Real projects that delivered real results.

Every project here started with a business problem, not a technology choice. These examples show how I've used automation, custom software, and AI to reduce manual work, improve consistency, and help teams move faster.

Custom Software · Workflow Automation · AI integration

Content operations platform

Problem

A content agency relied on separate tools and manual review to process interview transcripts, develop content ideas, and prepare client follow-ups. The workflow was slow, fragmented, and prone to errors, with delays at each handoff between contractors.

Solution

I designed and built a secure internal web application that manages the complete interview-to-ideation workflow. It includes transcript processing, automated ideation, follow-up email generation, user management, administrative controls, and audit logging. I also implemented authentication, access controls, cloud deployment, and monitoring.

Outcome

The platform reduced transcript-processing time by more than 80 percent, removed 3 days from an 8-day project timeline, and saves approximately $2,500 per month. It has since expanded to support additional parts of the agency’s content-production workflow.

Application modernization · Authentication · Cloud deployment

Freelancer management tool

Problem

A company’s prototype for managing freelancer availability was hosted on a platform that lacked the access controls and flexibility needed for production use. The system was difficult to secure, maintain, and expand.

Solution

I migrated the application to production infrastructure, restructured the codebase for maintainability, implemented Google OAuth authentication, and added features that made the tool easier to use and administer.

Outcome

The company now has a secure, maintainable freelancer-management application that can be expanded as its operational needs evolve.

AI workflow design · Document automation · Quality assurance

Case study generation platform

Problem

A content agency’s AI-assisted case study workflow produced inconsistent results and frequently failed to follow client-specific instructions. Manual document formatting introduced additional errors, leaving editors to find and correct the same problems repeatedly.

Solution

I designed a multiphase workflow that separates AI-assisted drafting from document production. The AI generates structured content, a Python application populates a 28-section template, and an automated audit checks the result against client-specific content and style rules.

Outcome

The workflow reduced drafting and formatting time from 2.5 hours to approximately 15 minutes. Automated checks now catch recurring violations before editorial review, freeing editors to focus on accuracy, narrative quality, and other work that requires human judgment.

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