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<h1 class="text-4xl md:text-5xl font-bold leading-tight mb-6">
🌅 Building Semantic Search for 100k+ Creative Assets
</h1>
<p class="text-xl text-gray-600 dark:text-gray-400 leading-relaxed">
How I transformed a chaotic Dropbox archive into an AI-powered search system that understands concepts instead of filenames.
</p>
<div class="mt-6 pt-6 border-t border-gray-200 dark:border-gray-700">
<p class="text-sm text-gray-500 dark:text-gray-400">
By <span class="font-semibold text-gray-900 dark:text-white">Jameson Campbell</span>
</p>
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<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">The problem wasn’t a lack of assets. It was a lack of discoverability.</p>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">At <a href="https://custom.sockclub.com/" target="_blank" rel="noopener noreferrer" class="project-link underline">Sock Club</a>, we had more than 100,000 creative assets sitting in Dropbox. Years of beautiful work that was effectively invisible. Finding a specific legacy design meant digging through deeply nested folders, guessing filenames, or relying on tribal knowledge.</p>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">Designers searched by concept. Sales searched under pressure, often mid-email or mid-call. The system only understood filenames.</p>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">This is the story of how I turned that functionally locked archive into a semantic visual search system that understands conceptual meaning. By moving away from rigid folder structures and toward a system that can actually “see” our work, we replaced hours of redundant recreation with seconds of discovery.</p>
<p class="text-sm text-gray-500 dark:text-gray-400 italic mb-10">Logo credit: Baylor Meche & Rachal Berry</p>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">The Problem</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">While the archive was large, it was functionally locked. Filenames were inconsistent. Folder structures varied depending on who created them and when. Over time, this created a real operational bottleneck.</p>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Designers regularly recreated assets because finding originals took too long</li>
<li>• Sales had to interrupt designers to find relevant past work for clients</li>
<li>• New hires relied on tribal knowledge just to locate basic brand files</li>
</ul>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">We tested Dropbox Dash hoping for a quick fix, but it lacked the depth required for nuanced, semantic discovery of visual assets. It provided a search bar, not conceptual understanding.</p>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">To truly unlock the archive, we needed something purpose-built: an internal system that recognized meaning, not just metadata.</p>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Requirements</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">After working closely with designers and sales, I defined a small set of non-negotiable requirements.</p>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">User requirements</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Search by concept, not filename</li>
<li>• Fast results across the entire library</li>
<li>• Support PSDs, PNGs, and exports</li>
<li>• Secure access to original files</li>
<li>• Integration with HubSpot deals</li>
<li>• A pipeline that could process 100k+ assets without manual intervention</li>
</ul>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">The system needed to be simple, intuitive, and reliable. If it required training, it would fail.</p>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Architecture Overview</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">The system uses a shared mathematical “language” for both images and text, allowing users to search visual assets using natural language descriptions.</p>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">Tech stack</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• <a href="https://nextjs.org/" target="_blank" rel="noopener noreferrer" class="project-link underline">Next.js</a> frontend on Vercel</li>
<li>• <a href="https://fastapi.tiangolo.com/" target="_blank" rel="noopener noreferrer" class="project-link underline">FastAPI</a> backend on Vercel’s serverless Python runtime</li>
<li>• <a href="https://docs.cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-multimodal-embeddings" target="_blank" rel="noopener noreferrer" class="project-link underline">Google Cloud Vertex AI</a> multimodal embeddings</li>
<li>• <a href="https://www.pinecone.io/" target="_blank" rel="noopener noreferrer" class="project-link underline">Pinecone</a> for serverless vector search</li>
<li>• <a href="https://aws.amazon.com/s3/" target="_blank" rel="noopener noreferrer" class="project-link underline">AWS S3</a> for asset storage</li>
<li>• <a href="https://aws.amazon.com/cognito/" target="_blank" rel="noopener noreferrer" class="project-link underline">AWS Cognito</a> for authentication</li>
<li>• <a href="https://developers.hubspot.com/docs/api-reference/overview" target="_blank" rel="noopener noreferrer" class="project-link underline">HubSpot</a> API for CRM integration</li>
