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Description
Metal serves as a comprehensive, fully-managed machine learning retrieval platform ready for production. With Metal, you can uncover insights from your unstructured data by leveraging embeddings effectively. It operates as a managed service, enabling the development of AI products without the complications associated with infrastructure management. The platform supports various integrations, including OpenAI and CLIP, among others. You can efficiently process and segment your documents, maximizing the benefits of our system in live environments. The MetalRetriever can be easily integrated, and a straightforward /search endpoint facilitates running approximate nearest neighbor (ANN) queries. You can begin your journey with a free account, and Metal provides API keys for accessing our API and SDKs seamlessly. By using your API Key, you can authenticate by adjusting the headers accordingly. Our Typescript SDK is available to help you incorporate Metal into your application, although it's also compatible with JavaScript. There is a mechanism to programmatically fine-tune your specific machine learning model, and you also gain access to an indexed vector database containing your embeddings. Additionally, Metal offers resources tailored to represent your unique ML use-case, ensuring you have the tools needed for your specific requirements. Furthermore, this flexibility allows developers to adapt the service to various applications across different industries.
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
Yes
API Access
Has API
Yes
Integrations
OpenAI
Yes
Amazon Web Services (AWS)
No
Azure Marketplace
No
ChatGPT
No
ChatGPT Plus
No
ChatGPT Pro
No
Cocos Creator
Yes
Cohere
No
Coral
No
GameplayKit
Yes
Integrations
OpenAI
Yes
Amazon Web Services (AWS)
Yes
Azure Marketplace
Yes
ChatGPT
Yes
ChatGPT Plus
Yes
ChatGPT Pro
Yes
Cocos Creator
No
Cohere
Yes
Coral
Yes
GameplayKit
No
Pricing Details
$25 per month
Free Trial
No
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
Metal
Website
getmetal.io
Vendor Details
Company Name
Zilliz
Founded
2017
Country
United States
Website
zilliz.com
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
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
