#buildinpublic CashClutter is our Shipaton 2026 project: a native iPhone app for finding realistic resale opportunities in the things you already own, turning them into a focused cash plan, and tracking the money that actually arrives.
The gap between clutter and a marketplace
Most selling apps begin after you have chosen an item. That leaves the hardest questions unanswered: What in this room is worth the effort? What is likely to sell? Which combination could fund the amount I need? CashClutter starts there, before a listing exists.
The product is a financial utility rather than a general inventory manager. Every major screen is designed to answer a money question, from total potential value to estimated net proceeds after fees.
Step 1: sweep a space or scan one item
A user can point the camera around a room, focus on one object, or import photos. The first pass happens on the iPhone. CashClutter detects likely candidates, suppresses duplicates, and creates a reviewable session instead of silently treating every guess as fact.
LiDAR-capable iPhones can add spatial room context and a visual cash map, but the core workflow works on every supported iPhone.
Step 2: identify and value with uncertainty intact
After the user confirms the item, CashClutter connects identity and market evidence to a valuation. It shows an estimated range, recommended asking price, quick-sale price, expected net after fees, liquidity, comparable count, and confidence.
That range matters. A resale estimate can look authoritative even when evidence is thin, so the interface separates what is known from what is inferred and never promises a sale price.
Step 3: build a plan for a real cash goal
A pile of values is interesting; a plan is useful. The user sets a target and deadline, and the goal optimizer selects a practical combination of items. The plan can favor fewer listings, faster sales, or more potential cash while showing the tradeoff.
Step 4: prepare the listing without taking control away
Sell Ready AI prepares photo guidance, a title, description, item specifics, and marketplace-aware pricing. The user can edit and copy everything, save prepared photos, or open a marketplace composer where supported. CashClutter never posts or completes a sale on the user's behalf.
Step 5: follow value through to net cash
Listings, offers, sale price, fees, shipping, and net earnings stay connected to the item and goal. This closes the loop between an estimated opportunity and the amount the user actually earned.
How we are building it
The iPhone app uses SwiftUI, SwiftData, Vision, StoreKit, optional RoomPlan and LiDAR capture, and strict provider boundaries for paid AI and market data. Cloudflare Workers provides the service boundary, Workers AI handles structured identification and listing copy, and D1 stores hashed access, idempotency, and photo-free calibration data.
RevenueCat owns production purchase execution and the Pro entitlement. A deterministic bundled provider keeps the complete app demonstrable, testable, and useful without depending on a live service during every development run.
Privacy is part of the workflow
Camera frames are analyzed on device first. Only selected stills needed for identification leave the iPhone, with faces and sensitive text redacted where detected. Server-side raw images are deleted within 24 hours by default, analytics are off by default, and CashClutter does not sell data or track users across apps.
What comes next
The next work is better licensed sold-comparable data, stronger foreground photo processing, improved calibration from photo-free sale outcomes, localized marketplace profiles, and collaborative household inventories. We will keep sharing the decisions, the hard edges, and the lessons as CashClutter moves toward launch.
#buildinpublic Shipaton 2026 is the deadline. A trustworthy camera-to-cash product is the goal.