DataStax to Launch Massive New AI Platform Updates at RAG++ Event in San Francisco; Partners Attending: LangChain, Microsoft, Mistral AI, NVIDIA, Unstructured.io, and More
June 24 2024 - 9:00AM
Business Wire
Featuring End-to-end Platform that Makes AI
Application Development 100x Faster Across the Entire AI
Application Lifecycle: Data Preparation and Readiness; Application
Development; Real-Time Data; and Deployment
RAG++ -- DataStax, the AI platform company, today
announced major updates to its Generative AI development platform
that help make retrieval augmented generation (RAG) powered
application development 100X faster. DataStax will demo its newly
released updates at the RAG++ event tonight in San Francisco with
partners including LangChain, Microsoft, NVIDIA, and Unstructured,
among others.
With DataStax, developers can focus on application development,
rather than infrastructure management, powered by multiple, new
updates:
Launching Langflow 1.0 and DataStax Langflow
In April, DataStax acquired Langflow, the popular, open source
visual framework for building RAG applications. Now, DataStax is
releasing Langflow 1.0, which includes a version of Langflow that’s
hosted in the DataStax Cloud platform.
Langflow 1.0’s drag and drop interface, with dozens of
integrations with the top Gen AI tools: LangChain, LangSmith,
OpenAI, Hugging Face, Mistral, and others, makes it easy for
developers to set up, swap, and compare all the major large
language model and embedding providers.
This gives developers tremendous flexibility to easily compare
different providers and their results. Developers can now make
major changes in just minutes instead of having to learn new APIs
and re-coding their applications.
Additionally, as part of the Langflow 1.0 open source release,
developers can now leverage LangSmith’s observability service to
trace an application’s responses for more relevant, accurate
LLM-based applications.
For more information, read the DataStax Langflow launch blog
post.
Making Data RAG-ready with Unstructured.io
A new partnership between DataStax and Unstructured enables
enterprises and developers to easily make their enterprise data
ready for AI, handling the data ingestion and chunking across data
types: PDFs, Salesforce, Google Drive, etc to use in AI
applications.
Developers benefit from lightning-fast data ingestion through
quick conversion of large data sets and common document types into
vector data. This new integration then enables these embeddings to
be quickly written to Astra DB for highly relevant GenAI similarity
searches. And, when managing very large datasets, users are able to
convert that data into embeddings and write them to Astra DB in
just minutes.
Read more about the Unstructured partnership.
Leverage the Largest Ecosystem of Embedding Providers in
Minutes, with DataStax Vectorize
Vectorize simplifies vector generation by letting developers
choose an embedding service, configure it with Astra DB, and start
building right away. Most embedding is currently handled
“client-side”- meaning that Developers need to learn many different
APIs. With DataStax Vectorize, vector embedding now happens on the
server; meaning developers only need to learn one API to now access
the 8 most popular embedding providers, and compare results between
them. DataStax has partnered with the top embedding providers to
offer robust choice, with simplified implementation that only
requires users to configure a single API to create embeddings.
Partner embedding providers include: Azure OpenAI, Hugging Face,
Jina AI, Mistral AI, NVIDIA, OpenAI, Upstage AI, and Voyage AI.
Read more about DataStax Vectorize.
Bringing the Best of GenAI Open Source Together with RAGStack
1.0
Since the launch of RAGStack in December 2023, DataStax has
added continued depth and breadth to the product with the additions
of several key features, integrations, and partnerships, all
available now in the RAGStack 1.0 release – the production-ready,
out of the box solution that streamlines RAG implementation at
enterprise scale, with an efficient set of tools, techniques, and
governance.
Every company building with GenAI right now is looking for the
most effective way to implement RAG within their applications.
Enterprises need proven paths to success with GenAI. They’re
dependent on external APIs that have no guarantees, release on
their own schedule, and often threaten the stability of the
applications they’re serving. Enterprises can’t depend on
unsupported open source projects or vendors who can’t effectively
support the needs and scale of their GenAI projects.
