Adding one attribute to a 300M-item catalog took days of rebuilds. Unifying vector and product data unlocked real-time hybrid search.
A second-hand fashion search engine manages a massive, fragmented catalog of over 300 million unique listings from external platforms that refreshes by more than a million items daily.
Maintaining separate databases for vector embeddings and catalog attributes created severe synchronization issues within the data ingestion pipeline....
“We rely on vector search. We’ll use a combination of a reverse image search, or an image plus text. We then generate an embedding of the product information, add weights to it, and apply that to a catalog using vector search.”
Browser extension for searching and aggregating secondhand fashion deals.
Multi-cloud developer data platform for building and scaling applications.
Beni's Unified product search is part of this use case:
Related implementations across industries and use cases
Daily updates delayed new content. A unified database now runs twice-daily refreshes with zero downtime.
Fragmented pipelines slowed cross-site suggestions. A unified AI vector database cut latency 90%, processing 1,500 queries per second.
Rigid data silos slowed engineering. A unified vector foundation now powers AI agents, accelerating development velocity 4x.
Fragmented pipelines slowed cross-site suggestions. A unified AI vector database cut latency 90%, processing 1,500 queries per second.
Scaling curation for 90M buyers was impossible. Now, experts build seed collections and Vertex AI expands them into millions of custom feeds.
A solo operator was firefighting volume. AI now resolves 50k monthly inquiries, freeing humans to handle complex enterprise cases.
Marketers spent two weeks manually updating battlecards. Now, AI synthesizes scattered win-loss signals to refresh them in hours.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.
Adding one attribute to a 300M-item catalog took days of rebuilds. Unifying vector and product data unlocked real-time hybrid search.
A second-hand fashion search engine manages a massive, fragmented catalog of over 300 million unique listings from external platforms that refreshes by more than a million items daily.
Maintaining separate databases for vector embeddings and catalog attributes created severe synchronization issues within the data ingestion pipeline....
“We rely on vector search. We’ll use a combination of a reverse image search, or an image plus text. We then generate an embedding of the product information, add weights to it, and apply that to a catalog using vector search.”
Browser extension for searching and aggregating secondhand fashion deals.
Multi-cloud developer data platform for building and scaling applications.
Beni's Unified product search is part of this use case:
Related implementations across industries and use cases
Daily updates delayed new content. A unified database now runs twice-daily refreshes with zero downtime.
Fragmented pipelines slowed cross-site suggestions. A unified AI vector database cut latency 90%, processing 1,500 queries per second.
Rigid data silos slowed engineering. A unified vector foundation now powers AI agents, accelerating development velocity 4x.
Fragmented pipelines slowed cross-site suggestions. A unified AI vector database cut latency 90%, processing 1,500 queries per second.
Scaling curation for 90M buyers was impossible. Now, experts build seed collections and Vertex AI expands them into millions of custom feeds.
A solo operator was firefighting volume. AI now resolves 50k monthly inquiries, freeing humans to handle complex enterprise cases.
Marketers spent two weeks manually updating battlecards. Now, AI synthesizes scattered win-loss signals to refresh them in hours.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.