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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 gaining insights. Finding the right information among a sea of text is becoming increasingly difficult.
Natural language is the most flexible and powerful way to communicate with data and software.
Deepset, a German startup, is working on an addition 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, Haystack, is an open-source NLP framework that allows developers to create pipelines for various search use cases.
The Haystack-based NLP is typically implemented through a text database such as Elasticsearch or Amazon’s OpenSearch branch and then connects directly to the end-user application through a REST API. It already has thousands of users and more than 100 contributors. It uses transformer models to enable developers to create a variety of applications, such as production-ready question answering (QA), semantic document search, and summaries. The company has also introduced Deepset Cloud, an end-to-end platform for integrating customized and high-performance NLP-powered search systems into your application.
Deepset aims to bridge the gap between research and industry by enabling developers to create flexible and powerful neural search engines that can search all kinds of data. They develop a semantic layer for the modern tech stack, powered by advanced NLP and open source.
The Berlin-based company has raised $14 million in Series A financing led by GV, Alphabet’s venture capital arm. The company plans to use these funds for product development and expanding its go-to-market strategy. The company’s upcoming technology advancements include native, speech-based search support.