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Machine Learning-based Content Preparation Services

Machine Learning-based Content Preparation Services

Process long form content faster, and more efficiently and cost-effectively

A first-of-its-kind machine learning-augmented
content preparation service

Why use machine learning for content preparation

Faster turnaround

Faster turnaround

Scale-up rapidly and process large volumes of content to eliminate content preparation bottleneck.

Build innovative broadcast experiences

Build innovative broadcast experiences

Deliver innovative broadcast experiences such as near-real-time live to VOD and thematic content segmentation.

Reduce manual errors

Reduce manual errors

Process content with an unique human-assisted approach to ensure content quality, identification of black frames and others.

How Amagi is using automation to make broadcast simpler

How TORNADO works

How TORNADO works

Neural-network trained models

Deploy machine learning models trained extensively using thousands of hours of content across genres and languages to generate high-confidence output.

Human validation

Use the interface to validate the output generated by machine learning models. This ensures that bulk of heavy-lifting is done by machines, while maintaining high degree of accuracy.

How machine learning will change broadcast jobs

Intelligent web-based dashboard

Upload assets and submit processing requests with ease

Upload assets and submit processing requests with ease

Define asset location and specify the task type such as VOD segmentation to submit requests to TORNADO system.

Accurately define nature of the tasks

Accurately define nature of the tasks

Select sub-tasks with a simple check box to define the scope of the tasks.

View and validate auto-generated segments

View and validate auto-generated segments

Access all segments created by TORNADO system, as well as the details about task type and accuracy score. Approve, delete, or create segments with click of a button.

Use cases for TORNADO

Factory-scale content segmentation

Factory-scale content segmentation

Detect scene-changes for ad insertion points, and technical segments for QC in thousands of hours of video.

Publish live to VOD in near-real-time

Publish live to VOD in near-real-time

Bring fresh off-the-air TV content to OTT in near-real-time. Scale the live to VOD delivery to hundreds of platforms without large manual production teams.

Automate content enrichment with thematic segmentation

Automate content enrichment with thematic segmentation

Use machine learning technology to simplify complex content functions such as detection of specific type of scenes, or generating metadata information for OTT platforms automatically.

Why TORNADO

Faster turnaround time

Cloud-native model with on-demand scaling

Cost reduction with minimal resource requirement

Greater efficiency with continuously evolving
ML models

Client success stories

Tony Huidor,  ‎Cinedigm Entertainment Tim Bertioli, Viceland TV Kaushik Basu, DSPORT Dave Alworth, AMC Networks Heather Killen, H&C TV Dinesh Singh, CTO, NDTV Ashok Shenoy, B4U Networks
quote

The time to market was extremely quick with Amagi cloud playout platform. We were able to launch our first broadcast quality channel with in a matter of weeks

Tony Huidor, ‎Cinedigm Entertainment

Moving to Amagi has provided us an opportunity to scale up faster, and more effectively.

Tim Bertioli, Viceland TV

Amagi's cloud managed services helped us launch a live sports channel with machine-learning driven automation.

Kaushik Basu, DSPORT

Using Amagi, we now have an increased offering of locally relevant programming.

Dave Alworth, AMC Networks

Using cloud-based solution from Amagi has made it commercially viable to serve specialized content in non-contiguous high value markets.

Heather Killen, H&C TV

Amagi's solution allowed us to monetize Middle East market without setting up separate satellite feed, or making changes to existing systems.

Dinesh Singh, CTO, NDTV

Amagi improved flexibility of our broadcast workflow, making it easy for us to deliver content relevant to each region while reducing OPEX and CAPEX.

Ashok Shenoy, B4U Networks

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