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What is Ximilar?

Leverage cutting-edge deep learning algorithms for your initiatives and streamline the deployment of innovative vision automation without the burden of development costs. Create powerful, customized image recognition solutions through a user-friendly web interface designed for ease of use. Our dedicated team consistently refines the core machine learning algorithms, ensuring you have access to the most recent breakthroughs in technology. Additionally, you have the option to train a personalized neural network tailored to recognize the specific images essential for your projects. Ximilar, a leader in Visual AI and Search technologies, has strengthened its offerings by acquiring Vize, which enhances performance, speed, and incorporates crucial features for businesses. Visit the Ximilar Homepage to explore our extensive range of services and discover how we can address your visual AI requirements. Elevate your business with our transformative solutions, unlocking new opportunities for growth and innovation in the visual domain. With our expertise, you can stay ahead in a rapidly evolving technological landscape.

What is Hive Data?

Create training datasets for computer vision models through our all-encompassing management solution, as we recognize that the effectiveness of data labeling is vital for developing successful deep learning applications. Our goal is to position ourselves as the leading data labeling platform within the industry, allowing enterprises to harness the full capabilities of AI technology. To facilitate better organization, categorize your media assets into clear segments. Use one or several bounding boxes to highlight specific areas of interest, thereby improving detection precision. Apply bounding boxes with greater accuracy for more thorough annotations and provide exact measurements of width, depth, and height for a variety of objects. Ensure that every pixel in an image is classified for detailed analysis, and identify individual points to capture particular details within the visuals. Annotate straight lines to aid in geometric evaluations and assess critical characteristics such as yaw, pitch, and roll for relevant items. Monitor timestamps in both video and audio materials for effective synchronization. Furthermore, include annotations of freeform lines in images to represent intricate shapes and designs, thus enriching the quality of your data labeling initiatives. By prioritizing these strategies, you'll enhance the overall effectiveness and usability of your annotated datasets.

Media

Media

Integrations Supported

Claude
Cursor
GitHub
GitLab
PHP
Postman
Python

Integrations Supported

Apache Atlas
Hive AutoML
Quickwork
Style Intelligence
Taxi for Email
Toad Intelligence Central
Wyn Enterprise
bipp

API Availability

Has API

API Availability

Has API

Pricing Information

$0
Use Ximilar's AI services through the App or API. API calls consume credits from your monthly plan.
Free Version

Pricing Information

$25 per 1,000 annotations

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Ximilar

Date Founded

2016

Company Location

Czech Republic

Company Website

www.ximilar.com

Company Facts

Organization Name

Hive

Date Founded

2013

Company Location

United States

Company Website

thehive.ai/data-labeling

Categories and Features

Computer Vision

Building Tools
Image Processing
Multiple Image Type Support

Image Recognition

Not specified

Categories and Features

AI Vision Models

Not specified

Computer Vision

Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration

Data Annotation

Not specified

Data Labeling

Labeling Automation
Labeling Quality
SDK
Supports Audio Files
Team Collaboration

Image Annotation

Not specified

Image Recognition

Not specified

Video Annotation

Not specified

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