE learns actual travel patterns and improves accuracy automatically.
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You have 45 visits on Monday . Instead of guessing "probably need 10 employees?", you select the visits and click optimize. CAIRE discovers: 9 employees needed , creates 14 optimal shifts, assigns all visits with 78% efficiency. Saves you 1 employee + 45 minutes of planning time.
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Why slingor matter: Home care is 90% predictable patterns. The same clients need the same services at roughly the same times every week. Fighting this reality with full AI optimization creates chaos and destroys continuity. CAIRE embraces this by letting humans design stable patterns (slingor) while AI optimizes around them.
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CAIRE combines the best of both worlds: human expertise in building stable care patterns that maintain continuity, and AI optimization for handling changes and disruptions. The result is a scheduling system that respects relationships while maximizing efficiency.
Planners excel at building stable recurring patterns that maintain continuity and respect client relationships. They understand the nuances of care delivery.
AI excels at finding optimal placement for new visits, handling disruptions, and optimizing routes to minimize travel time across hundreds of visits.
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Recurring weekly patterns built by planners. These visits are locked and provide continuity. Example: Mrs. Andersson gets help from Lisa every Monday, Wednesday, Friday at 09:00.
New clients fit into existing gaps using AI optimization. Movable visits are optimized around the baseline without disrupting slingor.
Handle disruptions (sick leave, cancellations) with instant AI re-optimization. Ongoing visits stay locked, future visits become flexible.
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Home-care routing is a computationally explosive problem combining multiple NP-hard challenges: vehicle routing with time windows (VRPTW), staff scheduling, skill matching, continuity requirements, and multi-objective optimization. A single day with 240 visits and 32 caregivers creates (240!) 32 possible route permutations. Neither humans nor algorithms alone can solve this complexity—only a hybrid approach works.
Learn more about the routing science behind CAIRE's hybrid model →
Read the Caire Core shift layer+Caire Core routing layer technical docs
CAIRE's scheduling system operates as one unified flow. All steps use the same UI (Bryntum SchedulerPro + Timefold AI solver): import master data → create a schedule → optimize → review → publish → handle disruptions.
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Purpose: Define recurring care needs per client without any dates. Municipality care decisions are imported as Insets (service types) + DaySlots + InsetGroups + VisitTemplates + TemplateTimeWindows. Slingor (recurring weekly patterns) are imported from external systems (Carefox, eCare, Attendo CSV) via manual CSV upload or API.
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Purpose: Materialize a schedule for a specific service area and date range.
How it works: Planner selects a service area and date range, then triggers createScheduleFromServiceArea . This materializes Visit, VisitTimeWindow, VisitDependency, and VisitGroup rows from the master data templates — and auto-starts Caire Core shift layer+Caire Core routing layer optimization immediately. The planning window is dynamic, derived from the visit time windows, not a fixed rolling window.
Planner opens the schedule creation dialog and picks which service area and time window to plan for.
createScheduleFromServiceArea creates Visit + VisitTimeWindow + VisitDependency + VisitGroup rows from the timeless master data.
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Purpose: Handle unexpected events during the day while protecting ongoing visits and maintaining continuity.
Algorithm freezes started/imminent visits. Only future visits become flexible.
Solver fills gaps and reassigns visits, minimizing disruption to rest of day.
Planner reviews "ghost tracks" (previous positions) and metrics, then publishes to mobile apps.
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Your role: Set up VisitTemplates and care decisions, create schedules, review optimization results, define continuity rules and skill requirements.
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Your role: Manage daily schedules, handle real-time disruptions, publish to mobile apps, monitor performance.
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Your role: Execute visits according to mobile app schedule, report deviations, receive real-time updates.
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Your role: Monitor KPIs, analyze performance trends, approve major schedule changes, set organizational rules.
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Your role: Review and approve proposed schedules, provide preferences, receive consistent care.
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CAIRE uses Bryntum SchedulerPro, a professional-grade scheduling grid component, for the user interface. This provides:
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The optimization engine is powered by Timefold (formerly OptaPlanner), a constraint satisfaction solver:
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CAIRE integrates with operations systems via APIs and CSV import/export:
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Core entities in CAIRE's scheduling system:
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CAIRE follows a microservices architecture:
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Preview how AI-optimized schedules, health check results, and route details appear in the platform. All personal data is masked but workflows are shown exactly as in production.
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Intuitive drag and drop interface for scheduling visits with real-time rule verification. Drag unplanned visits to the schedule and see immediate validation of continuity, competencies, and time constraints. Statistics
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Comprehensive statistics and route optimization insights for schedule performance. View service time, travel time, waiting time, utilization rates, and route segments for each employee. Filtering
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Powerful filtering options for visits, staff, competencies, and service areas. Filter by visit type, priority, staffing requirements, competencies, and service areas to focus on specific scheduling needs. Optimization
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Choose from predefined optimization scenarios or create custom optimization settings. Select scenarios like Daily Plan, New Clients, Disruption Management, Continuity Focus, or Maximum Efficiency, each with customizable weights and constraints. Pre-Planning
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AI identifies patterns that require user approval before optimization becomes a fixed plan. The panel shows priority, time suggestions, and why the change is recommended. Daily Review
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The timeline shows all employees' shifts, service, travel, and breaks in one view. Color coding makes it easy to see balance and identify gaps. Routes
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The map layout visualizes each caregiver's route, timestamps, and alternatives. Compare office start against optimal route and see quality indicators in real-time. Frequently Asked Questions
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CAIRE uses one unified flow : (1) Master data — municipality decisions are imported as timeless VisitTemplates and slingor patterns. (2) Schedule creation — planner selects a service area + date range; createScheduleFromServiceArea materializes visits and auto-starts Caire Core shift layer+Caire Core routing layer optimization (~35 min total). (3) Review and publish — planner reviews the Bryntum workspace, runs health checks, makes edits, and publishes. (4) Disruptions — pin intact visits, run from-patch re-optimization, re-publish. There is no separate pre-planning phase or daily scheduling phase; it is all the same system.
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Yes! While CAIRE has API integrations with Carefox and eCare Welfare for two-way sync, you can also use CSV import/export for offline workflows. This is common during pilot phases or for organizations using other systems.
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You define continuity priority per client (high, medium, low). High priority clients (e.g., dementia) will preferentially get the same caregiver every time. Medium priority (e.g., cleaning) allows more flexibility. AI respects these weights when optimizing.
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All AI suggestions are reviewed by humans before publishing. You can manually override any assignment using drag & drop. The system validates rules in real-time (skills, time windows, availability).
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Depends on problem size. Daily schedules (50-300 visits) typically optimize in 1-5 minutes. Pre-planning (longer time spans) may take 10-30 minutes. You can set time limits and stop early if needed.
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Yes! Use the pin/unpin feature. Pinned visits are locked and won't be moved by AI. This is useful for VIP clients or sensitive situations.
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Mark the employee as unavailable. CAIRE will protect ongoing visits (already started or imminent) and re-optimize future visits to other available caregivers. You'll see a diff view showing what changed.
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Yes! CAIRE scales from 5-10 employees to 100+. Smaller organizations benefit even more from time savings since manual scheduling is proportionally more time-consuming.
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Dive deeper into resource management and analytics to complete your understanding.