Pool, a Lisbon-built consumer app that uses AI to turn a phone's screenshot pile into a searchable, categorized archive, launched on iOS today as a free download. The startup is backed by just over $2 million in pre-seed funding from General Catalyst, Kima Ventures, Paris-based Source Ventures, and angels including Winston Du, Julian Blessin, and Thomas Ricouard. The pitch is narrow and specific: stop treating the Camera Roll as a graveyard for recipes, outfits, tweets, and product ideas you meant to revisit.
After granting photo access, users see their screenshots sorted into clusters Pool calls 'pools,' generated from the products, places, and concepts each person has saved. The app then tries to reattach each screenshot to its original source — linking a screenshotted product back to the retailer's page, or pulling the ingredients out of an Instagram recipe clip. Screenshots are also treated as memories with a shelf life: a ticket barcode can fade out after the event passes, while a flyer for an upcoming show triggers an agent that surfaces the ticketing link.
Co-founder Maxime Junique said the idea came from a habit he and co-founder Piet Terheyden shared and could never solve: they would screenshot something to remember it, then lose it.
Key facts
- 01Pool launched its iOS app today, sorting users' screenshots into AI-generated categories called 'pools' tied to products, places, and ideas.
- 02The startup has raised just over $2 million in pre-seed funding from General Catalyst, Kima Ventures, and Paris-based Source Ventures.
- 03Pool was first built around three years ago in Lisbon, then shelved when founders Maxime Junique and Piet Terheyden pivoted to B2B SaaS.
- 04The founders' studio also built CRM software Waitless, which was acquired last year, before returning to Pool as AI matured.
- 05A second, agentic app is in development, with Pool's rubber-duck mascot becoming the brand for the personal-assistant follow-up.
The two met years ago in a co-working space and built the first version of Pool around three years ago in Lisbon, cranking out the landing page, site, and initial build over a couple of weeks while living out of a van. They shelved the project when they realized they needed revenue first, pivoted into B2B SaaS through their Spinoff Studio, and shipped other products — including the CRM tool Waitless, which was acquired last year.
What pulled Pool off the shelf was the maturation of AI models capable of making sense of personal, unstructured visual data. Pool sits in a small but growing category of AI-era bookmarking tools alongside mymind, Fabric, and Raindrop, but it is the only one focused squarely on the screenshot — the most casual, least-organized save anyone makes on a phone.
Junique frames the dataset itself as the strategic bet.
Search inside the app is handled either through traditional queries or a built-in AI assistant. The founders plan to spin the agentic side into a second, separate app — a personal assistant where Pool's rubber-duck mascot, currently the press-and-drag entry point at launch, becomes the brand. The team flew from Lisbon to San Francisco in late May to meet investors about the next stage.
The model carries the standard caveats for a consumer AI app built on personal data. Pool needs broad photo-library access to work, the link-recovery feature depends on scraping or matching against live web sources that can break, and the 'memory' decay logic is only as good as the model's read of what each screenshot actually is. None of those are dealbreakers, and most are the sort of rough edges that get smoothed in successive releases. A bigger open question is retention: bookmarking apps have a long history of strong launches followed by users drifting back to the Camera Roll.
The interesting wedge here is not the app itself but the data category. Email, calendar, and chat are saturated battlegrounds for AI assistants; the screenshot folder is not. If Pool can prove users will pay — or share enough behavior — to make the screenshot a useful signal, the second agentic app becomes the real product, and the first one becomes the data pipe. At $2 million in pre-seed, that is exactly the bet General Catalyst and Kima are funding.
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