Kimera Tagging

The Kimera Technologies API is a set of AI Computer Vision solutions available as a web service that allows you to automate the process of analyzing, organizing and searching through large databases of unstructured visual content. Through our encoding systems we can store millions of images without losing any information. To this, we add a layer of super speed algorithms that allow us to find anything in the database in a matter of milliseconds. All this always focused on reducing costs, occupying as little memory as possible and optimizing resources. And of course, the most important thing for us, accessibility. So that this is easy to use for all companies and use cases. Because in the end the important thing is that your users find what they are looking for.

Differentiation

We use new generation models that work with unlimited categories, completely free and do not require retraining. On the other hand, our data processing makes us much more competitive by being able to manage databases in milliseconds thanks to a fully scalable cloud architecture. We ensure a restricted privacy policy as we are able to capture and embed all the information in a unidirectional encoding and we do not have to see the image again in the future for any use. Fully agnostic technology, which does not depend on market or user level, serving for any use case via API, front-end or plugin.

Product

The first of Kimera Technologies' Tagging tools: Text Tagger. This solution allows you to freely define a dictionary (in a .json file format) of whichever textual tags you need and apply it to your database!

We call these .json files "dictionaries". You can define and upload multiple dictionaries to the system. You can combine as many dictionaries as you want to get multiple tags for an image. You can also create hierarchical tags so depending on the parent tag we can reach the more specific ones.

The second tool is the next generation of tagger: Visual Tagger. This solution allows you to tag content relating it to other pictures as reference.

Here we will create a .json file with the words or descriptions (tags) and their reference images that you want to recognize from your pictures.

As before, we call these .json files "dictionaries". You can define and upload multiple dictionaries to the system. Be wise choosing the images you use as reference. Not many are required (however the more the better), but it is very important that they clearly represent the tag defined and that they are as different as possible among them.

Finally, we can also compute object detection to detect specific elements in your images and just check they appear, or maybe edit the image for your needs: blurr for privacy, edit it for image enhancement, segment it, etc.

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