Software engineer turned entrepreneur.
Building tools that help people sell, create, and discover.
Orlando, FL & Malibu, CA
I've been writing software since 1992 and building my own companies since 2013. The pivot from engineer to entrepreneur started at 3 AM on December 26, 2012, when I launched MerchantWords — an Amazon keyword research tool that went on to help over 130,000 sellers find their customers. That moment changed everything for me, and I haven't looked back.
These days I spend my time incubating products across e-commerce, real estate, procurement, and whatever else catches my curiosity. I like solving problems that feel just out of reach.
The pioneer in Amazon keyword research. Real shopper search data powering 130,000+ entrepreneurs since 2012.
Amazon sellers ranging from solopreneurs launching their first product to established brands managing hundreds of SKUs. Anyone competing on Amazon needs an advantage—and that advantage starts with knowing what customers are actually searching for.
In 2012, I realized Amazon sellers were flying blind. Everyone was guessing at keywords, trying to reverse-engineer search volume from their competitors, or worse—missing opportunities entirely. I built MerchantWords to democratize access to real shopper search data that was previously only available to Amazon insiders.
We were first-to-market in Amazon keyword research (2012), and we remain unique: direct access to Amazon's search autocomplete data (what shoppers actually type), 130,000+ users over 12+ years, and direct integration with your Amazon workflow. Like all tools in this space we use estimates for some metrics, but our estimates come from real Amazon search patterns, not browser extensions or guesswork. Competitors came later; we have the longest track record.
Discover hidden keyword opportunities competitors miss. Understand true search volume instead of guessing. Rank for high-intent keywords that convert. Save hours researching competitors manually.
Keyword research for makers and creative entrepreneurs on Etsy and independent platforms. Discover exactly what your buyers are searching for to guide your product decisions.
The ideal MakerWords user is an Etsy seller — a maker who handcrafts jewelry, candles, home decor, or digital downloads and runs their shop as a serious side income or full-time business. They're not guessing what to make; they want data. Their frustration is that Etsy gives sellers almost nothing: no search volume, no competitive density scores, no way to know if a niche is tapped out or still wide open. They've tried eRank or Marmalead and walked away confused when the two tools show search volume estimates that disagree by 5x.
I built MerchantWords in 2012 because Amazon sellers were flying blind on keyword demand. Etsy sellers have the exact same problem in 2025, and the current tools are worse. eRank and Marmalead derive their "search volume" from browser extension installs — a tiny, self-selected sample that skews toward tool-using power sellers. We built MakerWords on top of Etsy's actual autocomplete API (10+ million keyword suggestions scraped) combined with live listing supply data from the Etsy API. When you put real demand signals against real competition depth, you get something those tools can't: an honest opportunity score.
Most Etsy keyword tools are keyword tools — you type something, you get a list. MakerWords is structured around niches. We clustered 2 million scored keywords into 356 distinct markets by analyzing which listings appear together in Etsy search results. From that, we built the "Make This, Not That" view: for any niche, we show you the better entry point versus the more crowded alternative. A tool that tells you "personalized name necklaces" has high demand is useless if it doesn't also tell you it has 40,000 competing shops with deep back-catalogs. We show both sides. The other thing nobody else does from real data: tag recommendations. Every Etsy listing has up to 13 tags. We mine the actual tags used by the top-ranking listings per keyword and surface patterns.
Opportunity score, not just volume — demand signal plus competition depth in one number, so you can quickly triage niches worth entering versus ones that are saturated. Niche-first navigation — browse by product category or maker tool and land directly in the relevant market cluster, not a keyword list. Tag intelligence from real winners — recommended tags are mined from actual top-ranking listings, not guessed from keyword co-occurrence. "Make This, Not That" comparisons — for each niche, we surface the cleaner opportunity versus the crowded adjacent market.
AI-powered Amazon listing optimization. Writes keyword-rich product listings in minutes using real customer search data.
Busy Amazon sellers who lack copywriting expertise but need keyword-rich listings. Often they're launching 10+ products at once or managing inventory that grew faster than their time to write quality descriptions.
MerchantWords solves keyword discovery. PowerListing solves the next bottleneck: actually writing the listing. Manual optimization took hours and still often missed keywords. AI can do this instantly.
Powered by real search data from MerchantWords, not generic AI training. Naturally incorporates keywords instead of stuffing them. Learns from your actual product and market, not generic templates.
Create SEO-optimized listings in minutes instead of hours. Keywords naturally integrated for conversion. Launch products faster while maintaining quality. Scale your catalog without hiring writers.
Bringing keyword intelligence to Latin American e-commerce markets.
