Live From New York! It’s RAG++, The AI Event
We spend a lot of time thinking about what it takes to get generative AI applications from the idea stage to production. Developers have a huge array of tools, solutions, components, and models to choose from to help them. It’s a good thing, but it’s also a challenge: so many tools to learn about, so many changes to keep up with.
These challenges—and how to address them—were common themes on Wednesday, when we held our latest RAG++ AI Event in New York City. A packed house of over 500+ developers, CXOs, founders, and others joined us on the banks of the Hudson River to learn from a range of DataStax customers and partners, including IBM, Glean, AWS, NVIDIA, Google Cloud, Unstructured, and more. They shared their experiences of working with DataStax and other GenAI technologies.
DataStax Chairman and CEO Chet Kapoor kicked off the afternoon with a look at the state of GenAI in 2024. Chet and DataStax CTO Davor Bonaci also discussed the work we’ve done so far to build a stack that provides developers with the fastest and surest path to production by solving the major parts of the AI development lifecycle—including app development, data ingestion and preparation, scalable and low-latency data hosting, and deployment to production.
Industry leaders participated in a panel discussion focused on improving AI-driven systems with frameworks like LangChain and LangGraph, the latest coding practices driven by natural language queries, and a focus on trust, quality, and guardrails in AI deployments. Other panel discussions focused on AI strategies in the healthcare and financial services industries.
Our AI Platform-as-a-Service was on full display during a live demo, when our developer relations leader Carter Rabasa built a GenAI movie search app in under 20 minutes with minimal code. The day ended with more code as we conducted a well-attended hack night (check out the RAG++ NYC YouTube channel for session footage).
But we did a lot more than share stories and knowledge. We unveiled several new integrations aimed at making it easier for developers to get their GenAI applications to production quickly.
Here’s a quick rundown of the news we announced.
A DataStax-hosted Langflow API
With the API in DataStax Langflow, developers can now build and host their GenAI application anywhere with a simple HTTP call to an API endpoint hosted by DataStax, providing a fast and easy path to production. This new addition to the DataStax AI PaaS is in public preview. Read more in the blog post, “Move From Experimentation to Production in a Flash with the DataStax Langflow API.”
Two new Unstructured integrations
Unstructured.io solves a key challenge that developers face when building retrieval-augmented generation apps: how to handle the broad range of enterprise data formats. So it only made sense to expand our partnership with Unstructured with two new integrations: our updated Astra Data Loader, which now supports PDFs, and the inclusion of Unstructured flexible document ingestion capabilities in the low-code IDE Langflow.
Read more in the blog post, “Supercharging Astra DB with Unstructured: Simplifying Document Ingestion for Generative AI.”
New Glean integrations
We unveiled a new integration that enables users to easily connect data stored in Astra DB with Glean, an enterprise AI search platform. With this integration, Glean will be able to directly access and analyze data stored in Astra DB, enabling the platform to answer complex questions and provide relevant, accurate query responses. Users also will be able to leverage a new Glean Component for DataStax Langflow, which enables developers to easily create Glean queries within a Langflow flow.
And there’s even more coming up! Join us in London on September 24 for RAG++ London - The AI Event, where industry experts from Google Cloud, AWS, Amplience, and more will help you understand how to get AI applications from idea to production much faster. Register now!