New app Pool transforms your screenshots into organized, actionable collections
Table of Contents
You might want to know
How can an app make the countless screenshots on your phone easier to find and act on?
What role does AI play in turning screenshots into useful, time-sensitive reminders or links?
Main Topic
For many people, a phone’s Camera Roll doubles as both a photo album and a chaotic repository for things found online: recipes, fashion ideas, travel notes, quotes, tweets, product suggestions, and more. A new app called Pool aims to bring order to that clutter by reorganizing screenshots into personalized collections and using machine learning to make them actionable. To begin, users grant the app access to their photos. Pool then scans the images and groups them into thematic "pools" based on the products, places, or content captured in those screenshots, creating a structure that reflects each user’s unique interests and saved items.
Pool sits among a wave of modern bookmarking tools that rethink how we save and retrieve online content. Services such as mymind, Fabric, and Raindrop let people categorize links and images, but Pool concentrates specifically on screenshots and leverages AI to reconnect those images with their original sources. That focus enables the app to do more than store; it helps users rediscover items and follow up on actions they may have intended when they took the screenshot.
Once screenshots are imported into Pool, the app attempts to locate the original links or content associated with each image. For example, a screenshot of an item you were considering buying can be matched to the retailer’s product page. A captured recipe from Instagram can be traced back to the post containing ingredients and instructions. By mapping screenshots to their sources, Pool reduces the friction between saving something and acting on it later.
The concept grew from a simple, relatable problem described by Pool co-founder Maxime Junique: he and co-founder Piet Terheyden frequently took screenshots to remember things but then struggled to find those images again. Their conversations with friends revealed the behavior was common—people routinely capture design ideas, inspiration, and reference material, then forget where to find them. That insight motivated the founders to create an app that treats screenshots as a meaningful personal dataset rather than ephemeral clutter.
Pool originated as the first product from Spinoff Studio, the founders’ product and design workshop, roughly three years ago. The initial version was sketched and built quickly while they were living and working out of a van in Lisbon—enough to produce a landing page and prototype. Practical business needs then led the studio to prioritize revenue-generating projects, shifting focus to B2B SaaS and placing Pool on the back burner. The studio continued producing other tools, including a CRM called Waitless, which was later acquired.
What brought Pool back into focus was the rapid progress in AI capabilities. Junique says that machine learning advances made the idea of extracting structured value from largely unstructured, personal image collections viable. The founders saw screenshots as a rich but underutilized dataset—emotional, personal, and full of intent—that hasn’t been the central focus of most AI-driven productivity efforts, which typically target emails, financial records, or chat logs. Pool's approach treats this visual, personal data as an opportunity to deliver new utility.
A distinctive aspect of Pool’s design is how it handles the temporal relevance of screenshots. Some captures are time-sensitive—like a barcode for an event ticket—while others are longer-term references, such as inspiration images. Pool’s system recognizes that certain items may lose relevance after an event passes and can deprioritize or remove them accordingly. At the same time, the app can proactively surface actions: if you saved a flyer for an upcoming event, Pool can help locate where to purchase tickets and link directly to the ticketing provider.
Users can search their pools or ask Pool’s integrated AI assistant to find items or suggest next steps. The team plans to expand this functionality into a second app that will act as a more agentic personal assistant. Pool’s playful mascot—a small rubber duck used to open the app—will form part of the identity for the forthcoming assistant, which aims to take a more proactive role in helping users manage saved content.
The founders remain active across Europe, and while the early development phase involved a transient, van-based lifestyle, the company has since matured. Pool has also secured early-stage funding: the startup raised a pre-seed round of a little over $2 million from investors including General Catalyst, Kima Ventures, Source Ventures, and several angel backers. The app launched on iOS and is available as a free download, offering users an immediate way to test how their screenshots can be repurposed into organized, searchable, and actionable collections.
This key insight significantly impacts the understanding of personal data: screenshots represent a deeply personal and intent-rich dataset that AI can analyze to bridge the gap between saving and acting. Pool’s model reframes how we think about on-device archives, not merely as passive storage but as dynamic resources that can be queried and acted upon.
Key Insights Table
| Aspect | Description |
|---|---|
| Key Fact 1 | Pool organizes screenshots into personalized "pools" and links them back to original sources. |
| Key Fact 2 | The app uses AI to rediscover content, determine temporal relevance, and suggest actions like where to buy tickets or view recipes. |
Afterwards...
Looking forward, there are several technology and research directions that could amplify the value of apps like Pool. Improvements in on-device AI and privacy-preserving machine learning would allow richer analysis of personal images without exposing sensitive data to external servers. Advances in multimodal retrieval—combining visual, textual, and contextual signals—can make matching screenshots to original content faster and more accurate. Integrations with calendar, ticketing, shopping, and recipe platforms could turn passive collections into automated workflows that reduce friction for everyday tasks.
Exploring better user controls around retention and relevance, as well as clearer consent models for data access and linking, will also be important as these tools handle more personal, emotional datasets. As personal data becomes more actionable, balancing utility with privacy and user agency should remain a priority for developers and researchers alike.