Challenge
A fast-growing Canadian fintech needed a platform capable of processing high-frequency trades in real time while meeting strict regulatory requirements and scaling to meet surging user demand.
Solution
Mapletech Labs designed and built a cloud-native trading engine with AI-driven analytics, event-driven microservices, and an institutional-grade security layer — delivered in under 6 months.
Results
The platform now handles 50K+ daily transactions with 99.99% uptime, sub-300ms response times, and a 40% reduction in infrastructure costs compared to the client's previous vendor.
The Challenge
Building for Speed, Scale, and Compliance
Our client, a rapidly scaling fintech startup in Toronto, had outgrown their initial trading infrastructure. Their legacy monolith could not keep up with the volume of transactions their growing user base demanded. Latency spikes during peak trading hours were causing failed orders and eroding user trust.
Beyond performance, the platform needed to satisfy rigorous regulatory requirements from FINTRAC and provincial securities commissions. Every transaction had to be auditable, every data point encrypted at rest and in transit, and the system needed to support real-time compliance checks without adding latency to the trade execution pipeline.
The client also required the platform to integrate with multiple third-party market data providers, payment processors, and banking APIs — all while maintaining a seamless, intuitive user experience for both retail and institutional traders.
Our Solution
Event-Driven Architecture with AI at the Core
We decomposed the monolithic application into a set of event-driven microservices deployed on AWS ECS with Fargate. The trade execution engine was built in Python for its rich ecosystem of financial and ML libraries, while the real-time dashboard and order management system were built with React and Node.js for speed and developer efficiency.
At the heart of the system, we implemented a custom AI model trained on historical market data to provide real-time sentiment analysis and predictive trade signals. Redis was used as a high-throughput message broker and caching layer, ensuring sub-300ms end-to-end latency from order placement to execution confirmation.
PostgreSQL served as the primary data store with row-level security, full audit logging, and point-in-time recovery. We built a dedicated compliance microservice that runs regulatory checks in parallel with trade execution — adding zero latency to the critical path while ensuring every transaction is fully auditable.
Key Results
Measurable Impact, From Day One
“Mapletech Labs didn't just build us a trading platform — they gave us a competitive advantage. The speed, reliability, and intelligence baked into the system have fundamentally changed how our traders operate. We went from firefighting infrastructure issues to focusing entirely on growth.”
Chief Technology Officer
Leading Canadian Fintech