<li>• <a href="https://posthog.com/" target="_blank" rel="noopener noreferrer" class="project-link underline">PostHog</a> for usage analytics</li>
</ul>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">Data flow</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Assets migrate from Dropbox to S3</li>
<li>• Files are converted to PNG for previews and embedding</li>
<li>• Vertex AI generates high-dimensional embeddings</li>
<li>• Pinecone indexes vectors with rich metadata</li>
<li>• User queries are embedded and matched semantically</li>
<li>• The UI surfaces results with direct downloads and HubSpot context</li>
</ul>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Ingestion and Embedding Pipeline</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">Processing more than 100k assets required a pipeline that could survive failure.</p>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">Key challenges</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Staying within model rate limits</li>
<li>• Converting PSDs reliably</li>
<li>• Skipping corrupt or unusable files</li>
<li>• Recovering from long batch interruptions</li>
<li>• Detecting duplicates before embedding</li>
<li>• Handling PSDs that were effectively blank</li>
</ul>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">Design choices</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Batch execution with adjustable concurrency</li>
<li>• Exponential backoff and retry logic</li>
<li>• Dedicated PNG conversion pipeline</li>
<li>• Pinecone pre-checks to avoid duplicate vectors</li>
<li>• Metadata mapping for HubSpot integration</li>
<li>• Progress tracking for multi-hour runs</li>
</ul>
<div class="bg-gray-100 dark:bg-zinc-800 border-l-4 border-gray-300 dark:border-l-zinc-600 rounded-r-lg p-6 my-8">
<p class="text-lg text-gray-700 dark:text-gray-300">The pipeline processed more than 253k embedding units. Total compute cost was $25, reduced to about $8 after credits.</p>
</div>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Vector Database Strategy</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">Pinecone provided fast similarity search with minimal operational overhead.</p>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">Why Pinecone</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Serverless architecture</li>
<li>• Metadata-based filtering</li>
<li>• High read performance</li>
<li>• Smooth large-scale upserts</li>
</ul>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">Index structure</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• <a href="https://www.pinecone.io/learn/vector-similarity/" target="_blank" rel="noopener noreferrer" class="project-link underline">Cosine similarity</a> with 1,408-dimensional vectors</li>
<li>• Each asset receives a “digital fingerprint” representing its visual and semantic essence</li>
</ul>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">Conceptual vector example</h3>
<pre class="bg-gray-50 dark:bg-gray-800 rounded-lg p-4 overflow-x-auto text-sm leading-relaxed text-gray-800 dark:text-gray-200 border border-gray-200 dark:border-gray-700">[0.021, -0.114, 0.893, 0.004, -0.672, 0.318, … , 0.057]</pre>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">Values capture latent features so similar designs remain mathematically close, even when filenames and folders are unrelated.</p>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Search API</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">The FastAPI service handles:</p>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Text and image queries</li>
<li>• Embedding generation</li>
<li>• Vector retrieval</li>
<li>• Metadata hydration</li>
<li>• Authorization checks</li>
<li>• Secure access to original PSDs</li>
</ul>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">Why Vertex AI</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• High-quality multimodal embeddings</li>
<li>• Shared embedding space for text and images</li>
<li>• Strong benchmark performance</li>
<li>• Predictable latency</li>
<li>• Cost efficiency at scale</li>
</ul>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">Search results consistently return in under a second.</p>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Frontend Experience and Workflow</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">The interface is not just a search bar. It’s an operational tool that connects creative assets to business context.</p>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">High-value workflows</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Preventing redundant work by finding approved files instantly</li>
<li>• Handling zero-context client requests by reverse-searching images</li>
<li>• Surfacing complete brand histories for specific clients</li>
</ul>
<h3 class="text-2xl font-bold mb-4 mt-8 text-gray-900 dark:text-white">Core functionality</h3>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Unified search for text, images, and client names</li>
<li>• Direct links to HubSpot deals and internal projects</li>
<li>• "Explore similar designs" using embeddings</li>
<li>• Built-in asset flagging for quality control</li>
</ul>
<div class="my-8">
