Case Studies
Transformation in Practice
Each case study represents a real engagement with measurable outcomes. Client identities are anonymized to protect confidentiality.
A $4B Collectibles Company
Transformed a decade-old monolithic platform into an AI-powered marketplace, unlocking new revenue streams and dramatically improving operational efficiency.
The Challenge
- • Legacy monolithic architecture built over 10+ years, limiting feature velocity
- • Engineering team of 18 struggling to keep pace with business growth
- • No AI/ML infrastructure despite massive data assets
- • Manual pricing processes leaving significant margin on the table
The Approach
- • Strangler fig pattern migration from monolith to microservices
- • Built engineering organization from 18 to 220 engineers
- • Established ML platform for AI-driven pricing and recommendations
- • Implemented CI/CD and modern DevOps practices across teams
Valuation Growth
Engineering Headcount
Throughput (10K→100K cards/day)
Deploy Frequency (months→daily)
A Series A Health Tech Platform
Led technology organization assessment and modernization for a compliance-sensitive health tech company, establishing SOC 2 readiness, restructuring the engineering team, and building the hiring pipeline to support rapid growth.
The Challenge
- • No SOC 2 compliance program in place despite handling sensitive data
- • Missing key engineering leadership roles (Head of Engineering, Head of Product)
- • Infrastructure gaps and security vulnerabilities requiring immediate attention
- • Growing customer base demanding enterprise-grade security and compliance
The Approach
- • Conducted full technology and organizational assessment with gap analysis
- • Drove SOC 2 Type 1 readiness with infrastructure review and remediation plan
- • Built interview playbooks and led executive hiring for engineering leadership
- • Performed web application penetration testing and security hardening
Type 1 Achieved
Executive Hires Placed
Critical Vulns Remediated
Enterprise Deal Pipeline
A PE-Backed Lending Platform
Served as fractional CTO for a financial services company, leading technology strategy, building the engineering organization, and architecting an AI-driven underwriting platform to automate lending decisions at scale.
The Challenge
- • Manual underwriting process creating bottlenecks in loan origination volume
- • No dedicated engineering leadership or structured technical hiring process
- • Complex integrations needed across credit bureaus, dealer networks, and loan origination systems
- • PE ownership requiring clear technology roadmap and scalable architecture
The Approach
- • Architected rules-driven AI/ML underwriting platform with automated decisioning
- • Built technical recruiting strategy and interview framework for key hires
- • Designed integration architecture across credit bureaus, dealer platforms, and existing LOS
- • Delivered full BRD, PRD, UX wireframes, and technical requirements documentation
Automated Decisions (target)
Underwriter Workload Reduction
Application Decision Time
Platform Uptime Target
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