Real Automations, Built for Real Businesses

The Challenge

A full-time content creator was spending hours every week hunting down brand and sponsor leads, writing pitch emails from scratch, and manually tracking who'd replied. Follow-ups slipped through the cracks, her tone was inconsistent across messages, and every hour spent on outreach was an hour not spent creating content.

The Build

I built an AI agent that finds relevant brand and sponsorship leads, drafts personalized outreach messages written in her voice, and logs every conversation in a shared tracker. The agent queues follow-ups automatically on a set cadence and surfaces any warm reply for her to review and approve before anything goes out — she stays fully in control, but never has to start from a blank page.

The Challenge

Every incoming job request arrived as a scattered mix of emails, phone calls, and photos — part dimensions, coating type, quantity, and turnaround buried across formats. Quoting meant manually re-typing those specs into a spreadsheet and running the math by hand, which took days and led to inconsistent pricing on similar jobs.

The Build

I built an AI-driven intake pipeline that reads incoming requests — including attached photos and spec sheets — and automatically extracts the part details, coating type, and quantity needed to price the job. It runs that data through the shop's existing pricing logic, generates a formatted quote, and logs everything in a shared tracker so the team can follow up without re-entering anything.