Pricing score

7.6

Tasq Pricing Profile

Tasq.ai orchestrates the ML and GenAI lifecycle by combing world-class models and seamless human guidance for leading AI practitioners.

HQ Location

San Francisco, California, USA

Category:

AI

Key Takeaways

AI-Powered Automation

Tasq's platform uses machine learning algorithms to assist with the initial labeling of data, reducing the amount of manual effort required for large datasets.

High Volume

Tasq is designed to handle large-scale annotation projects, making it suitable for organizations with extensive datasets that need to be labeled quickly and accurately.

Human Verification

After the automated labeling process, human annotators review and refine the labels to ensure they meet the required accuracy and quality standards. This combination of AI and human oversight improves the efficiency and precision of data annotations.

Product Overview

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Tasq is a company that specializes in providing data labeling and annotation services for machine learning (ML) and artificial intelligence (AI) projects. Tasq leverages a combination of automation and human-in-the-loop (HITL) processes to ensure high-quality data annotations at scale, making it suitable for industries that rely on large datasets to train machine learning models. Tasq's platform is designed to handle complex data annotation tasks across various data types, such as images, videos, text, and audio, to accelerate AI and ML model development.

Tasq's platform offers a scalable, efficient, and flexible solution for annotating data in multiple formats, supporting diverse use cases across industries like computer vision, natural language processing (NLP), and speech recognition. By integrating AI-assisted automation with human quality control, Tasq ensures that the final labeled data is accurate, consistent, and ready for training robust machine learning models.

INSIGHTS

Our insights about Tasq pricing

01

Demo available

02

Offers custom quotes

03

Pricing information is not publicly available

Available Pricing Models

How much does Tasq cost?

Tasq does not publicly disclose its pricing on its website, as costs can vary based on factors like company size, the products selected, and specific requirements. For the most accurate and personalized pricing information, it’s best to contact Tasq directly through their website or speak with a sales representative.

Tasq Pricing Rating

Team Collaboration: 4.8/5

The platform offers features to facilitate communication between project managers, annotators, and quality assurance teams, streamlining the workflow and enhancing team coordination.

Integration: 4.7/5

Tasq provides API support for easy integration with machine learning workflows. This allows users to connect the annotation platform with their existing data pipelines and model training systems.

Custom Workflows: 4.9/5

The platform is highly customizable, allowing users to define workflows, labeling rules, and categories to match the unique needs of their projects.

FAQ on Tasq Pricing

What is the commonly used image labeling tool for object detection?

Image annotation can be defined as selecting certain objects in images and labeling them with proper attributes, classes, and tags to create a training set of data for machine learning models training. Annotated data is used in various sectors. and digital processes where the object recognition is one of the main preferences and goals such as aerial vision and imaging, video surveillance, autonomous driving, VR/AR devices, etc. The importance of proper annotation can be seen through the fact that almost 80% of the time during Machine Learning processes is consumed on data preparation and processing.

What is the best image labeling tool for object detection?

Data labeling ranks high in the development of Artificial Intelligence and Machine Learning. Data labeling can be handled by humans or through the training of Machine Learning models. Initial labeling is commonly done by humans, but with more training with that data, computers level up the precision in prediction capabilities. There are some data labeling tools that are automating the process but it is always a better option to hire professional companies and contributors, such as Tasq.ai.

How does Tasq's AI-powered annotation work

Tasq uses machine learning algorithms to automatically label data, which is then reviewed and refined by human annotators. The AI system generates initial annotations, while human workers verify and correct them as needed to ensure high-quality, accurate labels. This human-in-the-loop (HITL) approach optimizes the speed and accuracy of the labeling process.

Can I integrate Tasq with my existing ML pipeline?

Yes, Tasq offers API integration to connect its platform with your existing machine learning workflows. This makes it easy to incorporate labeled data directly into your model training and testing processes. Tasq also supports exporting data in multiple formats (CSV, JSON, XML, etc.) for easy integration with other tools and platforms.