top of page
49213479862_ff582c9276_o_edited.jpg

DATASTAX is a dotai partner!

to help support the ai tech ecosystem in europe

A BOLD NEW WORLD

DataStax helps developers and companies build a bold new world through GenAI.

 

They provide a One-stop Generative AI Stack with everything needed for a faster, easier, path to production for relevant and responsive GenAI apps.

A One-Stop GenAI Stack for Rapid GenAI App Production

Building a RAG Application is Easy with DataStax Astra DB, LangChain and Javascript

Build Your Applications on the Open Data Stack

DataStax delivers an open, multi-cloud data platform built on Apache Cassandra™, the world’s most scalable database; and a multi-cloud messaging and event streaming platform built on Apache Pulsar™.

​​

ANNOUNCEMENTS

techday_7c829119a3cecb23abd4.webp

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

DataStax announced significant updates to its generative AI platform, accelerating Retrieval Augmented Generation (RAG) application development by 100x. Key updates include the release of Langflow 1.0, a drag-and-drop tool integrated with DataStax Cloud, simplifying GenAI application setup. A new partnership with Unstructured.io streamlines data preparation for AI applications.

 

DataStax also introduced Vectorise, easing vector embedding with support for multiple embedding providers. The release of RAGStack 1.0 offers a comprehensive solution for enterprise-scale RAG implementation, enhancing stability and performance. These updates enable developers to focus on building applications rather than managing infrastructure. 

Generative AI and Data: Using Knowledge Graphs and RAG Together
 

Generative AI faces challenges, notably “hallucinations,” where inaccurate information is produced. Retrieval Augmented Generation (RAG) mitigates this by using vector searches on company data but struggles with complex queries and redundant data. Combining RAG with knowledge graphs enhances accuracy by connecting related information and eliminating redundancy.

 

Knowledge graphs allow for precise, multi-step retrievals, improving AI responses. Implementing knowledge graphs alongside RAG can simplify data management and eliminate the need for separate graph databases. This approach improves response accuracy, reduces computational costs, and scales more effectively for large data sets in generative AI projects.

Un développeur asiatique de sexe masculin en train de faire un brainstorming
datastax image.webp

DataStax Underpins Base Blocks In AI Application Lifecycle

DataStax is enhancing the AI lifecycle by focusing on generative AI development. The company recently launched Langflow 1.0, a visual framework for building retrieval-augmented generation (RAG) applications, simplifying the integration of popular AI tools. They also partnered with Unstructured to streamline the conversion of diverse data types into AI-ready formats.

 

These advancements aim to reduce infrastructure overhead, allowing developers to concentrate on innovation rather than technical complexities. DataStax is positioning itself as a key player in making AI application development faster and more efficient. 

datastax.png

will be at dotAI 2024!

Datastax will be our exclusive partner, you can meet them at their booth during dotAI 2024! Do you have your ticket yet? If not, this might be your last chance to join!

bottom of page