Text summarization is a type of Natural Language Processing (NLP) that automatically generates a concise summary of a longer document or text. The goal of summarization is to condense large amounts of information into a shorter, more manageable format while retaining the most important and relevant details.
Summarization APIs can be used to summarize news articles, research papers, customer feedback, and other forms of written content. They can be integrated into various systems and platforms such as content management, customer relationship management (CRM), and information retrieval.
You can use text summarization in numerous fields, here are some examples of common use cases:
While comparing Summarization APIs, it is crucial to consider different aspects, among others, cost security and privacy. NLP experts at Eden AI tested, compared, and used many Summarization APIs of the market. Here are some actors that perform well (in alphabetical order):
Aleph Alpha's Text Summarization API leverages advanced language models trained on extensive human text data to generate concise and coherent summaries from input text. It provides a powerful solution for condensing and extracting key insights from large volumes of textual data.
Cohere's API is known for its ability to produce accurate and concise summaries that capture the most important information in a given piece of content. Cohere uses advanced Machine Learning techniques to generate summaries that are both informative and engaging.
Connexun offers a summarization API that is particularly effective for generating summaries of news articles and other media content. The API uses more than 13000 human-written summaries to found dependencies and generate summaries that are both concise and informative.
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DeepAI's feature is designed to provide quick and accurate summaries for large volumes of text. It uses advanced algorithms to identify the most important information of the given text, aiming to reduce the size to 20% of the original.
With its advanced NLP techniques, Emvista can handle complex text structures (scientific papers, legal documents, and technical reports, etc.) and produce summaries that preserve the original meaning and context. Developers can quickly and easily integrate Emvista's summarization capabilities into their own products and services, saving time and resources while improving the overall quality of their offerings.
Hugging Face's text summarization models leverage state-of-the-art transformer architectures to generate accurate and concise summaries from input text. These models are trained on large datasets and can effectively condense textual information into coherent and informative summaries.
MeaningCloud's summarization API is known for its accuracy and versatility. This technology can generate summaries in multiple languages and can handle a wide range of content types, including web pages, articles, and social media posts.
This API is part of Microsoft’s larger suite of cognitive services. It performs most effectively in generating summaries of news articles and other media content in both extractive and abstractive types. In addition, the API can generate summaries in multiple languages.
NLP Cloud provides an API that can generate high-quality summaries of long-form content in multiple languages. It also offers the ability to customize the summarization process based on specific requirements and preferences.
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OneAI's summarization API is designed to provide accurate and concise summaries of text-based content. Users can specify the length of the summary, and the API will automatically generate a summary that captures the most important information in the text. Additionally, it has the ability to summarize content in multiple languages, including English, Spanish, German, and French.
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Open AI offers the GPT-3 Summarization API, which produces abstractive summaries that can go beyond simply selecting and combining sentences from the original text. The model is known for its ability to generate high-quality and human-like summaries of large volumes of text.
plnia's Text Summarization API is based on both advanced NLP and intelligent Machine Learning technologies, which allows it to quickly and accurately summarize long pieces of content. The feature focuses on summarizing long text blocks, documents, and articles.
Writesonic's AI-powered text summarization feature is designed to provide quick and concise summaries for various types of content. The platform leverages advanced AI models, including GPT-3.5 and GPT-4 32K, to generate real-time summaries based on input information.
For all companies who use Text Summarization in their software: cost and performance are real concerns. The text summarization API market is quite dense and all those providers have their benefits and weaknesses.
Performances of Summarization vary according to the specificity of data used by each AI engine for their model training. This means that some Summarization APIs may perform great for some languages but won’t necessarily for others.
Text summarization APIs perform differently depending on the language of the text. In fact, some providers are specialized in specific languages. Different specificities exist in Region specialties: some summarization APIs improve their machine learning algorithm to make them accurate for text in a specific language. For example, some Summarization APIs perform well in English (US, UK, Canada, South Africa, Singapore, Hong Kong, Ghana, Ireland, Australia, India, etc.), while others are specialized in Asian languages. Rare language specialty: some Summarization vendors care about rare languages and dialects. You can find Summarization APIs that allow you to process text in Gujarati, Marathi, Burmese, Pashto, Zulu, Swahili, etc.
Some text summarization APIs trained their engine with specific data. This means that some text summarization APIs will perform better for news articles, while others will perform better on technical documents.
Companies and developers from a wide range of industries (Social Media, Retail, Health, Finances, Law, etc.) use Eden AI’s unique API to easily integrate Summarization tasks in their cloud-based applications, without having to build their own solutions.
Eden AI offers multiple AI APIs on its platform amongst several technologies: Text-to-Speech, Language Detection, Sentiment Analysis, Question Answering, Data Anonymization, Speech recognition, and so forth.
We want our users to have access to multiple text summarization engines and manage them in one place so they can reach high performance, optimize cost and cover all their needs. There are many reasons for using multiple APIs :
Eden AI has been made for multiple AI APIs use. Eden AI is the future of AI usage in companies. Eden AI allows you to call multiple AI APIs.
You can see Eden AI documentation here.
The Eden AI team can help you with your Summarization integration project. This can be done by :
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