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Description
Vectorize is a specialized platform that converts unstructured data into efficiently optimized vector search indexes, enhancing retrieval-augmented generation workflows. Users can import documents or establish connections with external knowledge management systems, enabling the platform to extract natural language that is compatible with large language models. By evaluating various chunking and embedding strategies simultaneously, Vectorize provides tailored recommendations while also allowing users the flexibility to select their preferred methods. After a vector configuration is chosen, the platform implements it into a real-time pipeline that adapts to any changes in data, ensuring that search results remain precise and relevant. Vectorize features integrations with a wide range of knowledge repositories, collaboration tools, and customer relationship management systems, facilitating the smooth incorporation of data into generative AI frameworks. Moreover, it also aids in the creation and maintenance of vector indexes within chosen vector databases, further enhancing its utility for users. This comprehensive approach positions Vectorize as a valuable tool for organizations looking to leverage their data effectively for advanced AI applications.
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
Integrations
Amazon S3
Yes
Amazon Web Services (AWS)
No
Azure Blob Storage
Yes
Azure Marketplace
No
ChatGPT
No
ChatGPT Plus
No
ChatGPT Pro
No
Cohere
No
Confluence
Yes
Discord
Yes
Integrations
Amazon S3
No
Amazon Web Services (AWS)
Yes
Azure Blob Storage
No
Azure Marketplace
Yes
ChatGPT
Yes
ChatGPT Plus
Yes
ChatGPT Pro
Yes
Cohere
Yes
Confluence
No
Discord
No
Pricing Details
$0.57 per hour
Free Trial
Yes
Free Version
Yes
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
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)
Yes
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
Vectorize
Founded
2023
Country
United States
Website
vectorize.io
Vendor Details
Company Name
Zilliz
Founded
2017
Country
United States
Website
zilliz.com
Product Features
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
