Skip to main content
AA

Ango AI

Ango Hub is an AI data workflow automation platform that enhances data labeling efficiency through features like auto-labeling, optical character recognition, and interactive annotation tools. It addresses the challenge of high-quality data annotation by enabling real-time collaboration and performance tracking among annotators and project managers.

Founded 202083K+ followers
Updated 20 months ago

Funding

$720K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

5EE
Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Annotating data for AI models is often a time-consuming and expensive process, requiring significant manual effort. Ensuring high-quality annotations across diverse data types and large datasets presents a major challenge for organizations developing AI solutions.

Solution

Ango Hub is an AI data workflow automation platform designed to streamline and enhance the data labeling process. The platform offers AI-assisted features such as auto-labeling and optical character recognition (OCR) to improve annotation efficiency. Ango Hub facilitates real-time collaboration and performance tracking among annotators and project managers, ensuring precise annotations for training AI models. The platform supports various data types, including images, videos, text, documents, audio, and DICOM, enabling users to annotate data of any size and format.

Target Audience

Ango Hub targets AI and machine learning teams, data scientists, and project managers who require efficient and high-quality data annotation for training AI models.

Features

  • Auto-labeling of objects using pre-trained ML models for improved efficiency.
  • Optical Character Recognition (OCR) to detect, transcribe, and localize text within images.
  • Interactive tools like Magnetic Lasso for precise object boundary detection.
  • Workflow assignment, allowing multiple annotators to work on the same asset.
  • Quality control features enabling reviewers to accept, reject, or fix labels.
  • Real-time issue system for annotators to ask questions and receive instant feedback.
  • User roles and permissions to control data access and ensure security.
  • Import pre-labels from existing models or previous labeling jobs.
  • Detailed analytics and reports to track project performance and identify areas for improvement.
This profile is AI-generated and may contain inaccuracies.