Content API Overview

Content Comprehension API

While cookies had their passing value, the real value for marketing efforts today is a return to contextually-based solutions that are emerging through sophisticated Artificial Intelligence applications. These rapidly deployable solutions create contextual-based audiences and segments with similar or stronger signals to cookies. They also can provide brand safety measurement for content of all types.

Netra’s new breed of emerging deeper contextual comprehension delivers better results, greater relevance, and fewer fraud concerns than historical cookie-based targets while protecting PII. The signals obtained through Netra’s complete comprehension of content also provide a data classification schema that is common across all content types and provides consistency for a myriad of use cases.

Through the breakthrough use of AI technology, Machine Learning, and Natural Language Processing Netra’s platform cant x-ray content to provide a comprehensive view of:
- IAB contexts
- brand safety
- objects
- activities
- places
- emotions
- affinities
- celebrities
- logos
- brand archetype
- personality archetypes

Why our API is game-changing

• A single, AI-based endpoint to classify all types of content, including text, audio, image, and video that mirrors the depth of classification and quality achieved through hours of person-based review
• Supports industry standards like IAB and GARM, but also allows for custom taxonomies based on trainable use cases
• Provides total content comprehension and consistent taxonomies across media types and publishers

How it's implemented

• Netra’s technology recognizes both objects and text at the frame level, which is then used to construct the “aboutness” of a scene (in the case of video) which is then aggregated to provide a summary of the content asset
• Our API relays scores back after a review of the total media asset
• Scores are normalized to a scale of 0-100.
• General guidance is as follows (but custom rules can be applied as necessary):

• Scores of 30 or greater for IAB, places, activities, and objects show high correlation.
• For demographics and affinities, a score of 50 or greater relates to a high level of confidence.
• Logos and celebrities use a threshold of 80 or greater.
• For GARM, it is recommended to use the risk rating (H/M/L) as the key indicator for triage. 

• Inputs like titles, descriptions and custom tags can be used to further hone categorization.

Additional technical considerations and features

• If there are unique IDs or tags that are relevant to the content, we can associate those values with the evaluation output.
• Outputs are expressed in a multi-label classification format which include people, places, objects, activities, emotions, affinities, brand logos.
• The output is a file, which is human readable and constructed in a manner that is consistent and easily parsed for your use cases.
• We use a RESTful API that conforms to the constraints of REST architectural style and allow for interaction with RESTful web services.
• The API utilizes an asynchronous response structure. We confirm the receipt of a request with standard http error handling, and provide results back to a location of your choice when processing is complete.
• In terms of interpreting results, we provide all applicable categories and segments with a score. This score is a strength of association, at the scene level and aggregated to a summary for the entire asset.
• The API utilizes an asynchronous response structure. We confirm the receipt of a request with standard http error handling, and provide results back to a location of your choice when processing is complete.
• In terms of interpreting results, we provide all applicable categories and segments with a score. This score is a strength of association, at the scene level and aggregated to a summary for the entire asset.
• Support for industry standards like IAB and GARM are provided
• Custom taxonomies can all be supported

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