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AI powered video and image content classification platform

Content moderation platform that automates classification, tagging and indexing of high-volume user-generated visual content, significantly reducing human intervention.

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Our technology

Mirrors Sift’s AI powered computer vision technology addresses automated content moderation needs for video and image content, including unsafe contexts like nudity, violence, arms & guns, smoking, alcohol, and more.

Accurately detects in-video and in-image contexts like faces, objects, logos, actions, places, scenes and emotions.

A core capability of Mirrors Sift’s computer vision powered content classification offering. It then compares the features of detected context with pre-defined or custom database for tagging and indexing.

Mirrors Sift identifies the exact location of a predefined context in a video and time stamps it. Mirrors Sift accordingly indexes both video and image content with relevant tags or keywords.

Based on Machine Learning AI technology, the visual tagging model analyzes the pixel content of visuals, extracts its features and detects the objects of interest.

Relevant categories are automatically assigned to videos and images.

Mirrors Sift’s state-of-the-art machine learning algorithm provides instant content organization with very high accuracy.

Enables customers to specify categories and tags as per business requirements.

Offers custom-trained models as well as tailor-made models based on the customer’s requirements.

Especially useful in the cases where a company wants to move away from manual processes to AI-based solutions.

AI Powered Context Detection

Accurately detects in-video and in-image contexts like faces, objects, logos, actions, places, scenes and emotions.

A core capability of Mirrors Sift’s computer vision powered content classification offering. It then compares the features of detected context with pre-defined or custom database for tagging and indexing.

Mirrors Sift identifies the exact location of a predefined context in a video and time stamps it. Mirrors Sift accordingly indexes both video and image content with relevant tags or keywords.

Based on Machine Learning AI technology, the visual tagging model analyzes the pixel content of visuals, extracts its features and detects the objects of interest.

Relevant categories are automatically assigned to videos and images.

Mirrors Sift’s state-of-the-art machine learning algorithm provides instant content organization with very high accuracy.

Enables customers to specify categories and tags as per business requirements.

Offers custom-trained models as well as tailor-made models based on the customer’s requirements.

Especially useful in the cases where a company wants to move away from manual processes to AI-based solutions.

Deployment options

Mirrors Sift offers multiple integration models to suit your business requirements, which can be easily and seamlessly integrated with your current infrastructure and processes.

Cloud

Deploy Mirrors Sift’s content classification capabilities in the cloud to reduce IT costs and faster deployment.

On-premise

Or deploy on your private servers for full compliance with privacy regulations.

Applicable to a variety of use-cases

Trained to draw insights from millions of pieces of visual content, Mirrors Sift uses computer vision to identify contexts for appropriate classification of content. Insights drawn from the content are useful for a number of use cases.

18+ content moderation

Filters inappropriate content including images and videos intended for minors

NSFW Content tagging

Automates the detection of images and videos containing porn, suggestive & explicit nudity and gore to exclude Not Safe for Work content.

Media & Entertainment

The content is parsed through the platform to enhance the image metadata and provide powerful search capabilities. It learns from the publishing decisions made previously and works in real time, with a higher degree of accuracy.

E-commerce & Retail

Makes tagging of colors and style on shopping images instant and delivers over 96% accuracy for color extraction.

Video streaming platforms

Makes viewing and monetization of user generated content across video hosting platforms safe, including affinity and keyword based classifications, brand safety and policy compliance against unsafe contexts.

User-generated content platforms

Thousands of new posts, images and comments are uploaded the internet every day. Screens and makes sure all available content is safe for consumption.

Why Mirrors Sift

Mirrors Sift automates content classification at scale with self-training AI powered algorithms that offer high accuracy, are highly customizable and auditable, and can analyze millions of pieces of content with significantly reduced human intervention.

Precise and Accurate

Accurately recognizes objects, locations, backgrounds, faces, text, actions and scenes

Customizable

Has more than 1000 pre-defined tags and models. Can be further trained to recognize additional models using custom training.

Huge Volumes

Has analysed millions of videos and images - Mirrors Sift automatically scales to meet increased volume.

Searchability

Advanced tagging, indexing, and classification capabilities along with a comprehensive easy to use dashboard for advanced searchability.

Content Monetization

A higher quality environment with contextually relevant content makes your site a more interesting place for advertisers

Experience Sift

Learn how Mirrors Sift can serve your unique video content classification needs.

Request a Demo

Experience Sift