The Death of Traditional APIs? Building AI-Ready APIs for the Agentic Era

Traditional REST APIs were designed for human-driven applications — mobile apps, web frontends, and tightly controlled integrations. But AI agents operate differently. They reason, discover tools dynamically, maintain context, and execute autonomous workflows.

This session explores why conventional API patterns are struggling in the era of Agentic AI and how organizations can evolve toward AI-ready architectures using MCP (Model Context Protocol), semantic tool discovery, vector-aware systems, and intelligent orchestration patterns.

Through live demos and enterprise architecture examples, attendees will learn how to transform traditional APIs into AI-consumable services that autonomous agents can discover, reason over, and securely execute.

The session includes practical implementation guidance using:

MCP Servers
SQL Server 2025 Vector Capabilities
Microsoft Fabric
AI Agents
Semantic Search
Tool Orchestration Patterns

Attendees will leave with a blueprint for designing the next generation of APIs optimized for AI-native systems.

Session Objectives

By the end of this session, attendees will:

Understand why traditional REST APIs are insufficient for autonomous AI agents
Learn the architectural differences between:
Human-centric APIs
AI-native APIs
MCP-based tool ecosystems
Explore how MCP enables:
Dynamic tool discovery
Context-aware orchestration
Autonomous AI workflows
Learn how vector search and semantic context improve API interactions for AI systems
Understand governance, security, and observability challenges in Agentic AI architectures
Build a reference architecture for AI-ready enterprise APIs using:
SQL Server 2025
Microsoft Fabric
MCP Servers
AI Agents
See a live end-to-end demo of an AI agent discovering tools, querying enterprise data, and executing actions autonomously

Building Multi-Agent Enterprise Systems with Microsoft Foundry and Copilot Studio

Session Abstract

Enterprise AI is rapidly evolving from single copilots to orchestrated multi-agent ecosystems capable of planning, reasoning, integrating enterprise data, and automating complex business workflows. In this deep technical session, attendees will learn how to design, build, and orchestrate scalable multi-agent systems using Microsoft Foundry, Copilot Studio, Azure AI services, and enterprise data platforms.

We will explore real-world architectural patterns for building intelligent agents that collaborate across tasks such as data retrieval, workflow automation, document intelligence, business process orchestration, and enterprise decision support. The session demonstrates how Microsoft Foundry enables secure agent hosting, orchestration, observability, memory management, and enterprise governance while integrating with Microsoft 365 Copilot and business applications.

Attendees will also learn how to connect enterprise agents with Microsoft Fabric, SQL Server 2025 vector capabilities, MCP-based integrations, and secure retrieval-augmented generation (RAG) architectures to build production-ready AI systems.

Through live demonstrations and architecture walkthroughs, this session provides practical guidance for moving beyond isolated copilots into scalable enterprise-grade multi-agent AI platforms.

Key Takeaways
Understand multi-agent architecture patterns using Microsoft Foundry
Build orchestrated AI agents with Copilot Studio and Azure AI
Integrate enterprise data using Microsoft Fabric and SQL Server 2025
Implement secure RAG and MCP integration patterns
Learn governance, monitoring, observability, and deployment best practices
Design scalable enterprise AI systems ready for production workloads
Audience
Enterprise Architects
AI Engineers
Solution Architects
Microsoft 365 Developers
Platform Engineers
Data & AI Professionals
Session Level

Intermediate to Advanced

AI-Augmented Data Architecture: Vector Search, RAG, and SQL Server 2025 in Enterprise Systems

Session Objective

Attendees will learn how to design AI-augmented enterprise data architectures using SQL Server 2025 vector capabilities combined with Microsoft Fabric and RAG-based AI systems.

This session focuses on transforming traditional databases into semantic intelligence layers that power modern AI applications.

Key Takeaways
Vector search in SQL Server 2025
Designing enterprise RAG pipelines
Semantic data architectures for AI
Integrating Fabric + SQL for AI workloads
Optimizing enterprise data for AI agents
Demo Highlight
Natural language query → vector search → insight generation
RAG pipeline with Fabric + SQL Server

Building AI-Powered Semantic Search, RAG, and Intelligent Data Applications Inside SQL Server

As AI-powered applications become mainstream, databases are evolving beyond traditional relational workloads. SQL Server 2025 introduces powerful vector architecture capabilities that enable organizations to build semantic search, Retrieval-Augmented Generation (RAG), similarity matching, and AI-driven applications directly inside the database platform.

In this demo-driven session, attendees will explore how SQL Server 2025 handles vector embeddings, vector indexing, similarity search, and AI-integrated query processing. The session will walk through the end-to-end architecture of storing embeddings, creating vector indexes, performing semantic searches, and integrating AI models with SQL workloads.

Through live demonstrations, participants will learn how SQL Server 2025 bridges the gap between traditional structured data and modern AI workloads while maintaining enterprise-grade security, governance, and scalability.

Whether you are a DBA, data engineer, architect, or AI developer, this session provides practical guidance for designing next-generation intelligent data platforms using SQL Server 2025.

