The system must support complex fleet asset lifecycle automation from acquisition and financing through usage, resale, and data archiving, while consolidating fragmented data from multiple APIs and integrating with legacy infrastructure providers that offer limited connectivity. It also requires multi-tenant scalability with strict data isolation and compliance, as well as dynamic pricing logic that factors in vehicle usage, depreciation, and OEM condition data.
Softeta delivered a serverless, event-driven SaaS architecture that unifies OEM and telematics data, automates the full fleet asset lifecycle, and enables dynamic pricing based on real-time vehicle insights. A low-code orchestration layer accelerated MVP delivery, while Azure Functions and Supabase provided scalable compute, multi-tenant data isolation, and cost-efficient growth.
The next steps include implementing predictive maintenance through AI-driven failure models that leverage OEM sensor data to anticipate issues before they occur. In parallel, an advanced analytics layer will be developed to enhance asset valuation, optimize usage patterns, and provide detailed carbon impact tracking.
Technologies used:
Azure
Supabase