Microsoft Reactor

Streamlit Meets Scenarios: Building Adaptive AI for the Enterprise

Enterprise needs are rarely static—they evolve fast and unpredictably. In this session, we demonstrate how to build and deploy a Streamlit-powered AI application tailored for dynamic use cases, using scenario-based templates like Coding Assistant, Document Summarizer, and more.

The solution serves both Web Clients via an MCP Wrapper and MCP-native clients like Claude.ai, offering seamless integration across platforms. The user interface is intuitive and highly configurable—users can select models, modify system prompts, download JSON logs, and manage multiple sessions effortlessly.

Session orchestration is powered by FastAPI, exposing a rich set of tools to start, monitor, and control interactions—whether initiated from the web or directly through the MCP Client.

Under the hood, Azure Container Apps and DAPR deliver scalable hosting and resilient performance, making this architecture ideal for demanding enterprise environments.