AI-Augmented Data Architecture: Vector Search, RAG, and SQL Server 2025 in Enterprise Systems

Why this will get selected
Fabric is a core conference theme
Strong focus on real-time + analytics + AI activation
Very relevant for BI + Data Engineering audience
Session Objective

This session demonstrates how to build real-time intelligent data products using Microsoft Fabric and extend them with Agentic AI systems that transform insights into automated actions.

It bridges the gap between:

Data engineering pipelines
Real-time analytics
AI-driven decision systems
Key Takeaways
Designing real-time data pipelines in Microsoft Fabric
Turning data into AI-ready “decision streams”
Using event-driven architecture for analytics automation
Connecting Fabric with AI agents for action-based insights
Implementing data activation patterns
Demo Highlight
Real-time sales/ops data in Fabric
AI agent detecting anomalies
Automated insight + action workflow

Agentic DBA Copilot: Autonomous Ops for SQL Server at Scale

As SQL Server environments grow in scale and complexity, engineering teams struggle with noisy alerts, recurring performance issues, and time‑consuming investigation cycles. This session introduces Agentic DBA Copilot, a multi‑agent system built with Semantic Kernel and AutoGen that autonomously analyzes SQL telemetry, explains issues in plain language, and proposes safe remediations—while keeping humans firmly in control.
We’ll walk through how specialized agents collaborate—Planner, SQL Expert, Risk/Guardrails, and Explainer—to audit workloads, diagnose plan regressions, validate T‑SQL changes, and generate actionable fixes backed by evidence. You’ll learn architectural patterns for secure function calling, grounding with Query Store and DMVs, and approval‑based workflows that ensure reliability in production environments.
Attendees will leave with a practical blueprint for bringing agentic intelligence to SQL Server operations—accelerating troubleshooting, reducing toil, and enabling a safe path from assistive automation to autonomous remediation at enterprise scale.

Navigating the Future: SQL Server to Fabric Real-Time Intelligence

In today's data ecosystem, professionals face a critical decision: stick with familiar SQL Server technology or venture into Microsoft Fabric's Real-Time Intelligence (RTI) databases. This choice can significantly impact performance, scalability, and overall business intelligence capabilities. As a former SQL DBA and Microsoft Escalation Engineer who's worked extensively with both Azure Synapse and Fabric RTI, I'll guide you through this decision-making process with clarity and practical insights. We'll explore when SQL Server remains the optimal choice and when RTI databases offer compelling advantages. You'll discover the architecture differences that matter, performance considerations, and cost implications of each approach. I'll demonstrate how your existing SQL skills transfer to Kusto Query Language (KQL), showing familiar patterns and highlighting key differences. Through real-world scenarios and demonstrations, we'll examine migration paths, hybrid approaches, and integration strategies between these technologies. You'll see firsthand how these systems handle time-series data, complex analytics, and large-scale workloads differently. By the end of this session, you'll have a clear framework for database selection decisions and practical knowledge to implement or migrate to Fabric RTI when appropriate for your organization's needs.

Moving to Azure SQL from VM-based SQL

This will be an insightful session on transitioning from on-premises and VM-based SQL Server to Azure SQL. Discover the myriad benefits of moving to Azure SQL, including cost savings, enhanced features, ease of use, quick scaling, and improved reliability. I’ll explore various migration options to Azure SQL and discuss all the different versions available, such as Managed Instance, Hyperscale, Elastic Pool, and Serverless. Whether you’re interested in agility, security, or total cost of ownership, this session will provide you with the knowledge and tools to make an informed decision. Don’t miss out on learning how to transform your SQL Server infrastructure and unlock new opportunities with Azure SQL.

Heterogenous Migration Techniques

Learn methods and techniques available for heterogenous migrations. This session contains practical 5 methods to migrate data from SQL Server to PostgreSQL

Learn methods and techniques available for heterogenous migrations. This session contains practical 5 methods to migrate data from SQL Server to PostgreSQL

AI-Augmented Query Optimization: SQL Server 2025 Meets Fabric Self-Healing Data Platform

Session Description
SQL Server 2025 introduces advanced query optimization and observability features, while Microsoft Fabric delivers unified analytics and AI-driven insights. But how do we combine these innovations to create a self-healing data platform that minimizes downtime and maximizes performance?
This session is designed for DBAs, data engineers, and architects managing mission-critical workloads in hybrid or cloud environments. We’ll address a common pain point: manual troubleshooting of query regressions and performance bottlenecks. Instead, learn how to leverage SQL telemetry, Fabric ML notebooks, and AI-powered anomaly detection to automate root-cause analysis and remediation.
What you’ll gain:

A clear understanding of SQL Server 2025’s new optimization capabilities.
Practical steps to integrate Microsoft Fabric observability and AI for proactive performance management.
A blueprint for building a Self-Healing SQL Fabric Dashboard with real-world demos and POC architecture.

Walk away with actionable strategies to future-proof your data platform using AI-driven automation, Fabric analytics, and SQL Server 2025 innovations.