How to Curate the Right Context for AI Agents

Generative AI is becoming essential in analytics, leading teams to expect AI agents to handle complex queries, automate analyses, and act on results, yet the challenge remains in transitioning from prototypes to production while providing large language models (LLMs) with the necessary context. Sigma focuses on curating context for AI, emphasizing the importance of three context pillars: data warehouse and transformation metadata, semantic layer integration, and user input, to ensure accurate and relevant AI outputs. This curated context helps AI models understand unique business definitions and logic, enabling more precise and aligned outputs. By integrating these elements, platforms like Sigma enhance AI's capacity to collaborate in analytical workflows, transforming them into interactive, data-driven applications that align with business needs.