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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 BGE?

BGE, or BAAI General Embedding, functions as a comprehensive toolkit designed to enhance search performance and support Retrieval-Augmented Generation (RAG) applications. It includes features for model inference, evaluation, and fine-tuning of both embedding models and rerankers, facilitating the development of advanced information retrieval systems. Among its key components are embedders and rerankers, which can seamlessly integrate into RAG workflows, leading to marked improvements in the relevance and accuracy of search outputs. BGE supports a range of retrieval strategies, such as dense retrieval, multi-vector retrieval, and sparse retrieval, which enables it to adjust to various data types and retrieval scenarios. Users can conveniently access these models through platforms like Hugging Face, and the toolkit provides an array of tutorials and APIs for efficient implementation and customization of retrieval systems. By leveraging BGE, developers can create resilient and high-performance search solutions tailored to their specific needs, ultimately enhancing the overall user experience and satisfaction. Additionally, the inherent flexibility of BGE guarantees its capability to adapt to new technologies and methodologies as they emerge within the data retrieval field, ensuring its continued relevance and effectiveness. This adaptability not only meets current demands but also anticipates future trends in information retrieval.

Media

Media

Integrations Supported

Hugging Face
Anthropic
Claude
Convex
Cursor
Dify
Hermes Agent
LangChain
Langflow
LlamaIndex
Model Context Protocol (MCP)
OpenAI Codex
OpenCode
Pi
RAGFlow
Vercel AI SDK
n8n
nanobot

Integrations Supported

Hugging Face
Baseten
Nebius Token Factory

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Free
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Keenable

Date Founded

2026

Company Location

United States

Company Website

keenable.ai/

Company Facts

Organization Name

BGE

Date Founded

2025

Company Location

United States

Company Website

bge-model.com/Introduction/index.html

Categories and Features

AI Web Scrapers

Not specified

Categories and Features

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