I taught myself to run AI that prices freight, tracks my books, and powers my MBA, and to run it privately, on my own machine, without handing my data to anyone. Now I help small businesses do the same.
Brownsville, TX · Bilingual (English / Spanish) · MBA in Business Analytics, 2027 · Building toward Fractional Chief AI Officer and AI-consulting work. Also open to Data / BI roles.
I've been behind the wheel since 2007, when I earned my CDL Class A.
For years I ran under my own authority, and because I'd always loved Excel, I started building what I'd call dashboards today: simple sheets that told me exactly what each load would pay after fuel and costs. That instinct to measure everything never left. In 2023 I moved my freight over to Landstar to cut the paperwork and focus on the driving and the building.
Then AI showed up, and I leaned all the way in. I taught myself where to go, how to code, and how to actually ship things. My crude spreadsheets became professional tools that show me what works and what doesn't, and I expand them every single day. Every problem I solve opens the door to the next idea, and chasing that next idea is the part I genuinely enjoy.
That's who I am: an operator who builds. I've spent 20+ years leading teams (a 20-year Army career, a 40+ member platoon) and grew my freight business from $100K to $300K in revenue with data-driven decisions. Now, with an MBA in Business Analytics, I'm pointing all of it in one direction: helping other small businesses put AI to work the way I did, as a practical tool for real money decisions, not a buzzword.
Most small business owners know AI is powerful. One thing stops them: privacy. They don't want their client lists, financials, or proprietary work leaving their hands and landing in a public tool they don't control.
I get it, because I solved it for my own business. I run AI that keeps sensitive data on my own computer. You get the full power of AI without giving your information away.
Around the real work you already do, not a science project.
Set up so private information stays private.
The way I multiplied mine, one workflow at a time.
A web tool for shippers. The dock manager types in the order, picks the trailer, and gets back the complete load plan in seconds: a to-scale trailer diagram, the exact loading sequence for the forklift crew, strap counts by row, and weight and height checks, all before the first pallet leaves the rack.
I was picking up a flatbed load of roofing materials and watched the dock crew figure out the arrangement on the fly: what rides at the nose, what stacks on what, where the loose rolls go. All of that knowledge lived in people's heads. Get it wrong and you find out late, at the scale, at the strap check, or when freight comes back damaged. As the driver, I'm the one who straps it and hauls it legal, so I know exactly what a good load looks like.
A packing engine that knows the freight (pallet sizes, weights, what can bear weight, what crushes) and the rules of the road (payload limits, 8'6" height, center of gravity, strap working-load limits). It packs the trailer the way a good dock crew would: crush-sensitive foam at the nose, pyramid stacks of loose rolls braced at the rear, and the front row strapped as the backstop that braces everything behind it. Custom items can be added on the fly, and 34 automated tests keep the engine honest.
Every reload is forklift time, dock time, and driver detention. Every overweight or over-height surprise is a fine or a late delivery. This tool moves those mistakes from the dock, where they're expensive, to the screen, where they're free. It's the same playbook I used on my own business: find the spot where hours and dollars leak, then build the software that plugs it.
A market-intelligence dashboard built off load-board data that shows where freight is hot and where to position for the next backhaul.
A revenue and expense tracking system I built for my own trucking books, with a Google Sheet, Apps Script, and an iPhone shortcut all wired together.
A pricing engine that reads free U.S. freight market data and tells a broker what to charge to move a load: rate per mile, fuel surcharge, and margin.
For an MBA project I analyzed roughly 6 million shipments across air, rail, truck, and parcel, then determined the smartest mode by distance and shipment value.
A team of AI agents that power my MBA work. They hunt down credible articles and documents for my research, so my assignments are built on the most accurate, current data. They also turn my reading into MP3s I can listen to while I'm driving, and I ask questions about what I'm reading through a chatbot from the road.
A Python tool that turns a messy point-of-sale export into clean data and a ready-to-read sales report with a single command. It standardizes mismatched dates and prices, drops duplicates and broken rows, and accounts for every row so nothing disappears silently.
A lightweight Python tool that takes the raw, messy CSV a point-of-sale system exports and turns it into three usable files. It runs on the Python already built into your computer, so there is nothing to install and no monthly fee.
You run one line and point it at your export. It standardizes every date format, strips the dollar signs and commas off prices, tidies product names, removes duplicate orders, and pulls out broken rows (missing IDs, bad dates, zero prices). Then it hands you back a clean CSV, a plain-English report (revenue by product, by month, and top customers), and a machine-readable JSON.
What used to be an afternoon of copy-paste and find-and-replace becomes seconds. Every row is accounted for (kept plus skipped plus duplicates removed always equals rows read), and the report tells you exactly why anything was dropped, so you can trust the revenue figure. Build it once, reuse it forever.
Want to put AI to work in your business, or talk about a data role? I'm easy to reach.