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Data is everywhere. However, having access to data does not always mean having access to relevant, contextualized information for exploring and extracting insights. Finding the correct information amid a sea of text is becoming increasingly difficult.
Natural language is the most adaptable and powerful approach to communicating with data and software.
Deepset, a German startup, is working to add to Natural Language Processing by integrating a language awareness layer into the business tech stack, allowing users to access and interact with data using language. Its flagship product, Haystackis an open-source NLP framework that enables developers to create pipelines for a variety of search use-cases.
The Haystack-based NLP is typically implemented over a text database like Elasticsearch or Amazon’s OpenSearch branch and then connects directly with the end-user application through a REST API. It already has thousands of users and over 100 contributors. It uses transformer models to let developers create a variety of applications, such as production-ready question answering (QA), semantic document search, and summarization. The company has also introduced Deepset Cloudan end-to-end platform for integrating customized and high-performing NLP-powered search systems into your application.
Deepset aims to bridge the gap between research and industry by empowering developers to create flexible and powerful neural search engines that can query all kinds of data. They’re developing a semantic layer for the modern tech stack, powered by cutting-edge NLP and open source.
The Berlin-based company has raised $14M in Series A funding led by GV, Alphabet’s venture capital arm. The company aims to use these funds for product development and expand its go-to-market strategy. The coming technological advancements of the company include native Voice-based search support, among many others.