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What is Metal?

Metal acts as a sophisticated, fully-managed platform for machine learning retrieval that is primed for production use. By utilizing Metal, you can extract valuable insights from your unstructured data through the effective use of embeddings. This platform functions as a managed service, allowing the creation of AI products without the hassles tied to infrastructure oversight. It accommodates multiple integrations, including those with OpenAI and CLIP, among others. Users can efficiently process and categorize their documents, optimizing the advantages of our system in active settings. The MetalRetriever integrates seamlessly, and a user-friendly /search endpoint makes it easy to perform approximate nearest neighbor (ANN) queries. You can start your experience with a complimentary account, and Metal supplies API keys for straightforward access to our API and SDKs. By utilizing your API Key, authentication is smooth by simply modifying the headers. Our Typescript SDK is designed to assist you in embedding Metal within your application, and it also works well with JavaScript. There is functionality available to fine-tune your specific machine learning model programmatically, along with access to an indexed vector database that contains your embeddings. Additionally, Metal provides resources designed specifically to reflect your unique machine learning use case, ensuring that you have all the tools necessary for your particular needs. This adaptability also empowers developers to modify the service to suit a variety of applications across different sectors, enhancing its versatility and utility. Overall, Metal stands out as an invaluable resource for those looking to leverage machine learning in diverse environments.

What is Klee?

Unlock the potential of a secure and localized AI experience right from your desktop, delivering comprehensive insights while ensuring total data privacy and security. Our cutting-edge application designed for macOS merges efficiency, privacy, and intelligence through advanced AI capabilities. The RAG (Retrieval-Augmented Generation) system enhances the large language model's functionality by leveraging data from a local knowledge base, enabling you to safeguard sensitive information while elevating the quality of the model's responses. To configure RAG on your local system, you start by segmenting documents into smaller pieces, converting these segments into vectors, and storing them in a vector database for easy retrieval. This vectorized data is essential during the retrieval phase. When users present a query, the system retrieves the most relevant segments from the local knowledge base and integrates them with the initial query to generate a precise response using the LLM. Furthermore, we are excited to provide individual users with lifetime free access to our application, reinforcing our commitment to user privacy and data security, which distinguishes our solution in a competitive landscape. In addition to these features, users can expect regular updates that will continually enhance the application’s functionality and user experience.

Media

Media

Integrations Supported

LangChain
OpenAI
GameplayKit
JavaScript
SceneKit

Integrations Supported

LangChain
OpenAI
Codestral Mamba
Hugging Face
Llama 2
Llama 3
Llama 3.1
Llama 3.3
Mathstral
Meta Pixel
Ministral 8B
Mistral 7B
Mistral AI
Mistral Large
Mixtral 8x22B
Mixtral 8x7B

API Availability

Has API

API Availability

Pricing Information

$25 per month
Free Version

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

Mac

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Metal

Company Website

getmetal.io

Company Facts

Organization Name

Klee

Company Website

kleedesktop.com

Categories and Features

AI Development

Not specified

AI Fine-Tuning

Not specified

Machine Learning

Not specified

Vector Databases

Not specified

Categories and Features

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