SANTA CLARA, Calif.–(BUSINESS WIRE)–DataStax, the company that powers generative AI (GenAI) applications with relevant, scalable data, today announced the general availability of its Data API, a one-stop API for GenAI, that provides all the data and a complete stack for production GenAI and retrieval augmented generation (RAG) applications with high relevancy and low latency. Also debuting today is a completely updated developer experience for DataStax Astra DB, the best vector database for building production-level AI applications.
“The seamless user experience, native language client support, and effortless integration with GenAI ecosystems empower us to navigate the complexities of vector search with unprecedented simplicity,” said Mark Hauptman, chief executive officer, ReelStar. “With Astra DB, we’re not just shortening the development journey; we’re accelerating innovation and efficiency in our mission to redefine the landscape of video sharing with GenAI.”
Developers can use the Data API for an out-of-the-box AI ecosystem that simplifies integrations with major GenAI ecosystem leaders like LangChain, LLamaIndex, OpenAI, Vercel, Google Vertex AI, Amazon Bedrock, GitHub Copilot, Azure, and all major platforms while supporting the breadth of security and compliance standards. Any developer can now support advanced RAG techniques such as FLARE and ReAct that must synthesize multiple responses, while still hitting latency SLAs.
“Astra DB’s Data API has been a game-changer for us to build production RAG applications that use enterprise data,” said Rahul Singh, chief executive officer, Anant.US. “The ease of use of the Astra DB experience, coupled with the capability to instantly query real-time data updates for both vector and non-vector data, is essential for production GenAI applications on real-life data workloads. This has significantly expedited our production processes.”
“The Astra DB vector experience advanced GenAI development at Aviso,” said Santosh Maddila, principal data scientist, Aviso AI. “Its user-friendly interface, language clients, smooth ecosystem integration, and flexible API have streamlined our operations, providing exceptional ease of use. Astra DB isn’t just a tool; it’s an empowering force for developers to fully leverage Gen AI’s potential. The outstanding support from product and engineering teams has been instrumental in maximizing the benefits of Astra DB, ensuring a smooth and efficient experience throughout our development journey.”
“Astra DB is the backbone of our travel app at iWander, driving personalized audio guides through Gen AI,” said Antoine Nigond, chief technology officer, iWander. “Initially, we leveraged it for efficient storage using its Data API, streamlining user experience by retrieving cached guides for similar requests. As we develop our product further, we will integrate vector search to elevate recommendations based on user preferences and feedback. As a Python-centric team, we appreciate Astra DB’s user-friendly API for its seamless integration into our innovative application.”
See the new Data API and Astra DB developer experience in action at the live WikiChat launch event on January 24 where developers from DataStax and LangChain will break down the build of Wikichat—a Wikipedia-based, GenAI chat bot.
DataStax is the company that powers generative AI applications with real-time, scalable data with production-ready vector data tools that generative AI applications need, and seamless integration with developers’ stacks of choice. The Astra DB vector database provides developers with elegant APIs, powerful real-time data pipelines, and complete ecosystem integrations to quickly build and deploy production-level AI applications. With DataStax, any enterprise can mobilize real-time data to quickly build smart, high-growth AI applications at unlimited scale, on any cloud. Hundreds of the world’s leading enterprises, including Audi, Bud Financial, Capital One, SkyPoint Cloud, VerSe Innovation, and many more rely on DataStax to deliver real-time AI. Learn more at DataStax.com.
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