Boothy.

The problem

Independent artists who sell at art markets and farmers markets rarely have time to log sales in an app mid-event. Most just write them down on a sheet of paper — product name and price — then face a manual, time-consuming slog to get that into any tool.

On top of that, sales scatter across cash, Venmo, and marketplaces like Poshmark, Etsy, and Depop, some without public APIs. Platforms like Shopify or Square only capture transactions run through their own software, so the artist never really knows how much they sold of a given product, size, or at which event — leaving inventory and production decisions to guesswork.

The solution

Boothy turns a photo of handwritten market-sales notes into structured transactions and dashboards, so artists can see what sold, how much they made, and what to bring next time. It's positioned not as one-off OCR but as a reusable data pipeline for indie artist commerce.

The artist defines a catalog, snaps a photo of their pen-and-paper record, and Boothy extracts each item, quantity, and price into an editable review table before anything is saved. Corrections feed back into the model over time (human-in-the-loop). A second flow lets users ask for a custom report in plain text and see a new chart appear on the dashboard.

How it works

The core is a single vision call feeding a dashboard. The user enters event name and dates, uploads one or more images, and the model extracts rows for a review table where every cell is editable before import. Extraction runs on Claude with data stored in Supabase.

Prompt iteration hardened the hardest cases: explicit rules for bundled transactions (splitting "Poch Waves $44" into separate priced items instead of assigning the full amount to the first), plus confidence scoring, review notes, source-line tracing, and an estimate of visible transactions to flag potential missing rows. Count matters as much as accuracy — a missed row is invisible if you only check what came back. Extraction accuracy climbed from a 72% average toward 90%, with user corrections forming a growing ground-truth set.

Who it's for

This is a B2B product for small, local artists who sell homemade goods in person at art and farmers markets and online. The ideal customer sells across multiple channels and needs an aggregation tool for insight into their sales.

Higher-value users need more integrations — Depop, Shopify, Square — and a higher subscription tier. Their goals are to maximize sales by understanding top channels, events, product lines, and sizes, and to optimize inventory by producing more of what sells. Boothy launches in the Honolulu and Bay Area markets, where the team already has connections.

Why it matters

The arts and crafts market sat at $45.26B in 2023, projected to reach $63.21B by 2029, with demand for non-AI art resurging in protest to AI-generated work. Boothy runs a $10/month subscription with a 14-day free trial, where trust and apparent value are imperative and word of mouth carries the early going.

The plan starts with a pilot of artists who currently track sales by hand, testing against real handwriting styles before broader release. Value is measured through successful imports, retention, repeat uploads, time saved, and trial-to-paid conversion — with a continuous loop where production feedback keeps improving extraction quality.

At a glance

Project

Boothy

Built by

Michael Keller

One-liner

Boothy turns artists' handwritten market-sales notes into structured transactions and dashboards so they can understand what sold, how much they made, and what to bring to future events.