Cent Capital

Something we'd like to share is our deliberate choice of Java and Spring Boot for our backend. In an ecosystem often dominated by other languages for startups, we chose this stack for its proven enterprise-grade reliability, performance, and security—all non-negotiable in the Fintech industry. The maturity of the JVM, the comprehensive features of the Spring ecosystem like Spring Security, and the massive global talent pool allow us to build a highly scalable and secure application. This provides a rock-solid foundation for our platform, ready to meet the stringent compliance and Regtech demands required to partner with major financial institutions.

Use Cloudflare as a unified control plane in front of your multi-cloud infrastructure. We don't just use it for DNS and caching; it acts as our primary API Gateway and Web Application Firewall (WAF). By routing all traffic through Cloudflare, we get robust DDoS mitigation and can easily load-balance or route requests to the appropriate services running on AWS, GCP, or Azure. This simplifies our architecture, enhances security for our React single-page application and Spring Boot backend, and reduces latency for our users globally, all from a single dashboard.

A critical migration for us was moving our initial backend prototype from Supabase to a self-managed Java Spring Boot application. While Supabase's Backend-as-a-Service (BaaS) model was excellent for rapidly building our MVP with its auto-generated APIs, we required more granular control over our business logic and data persistence layer as we prepared to scale. The migration involved carefully moving our user data to a dedicated PostgreSQL instance and rewriting our RESTful APIs in Spring Boot. This move gave us full control over our architecture, allowing us to implement more complex JWT authentication flows using Spring Security and optimize database performance for our demanding Fintech workload.

We chose Amazon Bedrock as the core of our Generative AI engine for several critical reasons. As a Fintech SaaS platform focused on hyper-personalization, we needed secure, scalable access to a diverse range of powerful Large Language Models (LLMs) without the massive overhead of managing our own AI infrastructure. Bedrock provides this through a single, managed API, integrating seamlessly with our existing AWS ecosystem for services like Amazon SES and SNS. This serverless approach allows our team to rapidly prototype and deploy sophisticated AI features for our financial wellness application, ensuring both high performance and the data security required in the financial industry.