Case studies
How we helped teams transform infrastructure and move faster.
Modernizing logistics operations
Company: Midwest logistics software company (Series A, 80 engineers)
Challenge: Manual deployment processes, 4-6 week release cycles, fragile on-call operations.
The Work
- → Designed infrastructure-as-code architecture (Terraform)
- → Built CI/CD pipeline with GitHub Actions and AWS CodePipeline
- → Implemented multi-environment management (dev, staging, production)
- → Established infrastructure testing and plan review process
- → Created operational runbooks and on-call escalation procedures
Outcomes
- → Deployment frequency: 4-6 weeks → multiple per week
- → Mean time to recovery: 6-8 hours → 45 minutes
- → Infrastructure change lead time: 3-4 weeks → 2-3 days
- → On-call incidents requiring escalation: 60% → 20%
"We went from shipping features every quarter to every sprint. Infrastructure stopped being a blocker. The team understood our business constraints and didn't over-engineer the solution."
Michael Torres
VP Engineering
Audit-ready health data platform
Company: California health-data startup (Series B, 120 engineers)
Challenge: HIPAA compliance requirements unclear, audit readiness uncertain, observability gaps.
The Work
- → Audit control assessment mapping to HIPAA and HL7 requirements
- → Implemented encryption-in-transit and encryption-at-rest
- → Built comprehensive audit logging and evidence collection
- → Designed network isolation and data residency controls
- → Established disaster recovery and business continuity procedures
Outcomes
- → SOC 2 Type II certification achieved in 14 weeks
- → Audit control gaps: 23 → 2 (minor)
- → Infrastructure change auditability: 30% → 100%
- → Customer audit cycles: 4-6 weeks → 1-2 weeks (automated evidence)
"We were terrified of SOC 2 audit. The team made compliance feel concrete and achievable. Now we're confident in our audit-readiness, and customers see us as a safe partner."
Dr. Lisa Patterson
Chief Compliance Officer
Scaling for seasonal peaks
Company: Northeast specialty retailer (Series A, 45 engineers)
Challenge: Cloud spend 3x higher during holidays, capacity forecasting difficult, no cost visibility.
The Work
- → Comprehensive cloud cost analysis and waste identification
- → Implemented auto-scaling policies based on traffic patterns
- → Right-sized database, compute, and storage resources
- → Built cost allocation and chargeback model by team
- → Established forecast model based on historical traffic and growth
Outcomes
- → Annual cloud spend reduced from $850K to $580K
- → Holiday peak cost reduced from 280% baseline to 160%
- → Cost forecast accuracy: 50% variance → 15% variance
- → Infrastructure decisions now tied to cost impact clarity
"We were hemorrhaging money in cloud costs and had no idea why. The team gave us visibility and real answers. We're saving $270K annually and our peak season is actually our best performing season now."
James Rodriguez
CFO
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