How to Scale Data Integration
for Generative AI with Nexla
and Amazon Bedrock
Get practical advice on how to streamline and scale all of your data integration pipelines with Nexla to and from Amazon Bedrock for generative AI applications and models.
What you’ll learn:
- Efficient methods to feed unstructured data into Amazon Bedrock including via S3.
- Techniques for turning text data and documents into vector embeddings and structured data.
- Practical insights into scaling data integration for generative AI with Nexla and Amazon Bedrock.
- Real-world applications of Nexla’s RAG data flow capabilities in enhancing AI deployment.
The live product demo includes:
- Introduction to Nexla and Amazon Bedrock’s roles in data integration and AI model development.
- Demonstrations of direct data integration methods and strategies for enriching AI models with diverse data sources.
- Examples showcasing Nexla’s RAG capabilities and their impact on AI performance and insights.
Join us to explore advanced data integration strategies and harness the power of Nexla and Amazon Bedrock for driving innovation in your AI initiatives.
Sathya is a senior solutions architect at AWS. He is a seasoned software engineer with expertise in embedded operating systems, distributed applications, microservices, and cloud computing. Passionate about solving real-world problems with elegant software solutions, Sathya is dedicated to mission-critical systems that enable people to excel in crucial moments.
Gabriel is a solutions architect at Nexla. He is an expert in data integration and is seasoned in designing data architectures and building data pipelines. As Nexla’s GenAI Ambassador, Gabriel leads the exploration of AI use cases and the creation of compelling demo scripts, driving innovation and demonstrating the transformative potential of AI in data engineering.