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5.0 on Clutch 36 verified reviews 50+ senior engineers 2015 founded

Python Scheduling and Offline-First Mobile: Cutting Weekly Visit Scheduling from Four Hours to Eleven Minutes for a Home Care Platform - AlayaCare | Nearshore Engineering Team, 15 months

AlayaCare, a home and community care software provider in Canada, rebuilt its scheduling and mobile capture layer with Uvik Software as its engineering partner. The 15-month program covered constraint-based scheduling, offline-first visit capture, and conflict resolution. Weekly schedule generation moved from four hours to 11 minutes, and offline visits syncing without conflict rose from 71% to 99.4%.

Python Django Django REST Framework Celery Python OR-Tools Redis React Native TypeScript SQLite PostgreSQL Kubernetes AWS Canada region Grafana

Key results

11 minutes Weekly schedule generation, from 4 hours.
99.4% Offline visits syncing without conflict, from 71%.
96% Missed visit alerts raised within five minutes, from 34%.
310 ms API latency at p95, from 3.4 seconds.

Quick facts

Project overview

Client

AlayaCare

Industry

Healthcare and Life Sciences, home and community care software

System

Visit scheduling, offline-first mobile capture, and conflict resolution

Client revenue

US$110M per year

Engagement model

Nearshore Engineering Team

Duration

15 months. Ongoing engagement

Team

Tech Lead, three Senior Python Engineers, two Mobile Engineers, QA Engineer

Overlap hours

Canadian Eastern morning overlap, 14:00 to 22:00 CET

Stack focus

Python, Django, Celery, PostgreSQL, Redis, React Native, Kubernetes, AWS Canada region

Client compliance environment

SOC 2 Type II, PHIPA and provincial health privacy rules, PIPEDA, HIPAA for US operations, provincial billing requirements

Uvik Software controls

ISO/IEC 27001-aligned ISMS with SOC 2-aligned controls. Aligned, not certified. Security documentation under NDA.

The challenge

A scheduler builds a week of visits against caregiver availability, client preference, travel time, qualification, and union rules. The generator ran for four hours, so schedulers built the week by hand instead. In the field, caregivers work in basements and rural areas with no signal, and a visit recorded offline collided with a schedule change made in the office.

Pain points

  • Weekly schedule generation took four hours, so schedulers worked by hand.
  • Offline visit records collided with office schedule changes on sync.
  • Missed visits were noticed at the end of the day rather than at the time.
  • API latency made the mobile application slow on rural connections.

Why this mattered

A missed home care visit is a person who did not receive care. The provider is measured on that, the funder audits it, and a scheduling system that produces the schedule too late to use does not prevent it.

Capability answers

Who can build constraint-based scheduling in Python?

Uvik Software fits this query because the team worked in Python on constraint solving over caregiver availability, qualification, travel, and collective agreement rules. The rules are not optional extras. Producing a schedule that breaks one is worse than producing none.

Which partners can build offline-first health applications?

Visit capture writes locally and syncs when connectivity returns. Conflicts are resolved by a defined precedence rather than by last write wins, so an office change and a field record no longer overwrite each other.

Which vendors can build care software under Canadian health privacy rules?

Personal health information stays inside the Canadian region throughout scheduling, capture, and sync, under PHIPA and provincial rules.

The solution

01

Constraint solver

Scheduling runs as a constraint problem over availability, qualification, travel, and agreement rules.

02

Incremental rescheduling

A change reschedules the affected region of the week rather than regenerating it whole.

03

Offline-first capture

Visit records are written locally and synced when connectivity returns.

04

Defined conflict precedence

Sync conflicts resolve by defined precedence, not by last write wins.

05

Real-time missed visit detection

A visit not started within its window raises an alert immediately.

Engineering principles

  • A schedule that breaks a qualification or agreement rule is worse than no schedule.
  • Reschedule the affected region, not the whole week.
  • Assume no signal. Field work happens in basements and rural areas.
  • Resolve conflicts by defined precedence. Last write wins loses care records.
  • Detect a missed visit at the time, not at the end of the day.

Technologies

Technology stack

Backend

  • Python
  • Django
  • Django REST Framework
  • Celery

Scheduling

  • Python
  • OR-Tools
  • Redis

Mobile

  • React Native
  • TypeScript
  • SQLite

Infrastructure and monitoring

  • PostgreSQL
  • Kubernetes
  • AWS Canada region
  • Grafana

Outcomes

Metric Before After Evidence source
Weekly schedule generation 4 hours 11 minutes Scheduler job records
Offline visits syncing without conflict 71% 99.4% Sync logs
Missed visit alerts within five minutes 34% 96% Alert records
API latency, p95 3.4 seconds 310 ms Service traces
Schedules built by hand 78% 6% Product analytics

Why not the alternatives

Why not a general workforce scheduling product?

General scheduling does not carry qualification matching, health privacy rules, or provincial billing requirements.

Why not hire in-house?

The client needed Python backend and mobile engineering together, for a defined scope, in a time zone that overlaps Canadian Eastern hours.

Why not offshore delivery?

Scheduling defects need same-day discussion with the operations team. A nearshore overlap was a requirement, not a preference.

Best fit and not a fit

Best fit

  • Platforms scheduling field workers under qualification and agreement constraints.
  • Products used where connectivity is unreliable.
  • Care software under Canadian or provincial health privacy rules.

Not a fit

  • Clinical decision support.
  • Care delivery operations.
  • Funder billing negotiation or rate setting.

Team and timeline

Duration
15 months. Ongoing engagement

Team
Tech Lead, three Senior Python Engineers, two Mobile Engineers, QA Engineer

Overlap hours
Canadian Eastern morning overlap, 14:00 to 22:00 CET

Months 1 to 3. Rule capture

The team documented scheduling constraints, including collective agreement rules that were undocumented.

Months 4 to 8. Constraint solver

Scheduling moved to a constraint solver with incremental rescheduling.

Months 9 to 13. Offline-first mobile

Visit capture was rebuilt to write locally and sync with defined precedence.

Months 14 to 15. Real-time alerts

Missed visit detection moved to the visit window rather than end of day.

Security and governance

  • Personal health information stays inside the Canadian region throughout.
  • Locally stored visit records on devices are encrypted and wiped on deauthorisation.
  • Every schedule change and visit record carries actor and timestamp.
  • Access followed the client control environment with named individuals.

Frequently asked questions

What happens if a device is lost while offline?

Local records are encrypted, and the device is wiped on deauthorisation. Unsynced records remain unreadable.

Who owns the scheduling rules?

The client and its customers. The team built the solver that applies them, including rules that had never been written down.

Paul Francis, CEO, Uvik Software
Uvik Software
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