Backend Systems
LabsChecks
Health-tech platform helping users compare diagnostic tests, get recommendations, and book lab services across multiple cities.
01
Overview
Comparing diagnostic tests across labs is fragmented — pricing, test names, and availability differ by provider and by city. LabsChecks centralizes comparison, recommendation, and booking into a single flow.
02
Challenge
The same diagnostic test is often listed under different names, prices, and bundles by different labs in different cities. Making that comparable — and then booking against a real lab partner's availability — means normalizing inconsistent data before recommendation logic can mean anything.
03
Architecture
The backend aggregates test and lab data across cities into a normalized comparison layer. Recommendation logic ranks options against user needs, and the booking flow integrates with lab partner scheduling to confirm availability.
- User
- Search / Compare
- Recommendation Logic
- Booking Flow
- Lab Partner Integration
- Confirmation
04
Implementation
- Built the comparison engine that normalizes test/lab data across multiple cities and providers.
- Built recommendation logic to help users choose between comparable options.
- Built the booking flow, integrating with lab partner scheduling for confirmation.
05
Technologies
06
Engineering Decisions
Why normalize test data before building recommendations?
Recommendation logic is only as good as the data underneath it. Without normalizing test names, pricing, and bundles across labs first, any ranking would be comparing things that aren't actually comparable.
Why integrate directly with lab partner scheduling instead of a manual booking handoff?
A recommendation that can't be booked against real availability isn't useful. Direct integration keeps the comparison-to-booking flow in one system instead of dropping the user into a separate manual process.
07
Reliability
- Booking flow has to handle partner-lab availability changes and failures gracefully rather than confirming bookings that can't be fulfilled.
- Normalized comparison data reduces the chance of surfacing incorrect pricing or test information.
08
Outcome
A working platform for comparing, recommending, and booking diagnostic tests across multiple cities and lab partners.