Ricerca semantica
Crea applicazioni di ricerca AI dinamiche basate sulla ricerca semantica con il database vettoriale Zilliz Cloud (Milvus completamente gestito)
Semantic Search with Zilliz Cloud Vector Database
Semantic search uses NLP algorithms to understand user query intent and meaning. Easily craft a semantic search engine using Zilliz Cloud for streamlined data management, swift retrieval, system reliability, and more.
Built-in Vectorization Pipelines for AI-powered Search
Zilliz Cloud’s built-in pipelines convert documents into searchable vector embeddings, seamlessly navigating from data preparation to chunking, model selection, and transformation.
Robust Vector Retrieval for Optimal Search Experience
Achieve a 10x performance boost on Zilliz Cloud with advanced indexing algorithms, ensuring millisecond-level latency for prompt user interactions. Elevate your AI-bases search experience now!
Offer Real-Time Search Results with Unparalleled Precision
Ensure consistently up-to-date search results with unparalleled precision using range search, hybrid vector search and scalar filtering, seamless data management within Zilliz Cloud.
Effortless Scaling for Limitless Business Expansion
Say goodbye to data size concerns with Zilliz Cloud. The computing and storage resources seamlessly and independently scale to align with your budget and evolving needs.
Start with Simplicity and Amplified Productivity
Launch a large-scale similarity search service in minutes with user-friendly SDKs in multiple languages and streamlined data operations, ensuring an intuitive user experience.
Always On, Always Reliable
Build resilient AI search engines without interrupted services with multiple replicas, isolating system components, and robust backup and sync capabilities.
Come Zilliz Cloud alimenta la ricerca semantica？
Un motore di ricerca semantica basato su Zilliz funziona nei seguenti modi:
- I documenti vengono acquisiti in Zilliz Cloud.
- L’Ingestion Pipeline integrata di Zilliz Cloud converte i documenti in embedding vettoriali e li archivia nelle raccolte di Zilliz Cloud.
- L’utente effettua una query.
- La Search Pipeline integrata di Zilliz Cloud converte le query degli utenti in embedding vettoriali e le invia a Zilliz Cloud per il recupero per similarità.
- Zilliz Cloud recupera i risultati Top-K più pertinenti confrontando la distanza spaziale tra la query dell’utente e i vettori dei documenti.
- Zilliz Cloud restituisce i risultati Top-K agli utenti.
Storie di Successo
I leader del settore in tutto il mondo utilizzano Milvus o Zilliz (Milvus gestito) per potenziare le loro applicazioni con funzionalità avanzate di ricerca semantica.
Super Low Latency
in semantic search
Enhanced Scalability
in vector data storage
Faster and More Reliable
in image indexing
10x Smarter
search experience
Improved
user experience
Enhanced
scalability and reliability
<95 milliseconds
end-to-end query latency
<10 seconds
to ingest 3 million vectors
Enable
real-time threat detection
Flexible Scaled
with separated compute and storage
Enhanced
query precision with hybrid search
Accelerated feature deployment
with the leading open-source community
10x faster
in vector retrieval speed
> 95%
in news classification accuracy
Less memory consumption
for faster responses and reduced cost
Super Low Latency
in semantic search
Enhanced Scalability
in vector data storage
Faster and More Reliable
in image indexing
10x Smarter
search experience
Improved
user experience
Enhanced
scalability and reliability