Projects
Selected Work
Real problems, real solutions, real outcomes. Each project tells the full story.
Autonomous Customer Support Agent
Built an AI agent that handles 80% of customer support tickets autonomously for an ecommerce brand.
Context
A mid-size ecommerce brand was spending $15K/mo on customer support with 48-hour average response times. They needed faster responses without sacrificing quality.
Solution
Designed a multi-agent system with specialized agents for order status, returns, product questions, and escalation. Built with LangChain + GPT-4, with a custom knowledge base trained on 2 years of support history.
Stack
Outcome
80% ticket automation rate. Average response time dropped from 48 hours to 2 minutes. Support costs reduced by 60%.
What I'd improve next
Add proactive outreach — the agent could detect potential issues (delayed shipments) and reach out before customers complain.
AI Analytics SaaS MVP
Took a SaaS analytics tool from concept to 200+ beta users in 6 weeks.
Context
A founder had a vision for an AI-powered analytics tool that could explain data trends in plain English. They had a slide deck and $20K budget.
Solution
Built a full-stack Next.js application with AI-powered data analysis. Users upload CSV/connect databases, and the AI generates insights, charts, and plain-English explanations.
Stack
Outcome
Launched on time. 200+ beta signups in first month. $8K MRR within 3 months.
What I'd improve next
Add collaborative features — team sharing, comments on insights, and scheduled reports.
Ecommerce Conversion Rate Overhaul
Increased conversion rate by 40% for a DTC skincare brand through systematic UX and funnel optimization.
Context
A DTC skincare brand doing $80K/mo was struggling with a 1.2% conversion rate despite strong traffic. Their Shopify store had grown organically without strategic design.
Solution
Conducted a full conversion audit, redesigned product pages with social proof, optimized the checkout flow, implemented exit-intent offers, and set up proper analytics tracking.
Stack
Outcome
Conversion rate increased from 1.2% to 1.68% (40% improvement). AOV increased by 22% through upsell implementation.
What I'd improve next
Implement AI-powered product recommendations based on browsing behavior and purchase history.
Content Automation Pipeline
Built an AI content pipeline that produces 100+ pieces of content per week across 5 channels.
Context
A marketing agency was manually creating content for their clients, spending 40+ hrs/week on repetitive content tasks across social, email, and blog.
Solution
Designed an automated pipeline: AI generates drafts trained on each client's brand voice, routes through human review, then auto-publishes via API integrations with Buffer, Mailchimp, and WordPress.
Stack
Outcome
Content production increased 5x. Manual work reduced from 40 to 8 hrs/week. Client satisfaction scores increased.
What I'd improve next
Add performance feedback loop — use engagement data to automatically improve content generation prompts.
Complete Brand Identity System
Created a comprehensive brand system for a fintech startup that unified their visual identity across all touchpoints.
Context
A fintech startup had inconsistent branding across their app, website, marketing materials, and social presence. This was hurting trust and recognition.
Solution
Developed a complete brand system including logo, typography, color system, component library, marketing templates, and brand guidelines document.
Stack
Outcome
Unified brand presence across all channels. Brand recognition score improved by 35% in customer surveys.
What I'd improve next
Build an AI-powered brand guardian tool that automatically checks new content for brand consistency.
Marketing Attribution System
Built a custom multi-touch attribution system that revealed the true ROI of each marketing channel.
Context
An ecommerce brand spending $50K/mo on ads couldn't accurately attribute revenue to specific channels and campaigns. Last-click attribution was misleading their budget decisions.
Solution
Built a custom attribution system using a data warehouse approach. Collected touchpoint data across all channels, implemented multiple attribution models, and built a dashboard for comparing models.
Stack
Outcome
Discovered 30% of ad spend was going to channels with negative ROI. Reallocation led to 25% improvement in overall ROAS.
What I'd improve next
Add AI-powered budget allocation recommendations based on predicted channel performance.
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