Reminiz has an automatic tagging and indexing features in real time

Reminiz is a French startup computer vision company that has the ability to index any kind of video- it is very similar to Googlebot, but it is used for video content. You can use Reminiz to tag your friends. It also has a feature of applying different types of logos and emotions in live videos.

Co-founder and CEO Jack Habra told me:

“The web is designed so that you can search for text — not video. We are making it possible to search within videos.”

There are different scenarios for Reminiz. First of all the company works along with telecom and broadcasters industry. For example, this company has a collaboration with orange so that you can understand the person who is on the screen right now. It can potentially grasp the circumstantial adds for external contents or recommendations.

Reminiz has a feature of streaming live channel on its own server, adding tags and scanning images. Users are also allowed to download the metadata directly from the servers.

Then there is a new keynote where you can promote your brands with the help of relevant videos of it. For example, we can see how Hyundai is sponsoring Lyon’s soccer team. Hyundai has the right to show their promotional videos before any team news or game highlights of Lyon. But if you have a target audience, YouTube keywords will not work in that case- A video can only show the soccer team without showing any proper footage.

So brands are now distributing the ads of their product with the help of whitelist videos. The charging rate is based per minute of that video footage which is processed following the protocol by Reminiz.

AWS Rekognition is a big competitor of REMINIZ. It also competes with other generic video analysis APIs from cloud providers. Reminiz makes its own database of people, faces. Tags and brands. These make Reminiz different from other companies. It is easy to work with Reminiz compare to other generic solutions.

Habra said:

“With GDPR, everybody is contacting us to focus more on contextual data instead of personal data.”

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