RAGStack’s 1.0 release provides stability to all GenAI
applications and frameworks by offering the best of open source and
the latest techniques required for enterprise use cases. RAGStack
1.0 includes multiple new features:
- Langflow in RAGStack - users can build applications faster with
Langflow using RAGStack’s version of components tested for
compatibility, performance and security.
- Knowledge Graph RAG - provides a graph-based representation
designed specifically for GenAI applications to store and retrieve
information more efficiently and accurately than vector-based
similarity search alone with Astra DB.
- ColBERT in RAGStack with Astra DB - the first production-ready
implementation delivering significantly better recall than any
single-vector encodings, backed by Astra DB.
- Introducing Text2SQL/Text2CQL to bring structured,
semistructured and unstructured context into the GenAI flow
activating existing data with additional benefits.
- Vectorize in RAGStack and LangChain - enabling the open source
frameworks to leverage a new server side embedding pattern with
chains.
Read more about the RAGStack 1.0 release.
Supporting Quotes:
- “The Generative AI stack is a big and complex ball of
technology that many are working to get their arms around. We’re
focused on helping developers stay true to their roots so they can
do what they do best: build and develop, rather than worrying about
application infrastructure. We’re delivering a cutting-edge,
end-to-end stack to make this a lot easier,” said Ed Anuff,
chief product officer, DataStax. “From the launch of Langflow
in Astra, to bringing the largest ecosystem of embedding providers
together in one place, we’re delivering on our promise to make
GenAI application development as fast and simple as possible so
organizations can get their apps in production quickly, for
immediate impact.”
- “Mistral AI paves a seamless path for developers to generate
embeddings,” said Sophia Yang, Ph.D., head of developer
relations, Mistral AI. “Our collaboration with DataStax
accelerates development, allowing developers to focus on refining
core functionalities while streamlining the complexity of embedding
models.”
- “Partnering with DataStax, Unstructured equips developers with
the tools to seamlessly extract and transform complex data, storing
it in Astra DB Vector to power LLM-based applications,” said
Brian Raymond, founder and CEO, Unstructured. “This
partnership significantly enhances GenAI applications by delivering
faster data retrieval, reducing computational overhead, and
boosting scalability.”
- “Upstage is thrilled to partner with DataStax to offer
unparalleled performance and cost-effectiveness of running our
full-stack LLM solution within Astra Vectorize,” said Sung Kim,
co-founder and CEO, Upstage. “Our partnership with DataStax
enables us to provide developers with solutions that drive tangible
results, all while abstracting the complexity of embedding models
from the application code.”
- “With Vectorize, developers gain unprecedented access to
advanced AI capabilities,” said Saahil Ognawala, head of
product, Jina AI. “By integrating Jina Embeddings within
Vectorize, DataStax simplifies the development journey, empowering
developers to focus on refining their core functionalities without
the hassle of external system integrations.”
- “Our domain-customized embedding models, seamlessly integrated
into Astra Vectorize, promise enhanced retrieval quality and
optimized workflow, abstracting the complexity of embedding models
from the application code,” said Tengyu Ma, CEO, Voyage AI.
“Through this partnership, we’re empowering developers to achieve
meaningful application outcomes through an enhanced developer
experience.”
About DataStax
DataStax is the company that helps developers and companies
successfully create a bold new world through GenAI. We offer a
one-stop generative AI stack with everything needed for a faster,
easier, path to production for relevant and responsive GenAI
applications. DataStax delivers a RAG-first developer experience,
with first-class integrations into leading AI ecosystem partners,
so we work with developers’ existing stacks of choice. With
DataStax, anyone can 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, and many more rely on DataStax. Learn more at
DataStax.com.
© 2024 DataStax Inc., All Rights Reserved. DataStax is a
registered trademark of DataStax, Inc. and its subsidiaries in the
United States and/or other countries.
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DataStax Regan Schiappa press@datastax.com