Uploaded July 2026 | Updated September 2026, 3 weeks ago
In this session, participants will learn how to leverage Microsoft Copilot Studio and Code Interpreter to automate financial audit processes and gain actionable insights from financial data. The session focuses on transforming traditional manual audit activities into intelligent, AI-driven workflows that improve accuracy, efficiency, and decision-making.
Participants will discover how to build an AI-powered audit assistant capable of analyzing financial statements, identifying anomalies, detecting inconsistencies, generating audit summaries, and answering natural language questions about financial records.
Key Topics Covered:
- Introduction to AI-powered financial auditing
- Understanding Microsoft Copilot Studio for business automation
- Using Code Interpreter for financial data analysis
- Uploading and analyzing financial reports and spreadsheets
- Detecting anomalies, outliers, and compliance risks
- Generating automated audit findings and summaries
- Creating conversational audit assistants
- Building end-to-end audit workflows with AI Hands-On Project: Build a Financial Audit Copilot that can review financial data, identify potential issues, generate audit reports, and provide insights through a conversational interface.
Learning Outcomes:
- Understand AI applications in financial auditing
- Analyze financial data using Code Interpreter
- Create intelligent audit assistants with Copilot Studio
- Automate audit reporting and compliance checks
- Reduce manual effort while improving audit accuracy By the end of this session, participants will have a working AI-powered financial audit solution and a clear understanding of how to apply Copilot Studio and Code Interpreter to real-world finance and compliance scenarios.
[eventID:27358]
In this session, participants will learn how to leverage Microsoft Copilot Studio and Code Interpreter to automate financial audit processes and gain actionable insights from financial data. The session focuses on transforming traditional manual audit activities into intelligent, AI-driven workflows that improve accuracy, efficiency, and decision-making.
Participants will discover how to build an AI-powered audit assistant capable of analyzing financial statements, identifying anomalies, detecting inconsistencies, generating audit summaries, and answering natural language questions about financial records.
Key Topics Covered:
- Introduction to AI-powered financial auditing
- Understanding Microsoft Copilot Studio for business automation
- Using Code Interpreter for financial data analysis
- Uploading and analyzing financial reports and spreadsheets
- Detecting anomalies, outliers, and compliance risks
- Generating automated audit findings and summaries
- Creating conversational audit assistants
- Building end-to-end audit workflows with AI Hands-On Project: Build a Financial Audit Copilot that can review financial data, identify potential issues, generate audit reports, and provide insights through a conversational interface.
Learning Outcomes:
- Understand AI applications in financial auditing
- Analyze financial data using Code Interpreter
- Create intelligent audit assistants with Copilot Studio
- Automate audit reporting and compliance checks
- Reduce manual effort while improving audit accuracy By the end of this session, participants will have a working AI-powered financial audit solution and a clear understanding of how to apply Copilot Studio and Code Interpreter to real-world finance and compliance scenarios.
[eventID:27358]
![¿Y si tu próximo agente fuera una Logic App? Conversacional, autónomo y MCP Server
Cuando pensamos en construir agentes de IA, pensamos en frameworks, SDKs y todo el boilerplate que hay que montar antes de que el agente haga algo útil. Pero hay otro camino: Logic Apps ha incorporado el agent loop a su motor de workflows, ahora todo lo que ya tenía (conectores, ejecución durable, retries, monitorización, managed identities) se convierte en infraestructura de agentes que te viene dada.
En esta sesión, creamos en directo sobre un mismo escenario, un asistente de soporte interno, para poder compararlas bien: Parte 1, el agente conversacional. Creamos el agente desde el designer, le conectamos el modelo y le damos sus primeras tools usando conectores. Vemos cómo se depura de verdad: run history, transcripción del chat, y qué entra y sale del modelo en cada vuelta del loop. Y resolvemos el problema que casi nadie cuenta: el contexto de usuario.
Con autorización on-behalf-of, las tools dejan de ejecutarse con una cuenta de servicio y pasan a actuar con la identidad del usuario que está chateando: si el agente manda un correo, sale de tu buzón. Desplegamos el agente en Microsoft Teams. Parte 2, el agente autónomo.
