Unified AI-driven scheduling system combining monthly pre-planning with daily optimization and hybrid human-AI approach. Achieve 50%+ scheduling time savings, 20% travel reduction, and 75–80% staff utilization through intelligent automation and recurring patterns (slingor).
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.
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.
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.
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 →
CAIRE's scheduling system operates in three coordinated phases, each handling different time horizons and use cases. All phases use the same UI and backend (Bryntum SchedulerPro + Timefold AI solver), but with different time windows and optimization strategies.
Purpose: Onboard new customers from municipal decisions. Optimize movable visits (cleaning, walks, shopping) over weeks/months with flexible time windows before customer approval.
How it works: Import movable_visits_anonymized.csv containing both unplanned and planned movable visits. Run optimization with Timefold solver—same process as daily schedules but with broader time windows (e.g., "Monday 07:00 - Sunday 22:00"). AI creates optimized schedule where every movable visit gets a child fixed visit. This becomes the baseline for daily planning.
AI extracts customer details, service types, frequency, and time preferences from the PDF.
Set broad windows like "Morning 07:00-10:00" or "Any weekday" for flexible visits.
Solver finds optimal placement considering travel time, staff workload, and existing slingor patterns.
Present optimized schedule to customer. Once approved, visits become fixed with ±15 min buffers.
Publish approved schedule to Carefox/eCare Welfare. Fixed visits become part of recurring slingor.
Read the complete Pre-Planning guide
Purpose: Optimize today's visits with nightly automation. Handle sick leave and cancellations in real-time within ±15/±30 minute flexibility buffers.
How it works: Nightly import (02:00 AM, 60-day rolling window) from operations systems. Slingor are expanded into daily baseline with all visits marked as "fixed". AI can only optimize visits with flexibility buffers or newly added movable visits. Real-time updates during the day handle disruptions by temporarily unlocking affected visits.
Automatic import from Carefox/eCare Welfare. 60-day rolling window ensures fresh data.
Solver respects locked visits but can adjust flexible ones within narrow time windows.
Coordinators review optimized schedule, make manual adjustments if needed.
Sick leave, cancellations, urgent visits trigger instant re-optimization of affected routes.
Analytics show how well AI predictions matched actual executed visits.
Read the complete Daily Scheduling guide
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.
Powered by Timefold solver. Handles multi-objective optimization: minimize travel, maximize continuity, balance workload, respect time windows.
Seamless integration with Carefox, eCare Welfare, and other operations systems. CSV import/export for offline workflows.
View schedules across 3 days, 1 week, 2 weeks, or 1 month. See demand curves and patterns over time.
Clear visual distinction. Movable visits (dashed border) can be optimized. Fixed visits (solid border) are locked.
Define continuity priority per client. High priority for dementia clients, medium for cleaning. AI respects these preferences.
Guarantees tasks requiring specific skills (medication, wound care) are only assigned to qualified staff.
Visualize demand per hour (daily view) or per day (longer views). Identify bottlenecks before they happen.
Compare manual slinga against CAIRE optimized and actual executed schedules. See the impact in travel time, utilization, and continuity.
One-click publish to caregiver mobile apps. Real-time notifications for schedule changes.
Proactively finds flexible visits to fill gaps from cancellations, maximizing revenue and staff utilization.
Rules adjustable at Organization, Service Area, Employee, Client, or Visit level. Full flexibility.
Intuitive drag and drop interface with real-time rule verification. Immediate feedback on continuity, competencies, and time constraints.
Your role: Build stable slingor patterns, onboard new customers via pre-planning, define continuity rules and skill requirements.
Your role: Manage daily schedules, handle real-time disruptions, publish to mobile apps, monitor performance.
Your role: Execute visits according to mobile app schedule, report deviations, receive real-time updates.
Your role: Monitor KPIs, analyze performance trends, approve major schedule changes, set organizational rules.
Your role: Review and approve proposed schedules, provide preferences, receive consistent care.
CAIRE uses Bryntum SchedulerPro, a professional-grade scheduling grid component, for the user interface. This provides:
The optimization engine is powered by Timefold (formerly OptaPlanner), a constraint satisfaction solver:
CAIRE integrates with operations systems via APIs and CSV import/export:
Core entities in CAIRE's scheduling system:
CAIRE follows a microservices architecture:
Preview how pre-planning suggestions, daily AI-optimized schedules, and route details interact in the platform. All personal data is masked but workflows are shown exactly as in production.
Pre-planning handles long-term scheduling (14-30 days ahead) for onboarding new customers. It uses broad time windows (e.g., "Monday 07:00 - Sunday 22:00") and requires customer approval before visits become fixed. Daily scheduling handles short-term operations (1-7 days) with narrow time windows (±15-30 min) for real-time disruptions. Both use the same UI and backend.
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.
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.
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).
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.
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.
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.
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.
Dive deeper into resource management and analytics to complete your understanding.