Tisane Labs

It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.

It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.

rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.

It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks.

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications.

You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage on Google Cloud Storage.

It is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices.

It is a Natural Language Processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines that scale easily in a distributed environment. It comes with 160+ pretrained pipelines and models in more than 20+ languages.

It provides a set of natural language analysis tools written in Java. It can take raw human language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize and interpret dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases or word dependencies, and indicate which noun phrases refer to the same entities.

AlchemyLanguageTM is the world’s most popular natural language processing service. AlchemyVisionTM is the world’s first computer vision service for understanding complex scenes. AlchemyAPI is used by more than 40,000 developers across 36 countries and a wide variety of industries to process over 3 billion texts and images every month.

Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.

Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS), sense disambiguation and classification.

Wit enables developers to add a modern natural language interface to their app or device with minimal effort. Precisely, Wit turns sentences into structured information that the app can use. Developers don’t need to worry about Natural Language Processing algorithms, configuration data, performance and tuning. Wit encapsulates all this and lets you focus on the core features of your apps and devices.

It is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.

It is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism.

High performance NLP models based on spaCy and HuggingFace transformers, for NER, sentiment-analysis, classification, summarization, question answering, and POS tagging. All models are production-ready and served through a REST API. You can also deploy your own spaCy models. No DevOps required.

At the top of each mountain of data lies a nugget of invaluable knowledge, but it takes an incredibly powerful tool to bring that mountain to its knees. That's precisely what our Text Analysis API does.

Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT, etc.). It offers production-ready tools to build NLP backend services, e.g., question answering or semantic search.

Reduce development cost and complexity, and increase developer happiness, with the most powerful companion to any conversational AI project.

It can be used to complement any regular touch user interface with a real time voice user interface. It offers real time feedback for faster and more intuitive experience that enables end user to recover from possible errors quickly and with no interruptions.

prose is a natural language processing library (English only, at the moment) in pure Go. It supports tokenization, segmentation, part-of-speech tagging, and named-entity extraction.

Today's personal assistants and conversational interfaces fail to handle variations in a user's wording or multiple requests in one sentence. We take a language-based semantic approach to handle complex dialogue.

Dasha is a conversational AI as a Service platform. Dasha lets you create conversational apps that are more human-like than ever before, quicker than ever before and quickly integrate them into your products.

It is an efficient and easy-to-use text annotation tool for Natural Language Processing (NLP) applications. With this, you can train an NLP model in few hours by collaborating with team members and using the machine learning auto-annotation feature.

It is a NLP deep learning modeling toolkit that helps engineers/researchers to build end-to-end pipelines for neural network model training for NLP tasks. The main goal of this toolkit is to minimize developing cost for NLP deep neural network model building, including both training and inference stages.

Semantria applies Text and Sentiment Analysis to tweets, facebook posts, surveys, reviews or enterprise content.

The fastest and most reliable way for finding deep insights in NPS, CSAT, user research surveys and chat logs.

It is an easy-to-use NLP development and application toolkit in PyTorch, first released inside Alibaba in 2021. It is built with scalable distributed training strategies and supports a comprehensive suite of NLP algorithms for various NLP applications.

It uses language models against themselves to build suites of unit tests. It is an interactive (and fun!) process between a user and a language model that results in a tree of unit tests specifically adapted to the model you are testing.

It is a comprehensive suite of products which offers solutions for content discovery, semantic enrichment, governance, analytics, relevancy management and automated testing. It is a platform that offers research case management solutions and a variety of result analysis and advanced search options that helps researchers in deeper study and literature exploration. It exploits the unstructured content to yield an intelligent search and discovery solution.

It is a Chrome extension designed for Google Analytics. It enables the option to add annotations in bulk.

It is an open-source no-code system for text annotation and building text classifiers. With this, domain experts can quickly create custom Natural Language Processing (NLP) models by themselves, with no dependency on NLP experts. No AI knowledge needed; from task definition to working model in just a few hours!