Articles
Current articles on AI, digitalization, and trends in home care.
Explore our guides, articles, and whitepapers about AI-driven scheduling and digitalization in home care.
Start with care needs and visit planning, then explore staffing, routes, field work and the measures that connect them. Each guide keeps its own question and evidence in focus.
Current articles on AI, digitalization, and trends in home care.
Step-by-step guides for optimizing home care operations with AI and digital technology.
Objective comparisons between different systems and solutions for home care.
Detailed product guides that show how Caire solves onboarding, continuity, diagnostics, and optimization readiness.
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How Caire plans visit routes: less travel, more client-facing time, and the planner approves every proposal.
Thought leadership on how route optimization balances travel, continuity, skills, and human review.
Estimate savings from better efficiency, continuity, and route planning.
From reusable route patterns to automatic visit planning that follows change.
Everyone does their best, and still the day falls apart. An ordinary day in home care, hour by hour, with sources.
How home care planning systems are priced, what drives the total cost and what Caire costs.
How Caire's free schedule analysis of one selected period works.
Connect compatible AI tools to available planning data and prepare reviewable proposals.
What does AI scheduling mean in home care? A practical guide to inputs, human review, measurement, and rollout.
Practical ways to reduce travel time in home care through geographic planning, the right measures, continuity, and route follow-up.
A practical model for staff planning in home care: capacity, demand, skills, shifts, and follow-up.
How home-care organizations can complement Carefox with AI support for schedules, routes, continuity, and reviewable proposals.
How to analyze unassigned home-care visits and distinguish capacity gaps from constraints, time windows, and poor inputs.
Care time and travel time are governed by the same planning variables. Three levers to lower travel time and raise care time at once, without overloading staff.
Compare the roles: plan in Caire, keep Carefox for documentation and journal. Optional one-way GET of planning data. The planner approves every proposal.
Björn Evers was diagnosed with MS at 35. After 5,000+ home-care visits he founded Caire — care first, AI as enabler.
How modern route optimization balances travel time, continuity, skills, time windows, and human review in one connected schedule.
Evidensbaserad modell för att nå ~80% brukartid och stärka personalkontinuitet samtidigt – med fyra konkreta steg, KPI-definitioner och räkneexempel.
How to balance hard and soft constraints in home care scheduling. Caire's three-layer model, the KISS principle, and strategies that handle 85% of all conditions with time windows alone.
Forskningsartikel om AI-optimering av hemtjänst. En verklig tvåveckorsplanering i Stockholmsområdet gav 5,67 unika vårdgivare per brukare och 79,1 % brukartid.
Better planning is not a choice between lower travel time and better continuity. The right model makes both goals visible, configurable, and operationally realistic.
How mathematical optimization makes trade-offs between travel time, continuity, and clear scheduling measurable for each run.
How Caire uses VRPTW algorithms and home-care-specific constraints to compare visit coverage and travel-time trade-offs in optimization runs.
How AI revolutionizes scheduling in home care and what it means for future care organizations.
Learn how to optimize your home care schedules for maximum efficiency and staff satisfaction.
A comprehensive guide to prepare your organization for AI-driven home care planning.
An objective comparison of leading scheduling systems for home care and their features.
Compare traditional Excel scheduling with AI-powered solutions
Strategies and methods to optimize staff planning in home care.
A deep dive into the technological and organizational trends that will shape home care in the coming years.