A workforce time & attendance platform engineered for institutions where payroll has to be exactly right — digital shift scheduling, supervisor-approved self clock-in, and an audit trail behind every minute.
In care institutions, hospitals, and facilities running shift work, time is still tracked on paper sheets that get smudged, lost, or misread. Supervisors then re-key those numbers into a system — every keystroke a chance to introduce an error.
The result: wrong hours, wrong paychecks, repeated corrections, and trust eroded between staff and management. ShiftFlow removes the paper, captures every minute digitally, and surfaces anomalies before payroll runs.
Build weekly schedules, assign caregivers to day or night shifts, reassign in a click. Coverage warnings catch understaffed days before they happen.
Employees clock themselves in and out from their own profile. Timestamps come from the system clock — never typed. Device GPS is captured at the moment of each punch and compared to the configured worksite, so every entry is tagged on-site, off-site (with distance), or no-GPS before it reaches the supervisor for approval.
Three configurable tiers: Verify-Lite (browser GPS vs. worksite radius, ships today), Verify-Standard (adds Wi-Fi SSID allowlist), and Verify-Strict (adds daily-rotating QR / NFC at entrance). Mobile and home-care customers get per-visit micro-geofences against each client's address.
One-tap approval for pending self-entries with verification badges visible next to every row. Edits are tracked. Every correction records who changed what and when, plus the captured coordinates.
Late arrival, early departure, overtime, missing punches, shift gaps, off-site clock-ins — surfaced automatically on the supervisor dashboard.
Auto-calculated bi-weekly totals per employee, broken down by entry type (work, leave) and overtime category. OT and OFFSET classified deterministically. Print or export to CSV in one click.
In-app help that answers questions about leave balances, HR & company rules, and first-aid guidance for assisting people with disabilities. Plus a knowledge search agent.
Drop your Loom, YouTube, or MP4 embed into this section. See the shiftflow-demo-script.md file for a ready-made 90-second walkthrough script.
How does the supervisor know the worker is actually at the work area when they tap Clock In? ShiftFlow captures device GPS at the moment of the punch and compares it to a worksite geofence set by the supervisor — every entry is tagged on-site, off-site (with distance), or no-GPS, and the result is surfaced during approval and recorded in the audit log.
Coordinates are stored on the entry only — never tracked continuously through the shift. PIPEDA / PIPA notice and consent are captured during employee onboarding.
Browser Geolocation API captures device GPS at clock-in/out; haversine distance vs. configured worksite radius. Off-site entries are flagged for supervisor review.
Verify-Lite plus on-site Wi-Fi SSID / IP allowlist. Both signals must pass. Failing entries can be flagged or hard-blocked per tenant setting. For LTC, retirement, manufacturing, offices.
Verify-Standard plus a daily-rotating QR at the entrance (or NFC tap). Off-site or unverified clock-in is hard-blocked. For regulated healthcare and unionized environments.
For home care, security patrols, cleaning crews, and field-service operators, the geofence is the client/visit address — ShiftFlow stores per-visit coordinates and treats each visit as its own micro-geofence, so a home-care worker's clock-in is verified against the client's home rather than the agency's office.
ShiftFlow launched at Bea Fisher, a caregiving institution running 24/7 day and night shifts. Before ShiftFlow, caregivers logged time on paper and supervisors transcribed it into a payroll system — a process responsible for repeated salary errors.
With ShiftFlow, every entry is captured digitally, every correction is logged, and supervisors approve self-reported clock-ins before payroll runs. The audit trail closes the loop on accountability for both sides.
The demo runs entirely in your browser with seeded sample data. Want to deploy it for your own institution? We adapt the data model, branding, and integrations to your environment.