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Average Ratings 0 Ratings

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features
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support

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Write a Review

Description

Integrate semantic relevance alongside user feedback to effectively extract the best document segments in your retrieval-augmented generation framework. Additionally, merge semantic relevance with document recency in your search engine, as newer content is often more precise. Create a dynamic, personalized e-commerce product feed that utilizes user vectors derived from SKU embeddings that the user has engaged with. Analyze and identify behavioral clusters among your customers through a vector index housed in your data warehouse. Methodically outline and load your data, utilize spaces to build your indices, and execute queries—all within the confines of a Python notebook, ensuring that the entire process remains in-memory for efficiency and speed. This approach not only optimizes data retrieval but also enhances the overall user experience through tailored recommendations.

Description

Searching and analyzing structured data is easy; however, over 80% of generated data is unstructured, requiring a different approach. Machine learning converts unstructured data into high-dimensional vectors of numerical values, which makes it possible to find patterns or relationships within that data type. Unfortunately, traditional databases were never meant to store vectors or embeddings and can not meet unstructured data's scalability and performance requirements. Zilliz Cloud is a cloud-native vector database that stores, indexes, and searches for billions of embedding vectors to power enterprise-grade similarity search, recommender systems, anomaly detection, and more. Zilliz Cloud, built on the popular open-source vector database Milvus, allows for easy integration with vectorizers from OpenAI, Cohere, HuggingFace, and other popular models. Purpose-built to solve the challenge of managing billions of embeddings, Zilliz Cloud makes it easy to build applications for scale.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) No 
Azure Marketplace No 
ChatGPT No 
ChatGPT Plus No 
ChatGPT Pro No 
Cohere No 
Coral No 
Google Cloud Platform No 
HoneyHive No 
Hugging Face No 
IBM watsonx.data No 
Java No 
Milvus No 
OpenAI No 
PyTorch No 
Python Yes 
Weaviate Yes 

Integrations

Amazon Web Services (AWS) Yes 
Azure Marketplace Yes 
ChatGPT Yes 
ChatGPT Plus Yes 
ChatGPT Pro Yes 
Cohere Yes 
Coral Yes 
Google Cloud Platform Yes 
HoneyHive Yes 
Hugging Face Yes 
IBM watsonx.data Yes 
Java Yes 
Milvus Yes 
OpenAI Yes 
PyTorch Yes 
Python No 
Weaviate No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$0
Zilliz Cloud on AWS
Compute Unit (CU) - $0.259 / hour
Storage - $0.025 / GB per month

Zilliz Cloud on Google Cloud
Compute Unit (CU) - $0.215 / hour
Storage - $0.02 / GB per month
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Superlinked

Founded

2021

Country

United States

Website

superlinked.com

Vendor Details

Company Name

Zilliz

Founded

2017

Country

United States

Website

zilliz.com

Product Features

Database

Backup and Recovery Yes 
Creation / Development No 
Data Migration Yes 
Data Replication No 
Data Search Yes 
Data Security Yes 
Database Conversion No 
Mobile Access No 
Monitoring No 
NOSQL No 
Performance Analysis No 
Queries Yes 
Relational Interface No 
Virtualization No 

Alternatives

Alternatives

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Milvus Reviews

Milvus

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