Mismo escenario, pero sin nadie al otro lado: un trigger de evento arranca el workflow, el agente clasifica, decide y ejecuta por su cuenta. Vemos dónde colocar las agent actions dentro de un workflow normal, cómo combinar varias, y qué pasa con las ejecuciones de larga duración, los errores y la gobernanza cuando no hay un humano mirando.
Parte 3, la Logic App como MCP Server. Le damos la vuelta a la tortilla: en lugar de que el agente viva en Logic Apps, exponemos nuestros workflows como tools MCP para que los consuma cualquier agente externo, desde VS Code hasta el agente que tú quieras. Qué requisitos tiene que cumplir un workflow para ser una tool, cómo se gestionan las API keys y cómo montar varios MCP Servers en una misma Logic App.
Además, hablaremos sobre decisiones de arquitectura: Consumption con modelo gestionado por Microsoft o Standard trayendo tu propio modelo de Foundry, con sus diferencias en redes, autenticación, billing y desarrollo local. Si vienes del mundo pro-code, esta sesión te va a sorprender: no se trata de elegir entre código o designer, sino de saber cuándo el motor de Logic Apps te ahorra construir la mitad de tu plataforma de agentes.
Key Takeaways: Cómo construir agentes conversacionales y autónomos con el agent loop de Logic Apps, y en qué se diferencian Cómo ejecutar tools con la identidad real del usuario mediante autorización on-behalf-of Cómo desplegar tu agente en Microsoft Teams para que hable donde ya están tus usuarios Cómo exponer workflows como MCP Servers remotos consumibles desde cualquier agente o cliente MCP Consumption o Standard: qué SKU elegir según modelo, redes, billing y compliance.
🔗 Aprende más accediendo a los recursos: https://aka.ms/AgentsLogicApps
#MicrosoftReactor #LearnConnectuild #LogicApps #MCP
[eventID:27563] ¿Y si tu próximo agente fuera una Logic App? Conversacional, autónomo y MCP Server](https://i.ytimg.com/vi/Y-TNojksass/mqdefault.jpg)

![Architecting Context-Aware Agents with the Microsoft IQ Stack
Context-aware agents depend on a design that connects knowledge, enterprise data, work signals, and the live web.
Learn how the Microsoft IQ stack (Foundry IQ, Fabric IQ, Work IQ, and Web IQ) provides the enterprise intelligence layer for AI agents.
Map each layer onto a reference architecture, see where each one fits and how they compose, and learn how to choose the right intelligence for a given scenario.
Build a practical foundation for designing scalable, reliable, context-aware agents.
00:00 Welcome & Introduction
01:14 Why Context Matters for AI Agents
02:50 Understanding the Microsoft IQ Stack
04:07 Web IQ Overview
05:08 Web IQ Demo: Real-Time Grounding
07:57 Foundry IQ and Agentic Knowledge Retrieval
09:42 Fabric IQ and Business Data Understanding
11:13 Building a Hotel Agent with Foundry, Fabric, and Work IQ
17:27 Semantic Models vs Ontologies
22:54 Fabric Data Agents and Multi-Source Retrieval
26:30 Work IQ and Microsoft 365 Data
29:19 Agent 365 Autopilots Explained
33:29 Demo: Work IQ in Microsoft 365, GitHub Copilot, and Scout
37:30 Agent Identities, Permissions, and Security
44:31 Q&A: Permissions, Licensing, and Deployment Gotchas
52:34 Microsoft IQ Learning Resources and Upcoming Sessions
59:45 Closing Remarks
🔗 Resources: https://aka.ms/iq-series
📌 This event is a part of a series, learn more here: https://aka.ms/microsoftiqlive
[eventID:27386] Architecting Context-Aware Agents with the Microsoft IQ Stack](https://i.ytimg.com/vi/YOHnkoQ4Jic/mqdefault.jpg)

![Get Certified: Which Data Exam Fits You Best?
Not sure where to start? With options like PL-300, DP-600, DP-700, DP-800, and DP-900, it is easy to feel stuck before you even begin.
