Case Studies
Real projects. Measurable results. See how we’ve helped businesses modernize their infrastructure and implement AI solutions.
Featured Case Studies
Cloud Cost Optimization for SaaS Platform
Industry: SaaS • Software
Services: Cloud Infrastructure, Kubernetes Optimization
Challenge: Mid-sized SaaS company experiencing escalating cloud costs (€15K/month) with inefficient resource utilization and manual scaling.
Solution: Implemented Kubernetes autoscaling, right-sized instances, optimized database queries, and set up cost monitoring dashboards.
Results:
💰 40% cost reduction (€6K/month savings)
⚡ 35% faster response times
📈 99.95% uptime vs. previous 99.2%
🔄 Zero-downtime deployments
AI-Powered Customer Support Assistant
Industry: E-commerce
Services: Intelligent Automation (AI), RAG Implementation
Challenge: E-commerce platform handling 1,200+ support tickets monthly, with 70% being repetitive questions about orders, shipping, and returns.
Solution: Built RAG-powered chatbot using Claude 3.5 Sonnet with company knowledge base, product catalog, and order history integration.
Results:
🤖 60% ticket deflection
⏱️ 5-minute avg resolution (vs. 2 hours)
😊 95% satisfaction score
💸 50% support cost reduction
E-commerce Platform Modernization
Industry: Retail • E-commerce
Services: Software Development, Cloud Migration
Challenge: Legacy monolithic application with 8-second page load times, frequent downtime during traffic spikes, and difficult-to-maintain codebase.
Solution: Rebuilt as microservices with Next.js frontend, Node.js APIs, PostgreSQL database, and deployed on Kubernetes with auto-scaling.
Results:
🚀 60% faster page loads (3.2s avg)
💰 3× conversion rate increase
⚡ 40% lower infrastructure costs
🔧 10× faster deployments
CI/CD Pipeline Automation
Industry: FinTech
Services: Cloud Infrastructure, DevOps Automation
Challenge: Manual deployment process taking 4 hours, high risk of human error, no automated testing, and frequent production incidents.
Solution: Implemented GitOps workflow with GitHub Actions, automated testing, container scanning, and progressive deployments with automatic rollback.
Results:
⏱️ 12-minute deployment time (vs. 4 hours)
📉 80% fewer production incidents
✅ 100% test coverage on critical paths
🔄 3× release frequency
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