Sellers on Mercado Libre — Latin America's dominant e-commerce platform — who are competing in one or more of 18 Spanish and Portuguese-speaking markets and have no idea what buyers are actually searching for. They're optimizing listings by gut feel, copying competitor titles, or skipping keyword research entirely because no self-serve tool has existed for this market. This is especially acute for cross-border sellers entering LATAM for the first time, who don't have the language intuition local sellers do.
Mercado Libre has 80 million active buyers across 18 countries and $28.9B in annual revenue — it's the Amazon of Latin America. But the keyword research tooling is years behind what Amazon sellers take for granted. The only real competitor, Nubimetrics, requires a sales call just to see pricing and is priced for enterprise. We built the tool that Mercado Libre sellers deserve: self-serve, transparent pricing, real data, no gatekeeping.
Our keyword database comes from crawling Mercado Libre's own autocomplete API across all 18 markets — 18.6 million unique keywords derived from what buyers actually type, not extrapolated from web search data. Volume estimates use the same depth/strength/prominence methodology behind MerchantWords, which has been validated at scale on Amazon. The tool is fully Spanish-first, designed for the reality of LATAM search behavior, not translated from an English-centric product.
18.6M keywords and 135M keyword-product appearances across all 18 ML markets — the most complete LATAM keyword dataset available. Volume estimates based on real autocomplete signal structure, not guesswork or scraped competitor data. Cover all 18 markets from Mexico to Argentina to Brazil in one tool — critical for sellers expanding across LATAM. Self-serve at $29/month — no sales call, no annual contract, cancel any time.
Review monitoring platform that centralizes customer feedback from Google, Yelp, TripAdvisor, and other review sites into one dashboard. AI-powered response suggestions and enterprise-wide analysis across locations.
Business owners and managers, especially multi-location enterprises. Anyone drowning in reviews scattered across Google, Yelp, TripAdvisor, industry-specific platforms, and social media who can't respond fast enough to stay on top of their reputation.
Business owners spend hours daily checking multiple review platforms. One critical review can tank ratings if it goes unresponded, yet finding and responding to reviews across all platforms is impossible to do manually. We built Fountain to consolidate everything into one place and arm managers with AI-suggested responses so they can stay on top of their reputation.
Unified dashboard across all platforms vs. checking each one separately. Flat-rate pricing that doesn't gouge multi-location businesses (competitors charge per location or per review). AI response suggestions save hours of thinking about what to say. Enterprise analytics to spot trends and patterns across your entire operation, not just single locations.
Spot reputation issues immediately before they spread. Respond faster to reviews with AI-powered suggestions. See patterns across all your locations. Manage your reputation without abandoning other work. Save hours daily on review management across multiple platforms.
Real estate tools for finding and evaluating property opportunities. Access 140M residential properties in our database via API to power your investment analysis.
Real estate investors, proptech builders, and analysts who need actual property data — not just MLS feeds locked behind broker agreements or scraped snippets that break the moment a site updates. Think a small fund evaluating 50,000 single-family rentals across the Sun Belt, or a developer building the next Zillow-killer who needs price history, tax records, and parcel data for 140 million homes without negotiating a six-figure enterprise contract first.
I kept watching friends and clients pay $5,000-$50,000/month for real estate data that was either incomplete, locked to a single MLS region, or wrapped in such restrictive licensing that they couldn't actually build anything useful. Meanwhile, all the data already existed publicly — it was just trapped behind anti-bot walls and balkanized across 800+ MLSes. Straply started as "what if one person with the right scraping infrastructure could just collect all of it, clean it, and sell access at a price that doesn't require a Series A?" The answer turned out to be yes — 140 million properties later.
Most "real estate data" companies sell you either MLS-licensed feeds (clean but expensive and regionally fragmented) or scraped data of dubious quality (cheap but inconsistent and often stale). Straply sits in the middle: a single, unified national database covering every residential property in the U.S., with price history, tax history, schools, and dozens of other fields normalized into one schema. No MLS contracts, no per-region licensing, no per-record fees that make experimentation impossible. One API, one schema, one price.
Full national coverage out of the gate — every U.S. residential property in one queryable API, not 50 regional contracts. Pricing that doesn't punish exploration — flat tiers based on usage, not per-record charges, so you can iterate freely. Real signal, not just listings — price history, tax history, and sale events for properties whether they're currently listed or not. Self-serve from day one — get an API key and start querying in under 5 minutes; no sales call required.
A mobile app to find the right food choices in Disney parks for picky eaters or allergy concerns.
Families with picky eaters, food allergies, or dietary restrictions who are planning a Disney park visit and dreading the food situation. The parent who already knows their kid will only eat chicken nuggets, or who has to navigate a nut allergy in an environment with 300 dining options and no easy way to filter. Also adults with celiac, vegan diets, or other restrictions who don't want to make dining their full-time job at the park.
