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What is Keenable?

Keenable functions as an independent web search platform specifically crafted for AI research facilities, inference systems, agents, and developers who require swift and dependable access to real-time online information. The Search API provides AI systems with a vast repository of over 100 billion documents, engineered for quick retrieval and optimized for high-performance demands of production agents. Agents can explore web pages and extract content using a REST API, MCP server, or command-line interface, all manageable under one account and API key. Committed to enhancing its services, Keenable continuously evaluates and improves search quality using its NEEDLE benchmark, which measures retrieval efficiency among various search services and aligns findings with an oracle ranking based on collective results. For larger-scale AI initiatives, the platform offers specialized search capabilities along with choices for both cloud and on-premises deployment. Moreover, its Time Machine functionality strengthens retrieval options by enabling users to search through historical versions of web pages, providing a richer perspective on past information. This focus on both contemporary and historical data establishes Keenable as an adaptable and powerful resource for advanced AI endeavors, ensuring that users can access the information they need, regardless of the context or timeline.

What is Actian VectorAI DB?

The Actian VectorAI DB is a highly adaptable vector database designed with a local-first approach, specifically for AI applications that require immediate access to their data, making it ideal for edge, on-premises, and hybrid configurations. This innovative technology allows developers to create solutions that utilize semantic search, retrieval-augmented generation (RAG), and AI functionalities without relying on cloud infrastructure, thus avoiding issues such as latency, dependence on network systems, and costs associated with each query. By featuring native vector storage and optimized similarity search techniques, it utilizes strategies like approximate nearest neighbor indexing and HNSW algorithms, ensuring rapid retrieval from large-scale embedding datasets while maintaining an effective balance between speed and accuracy. Moreover, it is capable of conducting low-latency searches directly on various devices, from typical laptops to smaller platforms like Raspberry Pi, which promotes prompt decision-making and autonomous operations without needing a network connection. In summary, the Actian VectorAI DB not only enhances the efficiency of AI technologies but also provides developers with a robust tool to implement their innovations across a wide range of environments. Its versatility and performance make it a compelling choice for those aiming to leverage AI effectively and independently.

Media

Media

Integrations Supported

Hugging Face
Anthropic
Claude Desktop
Cursor
Dify
Haystack
Hermes Agent
Langflow
Lightpanda
Mastra AI
Model Context Protocol (MCP)
OpenAI Codex
OpenClaw
OpenCode
Pi
Pipecat
RAGFlow
Visual Studio Code
nanobot

Integrations Supported

Hugging Face
Docker

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Keenable

Date Founded

2026

Company Location

United States

Company Website

keenable.ai/

Company Facts

Organization Name

Actian

Date Founded

1980

Company Location

United States

Company Website

www.actian.com/databases/vectorai-db/

Categories and Features

AI Web Scrapers

Not specified

Categories and Features

Vector Databases

Not specified

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