Case Studies
Real engagements, real numbers. Here's what we've delivered for teams like yours.
Series B AI Startup
The Problem
Data science team built a fraud detection model that worked great in testing. Six months later, still not in production. Engineering says 'we need to build the right infrastructure first.'
What We Did
Built MLOps pipeline in 8 weeks: containerized model, set up versioning, added A/B testing framework, deployed to Kubernetes with auto-scaling.
Results
FinTech with $40M ARR
The Problem
AWS bill hit $65K/month. CFO asked for breakdown. CTO had no answer, just knew 'that's what the models cost to run.'
What We Did
3-week audit identified: oversized RDS instances, unused dev environments running 24/7, no auto-scaling, paying for reserved instances they didn't need. Fixed systematically.
Results
Enterprise ML Platform
The Problem
Every model deployment took 2 weeks and required multiple teams. Deployment Friday at 4pm? Expect to work the weekend. Team morale tanking.
What We Did
Rebuilt CI/CD from scratch with GitOps, automated testing, canary deployments, instant rollbacks. Standardized on one deployment pattern everyone could use.