Client
FinBridge Corp
Industry
FinTech
Tech Stack
AWSKubernetesApache KafkaPythonPostgreSQLTerraform
The Challenge
What We Were Up Against
FinBridge ran a 12-year-old Java monolith that processed $2B+ annually. System outages cost $200K/hour, fraud losses were growing 30% YoY, and the dev team couldn't ship features without breaking production.
Our Solution
How We Solved It
14-month strangler-fig migration to AWS microservices, event-driven architecture with Kafka, and a real-time ML fraud detection layer trained on 5M historical transactions — all with zero downtime.
01
Architecture Blueprint
Domain decomposition workshop with 40+ stakeholders to define service boundaries and migration sequence.
02
Strangler Fig Migration
Incremental cutover — new services proxy through the monolith, progressively taking over domains.
03
Event Streaming
Kafka event bus for all inter-service communication — monolith and microservices coexist during transition.
04
ML Fraud Detection
XGBoost model trained on 5M transactions, deployed as a low-latency service (~12ms p99) scoring every transaction.
05
Zero Downtime Cutover
Blue/green deployment with automated rollback — final cutover completed in a 4-hour maintenance window.
The Impact
Measurable Results
99.99% uptime SLA achieved from day one
Fraud losses reduced 78% within 6 months
API throughput increased 10× (handling 50K TPS)
Feature release cycle from 6 months to 2 weeks
$2M+ annual savings in fraud and infrastructure
"No one believes we ran a zero-downtime migration of a $2B banking core in 14 months. TechGeneses made it happen — and the fraud detection AI alone saved more than the project cost."
Rebecca Torres
CTO, FinBridge Corp
Key Outcomes
Uptime SLA met99.99%
Fraud losses−78%
API throughput10×
Migration timeline14mo
