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Description
Amazon S3 Vectors is the pioneering cloud object storage solution that inherently accommodates the storage and querying of vector embeddings at a large scale, providing a specialized and cost-efficient storage option for applications such as semantic search, AI-driven agents, retrieval-augmented generation, and similarity searches. It features a novel “vector bucket” category in S3, enabling users to classify vectors into “vector indexes,” store high-dimensional embeddings that represent various forms of unstructured data such as text, images, and audio, and perform similarity queries through exclusive APIs, all without the need for infrastructure provisioning. In addition, each vector can include metadata, such as tags, timestamps, and categories, facilitating attribute-based filtered queries. Notably, S3 Vectors boasts impressive scalability; it is now widely accessible and can accommodate up to 2 billion vectors per index and as many as 10,000 vector indexes within a single bucket, while ensuring elastic and durable storage with the option of server-side encryption, either through SSE-S3 or optionally using KMS. This innovative approach not only simplifies managing large datasets but also enhances the efficiency and effectiveness of data retrieval processes for developers and businesses alike.
Description
Keenable operates as a standalone web search infrastructure tailored for AI laboratories, inference frameworks, agents, and developers seeking quick and reliable access to real-time web content. The Search API equips AI entities with an extensive index comprising over 100 billion documents, specifically designed for rapid retrieval with performance fine-tuned for demanding production agent tasks. Agents are enabled to search through web pages and obtain page content via a REST API, MCP server, or command-line interface, all under a single account and API key. Continuously striving for excellence, Keenable assesses and enhances search quality through its NEEDLE benchmark, which evaluates retrieval efficiency across various search providers and aligns results with an oracle ranking derived from aggregated outcomes. For expansive AI tasks, the platform offers dedicated search capacity alongside options for cloud and on-premises deployment. Additionally, its Time Machine feature enhances retrieval capabilities by allowing users to conduct searches across historical webpage versions, offering a comprehensive view of past content. This dual focus on current and historical data positions Keenable as a versatile tool for modern AI applications.
API Access
Has API
API Access
Has API
Integrations
Amazon OpenSearch Service
Amazon S3
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
ChatGPT
Claude Desktop
Convex
Dify
Hermes Agent
Hugging Face
Integrations
Amazon OpenSearch Service
Amazon S3
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
ChatGPT
Claude Desktop
Convex
Dify
Hermes Agent
Hugging Face
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/s3/features/vectors/
Vendor Details
Company Name
Keenable
Founded
2026
Country
United States
Website
keenable.ai/