<img id="homeScreenImage" src="../assets/projects/SS_Home_Dark_Mode.png" alt="Home screen with unified search experience" class="w-full h-auto rounded-lg shadow-lg border border-gray-200 dark:border-gray-700">
<p class="text-sm text-gray-500 dark:text-gray-400 text-center mt-2">Home screen with unified search experience</p>
</div>
<div class="my-8">
<img id="searchResultsImage" src="../assets/projects/SS_Results_Dark_Mode.png" alt="A simple search for Denver airport instantly surfaces years of brand history" class="w-full h-auto rounded-lg shadow-lg border border-gray-200 dark:border-gray-700">
<p class="text-sm text-gray-500 dark:text-gray-400 text-center mt-2">A simple search for "Denver airport" instantly surfaces years of brand history, turning a needle-in-a-haystack search into a five-second win.</p>
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<div class="my-8">
<img id="previewModalImage" src="../assets/projects/SS_Modal_Dark_Mode.png" alt="A simple search for Denver airport instantly surfaces years of brand history" class="w-full h-auto rounded-lg shadow-lg border border-gray-200 dark:border-gray-700">
<p class="text-sm text-gray-500 dark:text-gray-400 text-center mt-2">A simple search for "Denver airport" instantly surfaces years of brand history, turning a needle-in-a-haystack search into a five-second win.</p>
</div>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Asset Quality Control</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">To maintain brand quality, I built a flagging system with four preset reasons. This calls out outdated or unusable assets within searches and gives designers a lightweight review workflow.</p>
<div class="my-8">
<img id="flaggingSystemImage" src="../assets/projects/SS_Flag_Dark_Mode.png" alt="The integrated flagging system allows designers to mark assets with knittability issues or outdated logos" class="w-full h-auto rounded-lg shadow-lg border border-gray-200 dark:border-gray-700">
<p class="text-sm text-gray-500 dark:text-gray-400 text-center mt-2">The integrated flagging system allows designers to mark assets with knittability issues or outdated logos, ensuring the team only references production-ready files.</p>
</div>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Performance and Reliability</h2>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Search latency: 300–600 ms</li>
<li>• Stable ingestion over multi-hour runs</li>
<li>• Zero-downtime deployments</li>
<li>• Full analytics and error tracking via PostHog</li>
</ul>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Cost Efficiency</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">The system runs for about $72 per month:</p>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Pinecone: $50</li>
<li>• Vercel: $20</li>
<li>• S3: $1–2</li>
<li>• Vertex AI: effectively zero after credits</li>
</ul>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">The architecture scales without major changes.</p>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Results</h2>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Search became ~10× faster</li>
<li>• The internal team now completes 1,000+ searches per week</li>
<li>• Designers stopped recreating work</li>
<li>• Fewer interruptions to senior team members</li>
<li>• Faster, more relevant sales follow-ups</li>
</ul>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">Adoption was organic. No training or rollout was required.</p>
<div class="bg-gray-50 dark:bg-gray-800 rounded-lg p-8 my-10 border border-gray-200 dark:border-gray-700">
<blockquote class="text-lg italic text-gray-900 dark:text-white mb-4">
"Sock Scout is phenomenal, by the way. I've used it many times this week and it has saved me so much time already. Thanks for building such an amazing tool for us!!"
</blockquote>
<p class="text-sm text-gray-600 dark:text-gray-400">Taylor Spence, Senior Designer</p>
</div>
<div class="bg-gray-100 dark:bg-zinc-800 border-l-4 border-gray-300 dark:border-l-zinc-600 rounded-r-lg p-6 my-8">
<p class="text-lg font-semibold text-gray-900 dark:text-white">The biggest validation: people used it without being asked.</p>
</div>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Lessons Learned</h2>
<ul class="space-y-3 text-lg text-gray-700 dark:text-gray-300 mb-8 ml-4">
<li>• Metadata is a byproduct, not a requirement</li>
<li>• UX drives adoption more than features</li>
<li>• Pipelines must be resilient by design</li>
<li>• Trust in search accuracy unlocks new workflows</li>
</ul>
<h2 class="text-3xl font-bold mb-6 mt-12 text-gray-900 dark:text-white">Final Takeaway</h2>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">Semantic search turns a static archive into a discovery engine. With modern AI tooling and a simple interface, a small team can build internal capabilities usually reserved for large engineering organizations.</p>
<p class="text-lg leading-relaxed mb-6 text-gray-700 dark:text-gray-300">This project reflects how I like to work: identifying real bottlenecks, designing pragmatic systems, and building end-to-end solutions that quietly make people’s work easier.</p>
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Published by <span class="font-semibold text-gray-900 dark:text-white">Jameson Campbell</span>
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Sales Operations Manager & AI GTM Systems Builder
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