Collect and organize reference images on a shared virtual whiteboard

Executive Summary

Designers, marketers, product teams and independent creators waste hours assembling and re-finding reference images across Slack, Google Drive, Figma, and phone galleries, which slows ideation and increases context switching. There are roughly 300 million knowledge workers who use visual references, implying a $15.0B addressable market at about $50/year per user. You could build a shared virtual whiteboard optimized for reference images that combines frictionless ingestion, collaborative annotation, and AI-powered capabilities - embeddings-based image similarity, automatic tagging from vision models, and deduplication - plus integrations with Slack, Figma, cloud drives, and mobile uploads. Core product priorities should be search accuracy, lightweight collaboration features like persistent moodboards and comment threads, and exportable boards for client reviews. This market is attractive now because advances in embeddings and vision models make image similarity and auto-tagging practically useful, remote creative collaboration is increasing, and the creator economy is expanding willingness to pay for niche productivity tools. To stand out, prioritize first-run experience and search relevance - for example, tuned combined vision-text embeddings and human-in-the-loop training on creative workflows - and solve workflow integration and rights metadata so teams can use assets confidently. Strengths are clear product-market fit and high revenue potential if you capture small teams and independent creators, but expect medium competition, nontrivial acquisition costs, and a realistic 12-24 month roadmap to reach product-market fit and healthy unit economics.