DataStax Acquisition Expands GenAI Application Development Portfolio

DataStax has acquired Langflow, provider of a popular framework for building generative AI applications that use retrieval augmented generation (RAG) technology.

With the acquisition DataStax, whose core data platform is based on the Apache Cassandra database, is looking to strengthen its position in the AI data and application development arena.

“AI development is completely different than what is needed to build traditional software and applications. And that’s because of the large language models that form the heart of these AI applications,” said Carter Rabasa, head of developer relations at Santa Clara, Calif.-based DataStax, in an interview with CRN.

Financial terms of the acquisition were not disclosed.ADVERTISEMENT

AI applications need large volumes of data to operate effectively and DataStax has been positioning itself as “the generative AI data company.” Last year the company added vector search capabilities, a key database capability for AI applications using large language models (LLMs), to its Astra DB cloud database. In January DataStax announced the general availability of its Data API “one-stop shop” API that provides data for production GenAI systems.

Retrieval augmented generation is a development technique for enhancing the accuracy and reliability of generative AI models by pulling in additional data from external data sources. In November DataStax launched RAGStack, a retrieval augmented generation system to aid in GenAI application development. RAGStack is based on LangChain, an open-source framework for building RAG applications.

Langflow’s developer system provides a graphical drag-and-drop user interface, reusable components for applications and data sources, rapid iteration of data flows, and related tools for building GenAI applications and LLMs. The Langflow platform dramatically speeds up AI application development and deployment, according to the company, and results in applications that produce fewer hallucinations.

LangChain is already integrated with the Astra DB Vector Database and the Apache Cassandra database. It’s also integrated with AI ecosystem frameworks supported by RAGStack.

The combination of the DataStax and Langflow technology portfolios will create a one-stop generative AI application stack for developers, according to the companies.

“This acquisition is a really big moment in the life of both DataStax and Langflow,” Rabasa said. “Langflow has built a huge, vibrant community of developers that both use the tool, but also contribute to it.”

Rabasa said DataStax is still mulling just how Langflow’s technology will be incorporated into – and integrated with – the rest of the DataStax portfolio. But Rabasa said DataStax is promising to maintain Langflow’s status as an open-source and vendor “agnostic” tool, including continuing support for numerous vector databases.

DataStax works with dozens of IT consulting partners, including EPAM, Perficient and Trace3, that provide application development technology and services to their customers. Rabasa said the DataStax and Langflow combination will provide “a huge productivity boost” for partner developer teams looking for ways to compress generative AI development project times.

“We are laser-focused on providing developers with tools that enable them to easily build RAG applications with the simplest and fastest path to production,” said Chet Kapoor, DataStax CEO, in a statement. “This acquisition is transformative to us and transformative to the industry. Langflow is an incredibly hot AI startup and our work with them will put us front and center for all RAG application development–it’s not just a tool or framework, it’s a vibrant ecosystem where developers are building, selling, and reusing AI components that are going to shape the next generation of AI applications.”

“With DataStax, we will be fully focused on the execution of our product vision, roadmap, and community collaboration, and will continue to add to the greatest breadth of integrations across different AI ecosystem projects and products – including more data sources and databases, models, applications and APIs,” said Rodrigo Nader, Langflow CEO, in the statement.

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