Engineering That Moves the Needle

A Series B fintech was deploying to production manually every 3 weeks. Each release required a 4-hour maintenance window, causing customer churn and developer burnout.

We designed and implemented a fully automated CI/CD pipeline on AWS using GitHub Actions, ECS Fargate, and Terraform. Blue-green deployments eliminated downtime entirely.

Deploy time dropped from 3 weeks to 45 minutes. Zero downtime releases. Developer velocity increased by 3x.

A global e-commerce brand was spending $2M/year on customer support for repetitive queries (order status, returns, tracking). Response times averaged 8 hours.

We built a multi-agent AI system using LangChain and GPT-4, integrated with their Shopify and Zendesk APIs via n8n. The agent handles tier-1 tickets autonomously and escalates complex cases.

80% of tickets resolved without human intervention. Average response time dropped from 8 hours to 90 seconds. $1.4M annual cost savings.

A HealthTech startup needed a cross-platform patient engagement app with HIPAA compliance, real-time messaging, and EHR integration — in 5 months.

Our Flutter team built a production-ready app with end-to-end encryption, Firebase real-time sync, and a custom HL7 FHIR integration layer. Deployed on AWS with full audit logging.

Launched on time, passed HIPAA audit on first attempt, reached 50,000 active users within 90 days of launch.

A legacy monolithic SaaS platform was costing $180K/month in infrastructure and taking 6+ hours to scale during peak load. The architecture was blocking new feature development.

We led a phased migration to Azure AKS microservices using the strangler fig pattern. Each service was containerized with Docker, with independent CI/CD pipelines and auto-scaling policies.

Infrastructure costs dropped to $72K/month. Auto-scaling handles 10x traffic spikes in under 2 minutes. Feature release cadence improved from monthly to weekly.

A logistics company was over-ordering inventory by an average of 40%, resulting in $8M/year in waste and storage costs. Their existing forecasting was spreadsheet-based.

We built a custom time-series forecasting model using TensorFlow and deployed it on Digital Ocean with an Airflow-orchestrated data pipeline pulling from 5 data sources.

Inventory waste reduced by 35%. Model accuracy of 91.3% on held-out test data. Full ROI achieved in 4 months post-launch.

A two-sided marketplace needed a mobile app for both service providers and customers, with real-time matching, in-app payments, and GPS tracking — all within 6 months.

We built a React Native app with Expo, a Node.js/GraphQL backend on AWS, Stripe Connect for split payments, and Socket.io for real-time provider tracking.

$2M GMV processed in Q1. 4.7★ rating on both app stores. 92% provider onboarding completion rate.