Komprehend AI APIs are the most comprehensive set of document classification and NLP APIs for software developers. Our NLP models are trained on more than a billion documents and provide state-of-the-art accuracy on most common NLP use-cases such as sentiment analysis and emotion detection.

The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow.

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The purpose of this API is to provide access to information collected by Lastline appliances on a protected network.

The Lettria Platform at app.lettria.com is used for setting up your project, importing your dataset, collaborating in a group, annotating your data, organising your knowledge, and building your NLP solution.
The Lettria API, on the other hand, is what you will use to build your application with the solution you’ve built on the platform using your data and knowledge.
Using the API, you can easily understand text data that is given as input to the API, using artificial intelligence and natural language processing.

The Lettria API is optimized for performance and easy integration. It will allow you to analyze your raw data and find the key elements. Automatic Language Processing is now available as a service. The Lettria API efficiently analyzes all points in contact with customers (emails, support, telephone). It organizes the data to create a clear, usable history and ensure GDPR compliance. It is useful for social listening applications or e-reputation monitoring. It modifies in real-time what is being said about your brand. Complete documentation to make the most of the French / NLP automated processing API. Tutorials to help you deploy the Lettria API into your projects. Transparent algorithms that are clear and orderly.

The API enables programmatic integration with Lilt, allowing developers to construct applications that directly leverage Lilt's features. Leveraging Lilt's API to make your organization's workflows faster and more efficient. Example applications include:

translation management system (TMS) integrations

adding interactive, adaptive machine translation to sites and apps

adding translation memory and terminology to sites and apps

bulk download/upload of content

APIs for Natural Language Processing

Microsoft Azure AI offers pre-built services that can be used to develop intelligent applications. These services include speech-to-text, text-to-speech, sentiment analysis, and language translation. Azure also offers a wide range of pre-built models, making it easy for businesses who want to get a product built using these applications without AI expertise. The API is easy to use and integrates seamlessly with other Azure services.

Microsoft Azure Cognitive Services is a collection of pre-built AI services that developers can use to add intelligent features to their applications. It includes APIs for tasks such as image and video analysis, text analysis, and natural language processing, and provides fast and accurate results.

The Bing Video Search API makes it easy to add video searching capabilities to your services and applications. By sending user search queries with the API, you can get and display relevant and high-quality videos similar to Bing Video. Use this API for search results that only contain videos. The Bing Web Search API can return other types of web content, including webpages, videos, news and images.

Welcome to the MonkeyLearn API v3 documentation.

Here you’ll find everything you need to access the MonkeyLearn API. You can use it to classify, extract, or manage your custom models programmatically.

We provide a REST API that you can access directly or through a client library.