Real-World Results, Delivered
Explore how we partner with businesses to transform infrastructure, accelerate delivery, and achieve measurable growth.
Scaling for Peak Traffic with a Cloud-Native Migration
Challenge: A legacy monolithic application struggled with Black Friday traffic surges, leading to downtime and lost revenue.
Solution: We architected and executed a full migration to a microservices architecture on AWS, leveraging Docker, Kubernetes (EKS), and a robust CI/CD pipeline built with Jenkins and Terraform.
Achieving DevSecOps and Compliance in a Regulated Industry
Challenge: Slow, manual release processes and difficulty meeting strict financial compliance requirements like PCI DSS.
Solution: We engineered a comprehensive DevSecOps pipeline on Azure, integrating SonarQube, Trivy, and HashiCorp Vault to embed automated security and compliance checks directly into the workflow.
Building a Scalable MLOps Platform from the Ground Up
Challenge: Data scientists were spending more time on infrastructure than building models. The process for training and deploying models was manual and not reproducible.
Solution: We designed and deployed a unified MLOps platform on Google Cloud using Kubeflow on GKE, integrating MLflow for experiment tracking and Seldon Core for robust model serving.
Automating Model Retraining for a Retail Giant
Challenge: A leading e-commerce platform's recommendation models were becoming stale, leading to decreased accuracy. The manual, quarterly retraining process was slow and resource-intensive.
Solution: We implemented an end-to-end MLOps pipeline on AWS that automatically triggers model retraining based on performance drift detected by Prometheus. New models are containerized and deployed to an EKS cluster using a safe, automated canary release strategy.
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