Recommendation
Platform.
Building the technical foundation behind a recommendation platform for tradespeople.
Cloudicia built robust backend services and APIs using a modern microservice architecture, with a focus on reliability, performance and scalability.
A recommendation
experience needs a strong foundation.
The platform had demanding uptime and scalability requirements. The core challenge was therefore not simply building an interface, but creating backend infrastructure capable of supporting a production recommendation platform reliably.
Separate the
pieces.
Connect the system.
A microservice approach allowed individual platform responsibilities to remain separated while working together through APIs.
The recommendation
experience sits on a system.
The visible product is only one part of the platform. Behind it sits the service and API architecture responsible for supporting reliability and scale.
Discovery
Users begin with a need that has to be matched to the right tradesperson.
Recommendation
The platform turns available information into a recommendation experience.
Services
Backend services separate platform responsibilities into scalable components.
APIs
Well-defined APIs connect the experience with the underlying platform.
Production
The architecture is designed around reliability, uptime and scalability.
Built for the
demands of a production platform.
Cloudicia focused on the underlying engineering: robust services, API infrastructure, microservices and the ability to operate reliably at scale.
Microservice architecture
A modern microservice architecture provides the foundation for the platform.
Backend services
Robust backend services support the recommendation platform and its workflows.
API infrastructure
APIs provide the integration layer between the product experience and backend capabilities.
Scalability
The platform was engineered to handle demanding scalability requirements.
Reliability
Production architecture was designed around high availability and dependable operation.
The numbers reflect
the engineering.
The project material reports measurable improvements across conversion, uptime, user satisfaction and platform scalability.
A recommendation experience is only as dependable as the system behind it.
Good product experiences depend on boring things being done exceptionally well: services, APIs, reliability and scale.