Disney parks are enormous and dining options are endless — but if you're looking for something specific, the official app isn't built to help you filter by restriction or preference. Most parents figure out their kid's food options by asking in Facebook groups the week before. We built PickyMickey to be the resource that should have existed: every menu, every option, filterable by what actually matters to your family.
The Disney app shows you what's available. PickyMickey shows you what's available for your specific situation. That distinction — filtering by allergen, dietary preference, and picky-eater-safe options — is the entire product. We also stay updated as menus change seasonally, so you're not planning around options that no longer exist.
Find every menu item at every park location that fits your dietary restriction or allergy. Plan meals before you arrive so you're not making anxious food decisions in the middle of a hot, crowded park. Know which locations are most accommodating to your needs so you can build your day around them. Reduces the stress of traveling with dietary restrictions in an environment that already has enough variables.
A mobile app to keep track of friends and rides in Disney parks. Because the magic shouldn't include losing your group.
Disney park visitors going with a group — families with kids of different ages, friend groups with different ride preferences, anyone who's ever lost track of someone at a crowded theme park. The parent who wants to let their teenager wander independently but still know where they are. The group that always spends 20 minutes trying to figure out where to meet up.
Disney parks are huge, loud, and full of spotty cell service. Standard map apps are useless inside the park, and Find My Friends is great until you're trying to explain "I'm near the blue building past the castle" to six people via text. We built RideSpy because park navigation is a genuinely unique problem — real-time location in the context of the park map, not a generic street grid.
RideSpy is built around the Disney park layout specifically — attractions, lands, and the actual geography of the parks — not a generic GPS layer on top of Google Maps. It shows you where your group is relative to where you're trying to go, with context that makes sense inside the park. You see real-time ride status and get notifications the instant a ride breaks down, so you're not walking 10 minutes to a closed attraction.
Never lose people again — see friend locations on a map updated in real time. Smarter wait time decisions with real-time ride status plus friend proximity. Ride down notifications so you're not walking to closed attractions. Location-aware recommendations that suggest nearby rides based on where you actually are and your preferences.
Trip planning platform for Disneyland vacations. Plan itineraries, search attractions, find dining options, and get daily park strategy—all to help you bring the magic back to your visit.
Disneyland planners (families, couples, solo travelers) trying to maximize their vacation. Especially families with kids who want strategy without the overwhelm, or first-time visitors who don't know where to start.
Trip planning stress is real—information is scattered across 20+ websites, there are too many variables, and most planning tools are outdated or incomplete. ParkMagic consolidates everything so you plan once and enjoy fully.
Single platform that covers itineraries, attraction search, dining finder, daily park strategy, and more. Real-time data integration with Disney parks. Built specifically for Disneyland vs. generic trip planning tools.
Reduce planning stress by 90%. Create smart itineraries based on crowds and wait times. Find dining that fits your preferences and budget. Hit all priority attractions. Spend less time planning, more time enjoying the magic.
Surfacing procurement and bid opportunities so you never miss a contract.
The ideal ProcureTap user is a small-to-midsize contractor, IT consultant, facilities company, or service provider who wants government contracts but finds the sourcing process overwhelming. They know the work is out there — billions in RFPs, RFQs, and ITBs posted every month by federal agencies, state governments, hospitals, and universities — but the bids are scattered across hundreds of portals with no central place to find them.
Government procurement data is legally required to be public, but "public" doesn't mean accessible. A janitorial company in Ohio shouldn't need to check 15 different portals to find out what's open in their state. We built ProcureTap because aggregation itself is the product — not the data, which already exists, but the normalization, deduplication, and delivery of it in one place. The existing players (BidPrime, FindRFP) are either priced for enterprise ($10K+/yr) or built on dated UX that hasn't changed since 2008.
ProcureTap aggregates from 600+ sources — federal APIs, state portals, Bonfire, PlanetBids, Jaggaer, DemandStar, and dozens more — normalized into a single schema with consistent industry tags, due dates, and contact info. Competitors scrape a fraction of that and charge more for it. At $99/month we're priced at roughly 10% of BidPrime for comparable or broader coverage. The free tier (25 bid views/week) lets a contractor validate the data quality before spending anything.
Single search across 600+ sources — federal, state, local, international, and niche platforms all normalized and deduplicated. AI-powered keyword matching that surfaces bids with different terminology than what you typed. Industry-filtered browsing with 24 categories (construction, IT, janitorial, landscaping, etc.). Instant alerts on new matches so relevant bids land in your inbox the day they're posted.
Keyword analysis for the App Store. We're still ideating on how to build a tool that stands out in this crowded market.
This project is on hold while we evaluate the best approach to stand out in a very crowded ASO market. More details coming when we've solidified our direction.
Software Architect — built real-time secure messaging for healthcare.
Helped build the first platform to buy a car completely online.
Early days of local search and city guides on the web.
Where it all started — software engineering from the ground up.