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.
Data silos across 300+ products made navigating fiscal regulations slow. A unified AI assistant now securely answers complex user queries.
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.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
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.
Data silos across 300+ products made navigating fiscal regulations slow. A unified AI assistant now securely answers complex user queries.
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.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.