The prediction API provides an ai-powered sorting of multi-dimensional data. As a first request,
you define a set of rules describing the structure of your data (e.g. numerical or textual). Then,
you can send the data in form of a JSON-list. As a return value, you obtain the sorted list,
predicting the matching quota.
This API can be used for a various multi-dimensional problems, such as finding the optimal candidate
for a job or the perfect product for a customer.
* requests and net prices per month
The recommendation API finds nearest neighbors on a multi-dimensional data mesh. On the one hand, you
can add data to your mesh (e.g. by sending usage data of your website). On the other hand, you can request
the nearest neighbor for a certain data profile (e.g. to recommend sub-pages to a user).
This API solves multi-dimensional problems such as product or media recommendations, providing highly individualized
consumer predictions. Currently, the recommendation API is not part of the SDK - get in touch for more information.