In this session, we will break down each exam and the role it maps to, from Power BI Data Analyst to Fabric Analytics Engineer, Fabric Data Engineer, and SQL AI Developer. You will get a clear sense of what each exam covers, how they differ, and which one fits your background, interests, and goals.
We will also share practical tips on how to choose your path with confidence so you can avoid spending time on the wrong thing and focus on what actually moves you forward. By the end, you will know exactly where to start and what to do next.
🔗 Register for Data Days: https://aka.ms/datadays
📍 This session is a part of a series. Learn more here: https://aka.ms/datadayslive/cert-y
#MSFTReactor #learnconnectbuild #DataDays #GetCertified
Chapter markers:
0:00 Introduction and housekeeping
0:58 Speakers introduction
2:00 Data Days overview and resources
3:10 Fabric community and contests
4:06 Power BI Data Viz World Championship
4:53 User panels
6:34 Moderator introductions
7:12 Agenda overview
8:14 Microsoft certifications explained
9:45 DP-900: Azure Data Fundamentals
11:30 Role-based certifications overview
12:46 PL-300: Power BI Data Analyst
15:07 DP-600: Fabric Analytics Engineer
19:07 DP-700: Fabric Data Engineer
23:46 DP-800: SQL AI Developer Associate
29:05 Q&A: Experience requirements
30:28 Q&A: Overlap between exams
32:28 Q&A: Job roles for DP-800
33:36 Q&A: Exam resources and strategy
35:10 Deciding which exam is right for you
36:18 Additional sessions and closing resources
37:54 Q&A: Deep dive into exam content and recommendations
42:33 Q&A: Study groups
44:24 Q&A: Why get certified?
47:11 Q&A: Exam format and structure
48:36 Q&A: Exam order recommendations
50:11 Closing remarks
[eventID:27217] Get Certified: Which Data Exam Fits You Best?](https://i.ytimg.com/vi/YViNorNYV3c/mqdefault.jpg)
![Give Microsoft AI Agents Communication Superpowers
In this webinar, youll learn how to use Infobips MCP servers to give your AI agents running on Azure communication tools.
From personal Al assistants to scalable customer support and marketing agents, discover how to build agents that reach, engage, and deliver outcomes through global communications.
🔗 https://aka.ms/UnlockAIAgentCommunication/Blog
🔗 https://aka.ms/MCPcenter
🔗 https://aka.ms/AIagentsAzure
Explore the documentation for the three showcased examples below:
🔗 Weather Agent: https://www.infobip.com/docs/tutorials/build-sms-weather-agent-copilot-studio
🔗 GitHub Issue Agent: https://www.infobip.com/docs/tutorials/build-github-security-alert-agent
🔗 Trivia Agent: https://www.infobip.com/docs/tutorials/build-whatsapp-trivia-agent
Ready to give your Microsoft AI agents communication superpowers? 🚀
0:13 - Introduction to the Session
1:03 - What is Infobip & Communication Platforms
3:52 - Understanding MCP (Model Context Protocol)
6:44 - Overview of the Three AI Agent Demos
7:31 - Demo 1: Weather Agent (using Copilot Studio)
17:08 - Demo 2: GitHub Security Issue Agent (using Microsoft Foundry)
32:12 - Demo 3: WhatsApp Trivia Agent (using Microsoft Foundry)
54:10 - Resources, Summary, and Q&A
#MicrosoftReactor #LearnConnectBuild
[eventID:27362] Give Microsoft AI Agents Communication Superpowers](https://i.ytimg.com/vi/Yht3hOf-MQU/mqdefault.jpg)

![Resumo Digital da Build: Português
O Microsoft Build (https://build.microsoft.com) nos apresenta o que vem a seguir.
Esta sessão foca no que isso significa para você. Participe de um walkthrough curado com os anúncios mais relevantes do Build, traduzidos em insights práticos e relevantes para a sua região. Conheça as perspectivas de GitHub, DevRel e expertos locais sobre como aplicar essas inovações em cenários reais e o que os desenvolvedores devem priorizar a seguir.
Saia com uma visão clara do que importa, do que observar e de como transformar o impulso do Build em ação.
