Overview
iDenfy is a leading identity verification service provider that supports businesses in combating fraud and meeting compliance requirements through AI-powered identity checks. As iDenfy scaled its operations and onboarded more clients requiring real-time verification, the performance of their infrastructure became a critical factor in maintaining a smooth customer experience. To address growing latency issues and maintain system responsiveness, iDenfy partnered with CTO2B for a tailored infrastructure optimization initiative.
Challenges
As iDenfy’s customer base expanded, the volume of identity verification requests increased significantly. These verifications involved complex image recognition and liveness detection, which required substantial compute power. The key challenges they faced included:
- Slow response times due to CPU-based image processing under peak load
- Inconsistent user experience caused by verification delays
- Scalability limitations as standard compute instances failed to meet growing performance demands
- Cost inefficiency, as scaling with traditional infrastructure yielded diminishing returns
CTO2B’s Solution
CTO2B conducted a detailed analysis of iDenfy’s workload and identified GPU-powered compute as a game-changer for handling image-intensive tasks more efficiently. The decision was made to integrate GPU instances into the real-time verification pipeline. This allowed iDenfy to offload critical AI and image processing functions to hardware optimized for parallel processing.
CTO2B provided not only the infrastructure components but also hands-on DevOps implementation and cloud optimization strategy, ensuring that the transition was seamless and aligned with iDenfy’s operational goals.
Key Actions Taken
Infrastructure Assessment: CTO2B conducted a performance audit to pinpoint bottlenecks in the verification process.
Implementation of GPU Instances: iDenfy’s AI workloads were migrated from CPU to GPU instances, improving efficiency.
Load Distribution Optimization: CTO2B restructured the load balancers and autoscaling policies to route heavy image-processing requests to GPU-accelerated nodes.
Monitoring and Cost Management: Implemented cloud monitoring tools to track performance improvements and maintain cost control.
Results
2.2x reduction in compute operational cost: The average verification time dropped significantly due to faster image processing.
35% faster processing per identity verification: End-users experienced quicker and smoother verifications across all devices.
Increased Throughput: The optimized infrastructure handled higher concurrent verification requests with no degradation in performance.
Cost-Effective Scaling: iDenfy was able to scale its services efficiently without overspending on underperforming infrastructure.
Conclusion
iDenfy’s collaboration with CTO2B turned a critical infrastructure challenge into a competitive advantage. With the integration of GPU-powered instances and expert DevOps support, iDenfy achieved a scalable, high-performance identity verification platform that’s ready for future growth.
