Case Studies
DEEP DIVES INTO PRACTICAL
AI WORKFLOW PROJECTS
Full breakdowns of how I approach problems. From discovery and research through to solution design, tradeoffs, and results.
TalkOps Voice AI Platform — End-to-End Product Case
How I designed and built a commercial voice AI agent platform from scratch — from blank repo to white-label B2B product — covering system architecture, key product decisions, and the hard tradeoffs of building real-time infrastructure under commercial pressure.
Key insight
The real product was not the voice agent technology — competitors had similar capabilities. The product was the operational layer that made deploying and managing voice agents fast and repeatable. Whoever reduced deployment time from weeks to days would win the early market.
Super Enrich: From Open-Source Scraping Demo to Multi-Provider Enrichment Tool
Super Enrich started as Fire Enrich, an open-source demo Firecrawl built to show off their scraping API. I forked it and spent the following weeks turning a single-user, single-provider demo into something that could run for real people: pluggable scraping and LLM providers, full authentication, and the security hardening a public tool needs that a demo never did.
Key insight
The gap wasn't AI quality. Fire Enrich's phased pipeline, each stage building on what the last one verified instead of asking one model call to guess everything at once, already produced solid extractions. The actual blocker was distribution: one provider pair, no concept of a user, no hardening for public traffic. That's a much smaller problem than "build a better enrichment engine," and it's the one I actually had to solve.