Case Studies

Reduced Manual Staffing Work by 90% with a Custom Platform

We built a platform that replaced a nursing agency's 24/7 manual booking processes with an automated system, reducing the workload from a 3-person team to 1-2 hours a day.

HealthcareStaffing
February 2026

Concept

The client is a UK nursing agency established in the 90s, supplying temporary nurses and healthcare assistants to public hospitals and private facilities across the country.

One of their main processes is booking available nurses to open shifts across dozens of hospital platforms, considering each nurse’s availability, specialties, location, preferences, and experience.

They came to Prometex to explore how much of this workflow could be automated, and build a platform for it.

Challenge

The existing workflow was manual, fragmented, and running non-stop:

24/7 manual portal monitoring
Each hospital operates its own platform for posting shifts. A team of three people worked in shifts - 24 hours a day, 7 days a week - manually checking every portal for new openings.
Manual nurse matching and booking
Staff had to cross-reference shifts against nurse availability, specialties, location, and hospital experience - all stored across several systems. Then manually enter each bid, copy-pasting details and rates.
Fragmented communication
Confirming shifts required jumping between a separate WhatsApp messaging tool, the hospital portal, their internal system, and CRM. Every confirmation meant copy-pasting between multiple windows.

Approach

Before writing a single line of code, we invested time in truly understanding the business.

  • Discovery. We ran a series of interviews with stakeholders and the team members doing the actual work - understanding not just the process, but the pain points, current workarounds, and edge cases.

  • Research. We spent a week navigating hospital platforms, studying their APIs (where available), and testing scraping and browser automation approaches. We mapped out which features would deliver the most impact and which weren’t worth automating.

  • Prototype. Within a week, we built a frontend prototype to validate the UX, flow, and feasibility, and got direct feedback from the team before committing to full development.

  • Iterative build. Based on that feedback, we finalized features and design. Then we built the platform in close collaboration with their team, adjusting as we went.

Solution

We built a custom platform that covers every stage of the booking process - from shift discovery to nurse communication.

Automated shift discovery

The platform scans all connected hospital platforms every 5 minutes using custom integrations, browser automation, and scraping. New shifts appear instantly in a unified dashboard - filterable by date, hospital, department, profession, and status. No more manual portal checking.

Shifts Dashboard
Shifts Dashboard

Smart nurse matching and auto-booking

For every shift, the platform surfaces relevant nurses from their internal system. It also shows each nurse’s surrounding shifts for easy availability checking.

For nurses who are a 100% match (right availability, right specialty, right location), the platform automatically books them and notifies the team. No manual intervention needed.

Shift Page
Shift Page

One-click and bulk booking

For manual bookings, staff select nurses and book with prefilled rates based on historical data. Each hospital’s specific platform is handled behind the scenes - with a dedicated integration configured for each one.

To book nurses across multiple shifts at once, the bulk booking view shows nurses availability and experience across all selected shifts, with one-click booking for all of them.

Bulk Book Shift
Bulk Book Shift

Full WhatsApp chat system

We didn’t just add a WhatsApp integration - we built a complete WhatsApp-based communication system that replaced their existing messaging software entirely.

The built-in chat includes message templates for availability checks and shift confirmations, automatic notifications, file and voice message support, and AI-assisted response drafting and message summarization. Shift confirmation messages are pre-populated with relevant details and can be sent directly from the shift page.

There’s also a WhatsApp Bot that reaches out to nurses who aren’t a 100% match for a shift - notifying them about relevant openings, asking for confirmation, and letting them book with a single tap. This reduces manual outreach and accelerates the booking cycle even more.

WhatsApp Chat Interface
WhatsApp Chat Interface

Automated notifications

Throughout the entire workflow, relevant team members receive email notifications about new shifts, bid updates, confirmations, and status changes - automatically, without anyone having to check or forward anything.

Impact

Before: 3 people working 24/7 in shifts. Manually checking portals, cross-referencing nurse data, copy-pasting between systems, and juggling fragmented communication tools.

After: 1 person spends 1-2 hours a day - mostly validating that everything runs smoothly and handling edge cases.

  • ~90% reduction in manual staffing work. Shift discovery, nurse matching, and most of the booking happens automatically. The team shifted from reactive, 24/7 manual labor to strategic oversight.

  • 12x faster time-to-bid. Average time-to-bid went from around 1 hour (slow detection and manual details copy-pasting) to under 5 minutes with automated detection and submission.

  • Higher booking success rate. By submitting qualified nurses faster and in higher volume, the platform wins more shifts than manual speed ever could.

  • Zero context-switching. Shifts, nurses, bookings, and communication - all in one platform. No more jumping between hospital portals, CRM, and separate messaging tools.

“What surprised me was how quickly they understood our business. Within a month we had a first version working, and the end result cut our booking workload by 90%! I'd happily recommend them.”
Anonymous
Managing Director

* Client and company details have been anonymized on their request.

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