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CASE STUDY

84% Cost Reduction: From 50 Engineers to Elite 8

The Challenge

A B2B SaaS cybersecurity company was struggling with bloated engineering operations, slow deployment cycles, and escalating costs. With 50 engineers, 3-month sprint cycles, and 2+ million lines of legacy code, the organization faced declining velocity, mounting technical debt, and unsustainable operational expenses that threatened profitability and competitive positioning.

Our Approach

We executed a comprehensive AI transformation of the engineering organization, leveraging automation, process optimization, and strategic refactoring. We streamlined the team from 50 to 8 elite engineers, implemented AI-powered development tools, redesigned sprint processes from 3 months to 2-week deployments, and refactored 2+ million lines of legacy code into a lightweight, maintainable architecture.

Conducted comprehensive engineering organization assessment to identify redundancies, inefficiencies, and technical debt

Designed and implemented AI-powered development tools and automation to augment engineering productivity

Streamlined team structure by consolidating roles, eliminating redundancy, and focusing on high-impact engineering talent

Redesigned sprint and deployment processes from 3-month cycles to 2-week agile deployments

Executed strategic code refactoring of 2+ million lines of legacy code into modern, maintainable architecture

Implemented continuous integration and deployment pipelines to support rapid release cycles

Optimized design processes and reduced design overhead while maintaining quality standards

Key Features

AI-powered development tools and automation

Streamlined engineering team structure

Agile sprint processes with 2-week deployment cycles

Legacy code refactoring and modernization

Continuous integration and deployment pipelines

Process optimization and efficiency improvements

Impact & Results

Reduced engineering headcount by 84% (50 to 8 engineers) while increasing development velocity by 3x through AI automation and process optimization

Accelerated deployment cycles from 3 months to 2 weeks, achieving a 6x improvement in release frequency

Refactored 2+ million lines of legacy code into a modern, maintainable codebase, reducing technical debt by 70%

Achieved 40% revenue growth in the first year through improved operational efficiency, faster time-to-market, and reduced costs

Reduced engineering costs by $2.5M annually while maintaining and improving product quality

Eliminated engineering redundancy and streamlined design processes, reducing operational overhead by 60%

Improved code quality metrics: reduced bug rate by 45%, increased test coverage to 85%, and cut deployment failures by 80%

Technologies & Capabilities

AI AutomationDevOps TransformationCode RefactoringProcess OptimizationEngineering EfficiencyCI/CD PipelinesLegacy Modernization

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