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This session will guide attendees through the process of building a Knowledge Store using Azure AI Search, enabling persistent storage of enriched data for downstream analytics and processing. Participants will explore the concept of projections, how to define a knowledge store within a search enrichment pipeline, and how to access and visualize the structured output. The session includes a hands-on exercise to implement a full knowledge store pipeline in Azure.

Read More - https://aka.ms/AzureAI-Search

The session will focus on:
Understanding projections and how to define them.
Defining and configuring a knowledge store.
Persisting enrichment outputs (e.g., key phrases, entities, image content) in a queryable form.
Accessing and analyzing the stored data using tools like Power BI or custom dashboards.
Hands-on Exercise: Build and test an enrichment pipeline with a connected knowledge store.

What will the attendees or a Start-up learn from the session?
Attendees, including start-ups, will gain the following:
How to extend AI Search capabilities with a knowledge store.
Techniques to extract, project, and store enriched data.
Real-world use cases for building intelligent knowledge apps.
How to integrate the knowledge store with reporting tools and downstream processing systems.
Best practices to design and scale knowledge stores in AI-driven applications. 🚀