Getting Started with Generative AI Infrastructure

GenAI is a priority for enterprises large and small – but there are some core challenges that need to be overcome to move from idea to production with speed and scale. These include managing diverse data formats that range from structured tables to unstructured text files and PDFs.

This guide is a roadmap for enterprises adopting GenAI technologies to generate and scale content, analyze unstructured data, and improve decision-making processes—enabling impactful, future-ready AI solutions.

In this guide, you’ll learn how to:

• Design a robust infrastructure for Generative AI that enables scalable content generation, recommendation systems, and beyond
• Apply vector embeddings to structure data for seamless machine learning processing
  Integrate and optimize diverse data sources using industry-leading tools like Nexla’s Data + AI platform
• Implement best practices in security and data management to ensure reliable and efficient AI performance

Key topics include:

• Vector Embeddings: Transform unstructured data into actionable insights with foundational embedding techniques
• Data Integration & Workflow Management: Streamline data flows to unlock the full potential of your AI systems
• Security & Scalability: Adopt best practices to build secure, scalable AI infrastructures that are ready for the future
• Real-World Applications: Explore how generative AI supports e-commerce, sentiment analysis, language translation, and more