Candid Garden is a digital garden for art and music—a search engine powered by semantic understanding and multimodal AI.
Use semantic search to discover artworks and songs that match your concepts, themes, or emotions. It tries to understand the meaning behind your queries and performs vector searches across a growing collection of over 54,000 artworks and 2,100 curated songs.
Beyond search, Candid Garden is a community (and soon a public library). You can ask joining our monthly Film Club. You can also add a Passage—shared reflections that connect visitors through art and music—or discover curated recommendations based on your interests. Each feature is designed to deepen your connection with art and foster meaningful cultural conversations.
It's built with love, not funding—for now. If it speaks to you, you can support the project and help unlock features like high-res image downloads via Buy Me a Coffee or PayPal Donate buttons below.
Hello! I'm Osman, the developer behind Candid Garden.
I'm based in Munich, Germany. I earned my Bachelor's degree in Economics from Yildiz Technical University in Istanbul, Turkey, before pursuing a Master's in Economics at Ludwig-Maximilians-Universität München (LMU).
Following my master's degree, I began doctoral research at LMU focused on automating the tagging of art images, building on crowd-sourced data from the Artigo project. My research explored training machine learning models to recognize not only pre-iconographic elements—like chair, clock, or human—but also abstract concepts in representational paintings.
The goal was to create a system that could respond to queries like: "Show me paintings that depict Maria from the 1400s to the 20th century," returning not only obvious portrayals but also subtle, symbolic representations.
I envisioned democratizing art interpretation—creating a tool that helps anyone, regardless of their art history background, understand the rich visual language and symbolism in art. For researchers, this addressed a practical challenge: the overwhelming volume of contemporary visual production that makes comprehensive analysis increasingly difficult.
While working on this research from 2018 onwards, I experimented with early AI models and achieved promising results. I transitioned into industry and gained hands-on experience with production-scale AI systems.
During my time in industry, the AI landscape evolved dramatically. The emergence of breakthrough technologies—CLIP from OpenAI, SegNet from Meta, and Large Language Models—transformed what's possible in multimodal AI. These advances brought the capabilities I had envisioned during my doctoral research within reach, but with power and sophistication far beyond what was achievable in 2018.
Witnessing this technological evolution reignited my passion for the original research questions that had driven me to pursue a PhD.
This technological evolution inspired me to create Candid Garden— a project that leverages today's state-of-the-art AI to realize the vision I had years ago.
My goal is to help people discover deeper connections with art— to explore different perspectives, connect with the emotions and history embedded in artworks, and begin their own journey of reflection and discovery. This project combines my economics background, research experience, and industry knowledge to create practical AI applications that serve real user needs.
I'm passionate about developing open-source AI tools that prioritize empathy, creativity, and shared understanding—technology built by people, for people.
Thank you for visiting Candid Garden. If this project resonates with you, I'd love to hear from you:
📬 hey[at]candidgarden.com