📍https://aka.ms/Build2026/digital-recaps
Capítulos:
0:00 - Introdução e Boas-vindas
1:07 - Contexto do Microsoft Build 2026
2:59 - Introdução ao Microsoft IQ
6:52 - Novidades nos Modelos de IA (My AI)
11:56 - GitHub Copilot App e Workflow
16:12 - Open Cloud no Windows e Segurança
20:11 - Hardware: Surface RTX Spark Dev Box
23:16 - Hosted Agents no Microsoft Foundry
24:43 - Segurança com Agente 365
28:34 - Avanços em Computação Quântica
32:31 - Microsoft Discovery: Pesquisa e Desenvolvimento
35:01 - Dicas e Considerações Finais
36:49 - Perguntas e Respostas sobre o Discovery
41:11 - Encerramento
#MSFTReactor #learnconnectbuild
[eventID:27267] Resumo Digital da Build: Português](https://i.ytimg.com/vi/Yx9TTyi75jU/mqdefault.jpg)
![Agent Build Along Series: Build Your 1st Agent
Join this interactive, hands-on session where youll learn how to design, build, and test your own AI agents using practical, real-world techniques. From defining an agent’s purpose and goals to connecting the right data and knowledge sources, youll gain a step-by-step framework for creating intelligent solutions that deliver meaningful outcomes.
Through guided exercises and live demonstrations, youll explore how to evaluate agent performance, refine behavior, and adapt agents to real business scenarios. Whether youre just getting started or looking to enhance existing solutions, youll leave with a working agent, a repeatable development approach, and the confidence to apply AI agents to solve everyday business challenges.
🔗https://aka.ms/AgentsBuilder901
📌 This event is a part of a series, learn more here: https://aka.ms/AgentBuildAlongSeries
0:06 Introduction and Housekeeping
0:59 Welcome and Session Overview
2:10 Accessing Build-Along Materials (GitHub)
3:38 Navigating to Agent Builder
5:50 Naming and Describing the Agent
8:03 Configuring Agent Instructions
10:44 Understanding Model Logic (Auto vs. Think Deeper)
11:56 Uploading Knowledge/Grounding Data
14:28 Setting Up Suggested Prompts
18:18 Recap of Configuration Steps
19:25 Creating and Launching the Agent
21:04 Testing the Agent and Validating Sources
24:46 Advanced Features: Scheduling and Exporting
27:56 Sharing and Collaboration
31:18 Choosing LLM Models
34:36 Admin Monitoring and Security (Agent 365)
35:54 Understanding Agent vs. Co-pilot
40:54 Q&A and Closing Remarks
[eventID:27407] Agent Build Along Series: Build Your 1st Agent](https://i.ytimg.com/vi/ZB5m0BfcxAM/mqdefault.jpg)
![Microsoft Agent Framework Office Hours for June 17, 2026
Learn more: https://aka.ms/maf
These 60-minute live office hours are where you can connect with the Microsoft Agent Framework team to get your questions answered live.
Find our past episodes on demand at: https://aka.ms/maf-officehours-playlist
[eventID:23448] Microsoft Agent Framework Office Hours for June 17, 2026](https://i.ytimg.com/vi/ZfwkrhhSOmE/mqdefault.jpg)
![Arquitectura completa: agentes de Power BI end-to-end en producción
La sesión final integra todo lo aprendido en una arquitectura agéntica end-to-end sobre Power BI.
Diseñaremos un sistema donde un agente orquestador usa el Remote MCP para responder preguntas de negocio sobre datos en vivo, el Local MCP para mantener y evolucionar el modelo semántico, y PBIP + Git + CI/CD para gobernar los cambios en producción.
Hablaremos de patrones reales de adopción: cómo gestionar la autenticación con Service Principal para agentes autónomos, cómo controlar qué operaciones requieren confirmación humana y cuáles pueden ejecutarse sin intervención, y cómo monitorizar lo que los agentes hacen sobre tus modelos.
Cerraremos con una hoja de ruta práctica — qué está GA, qué está en Preview, qué viene en los próximos meses — y los últimos 15 minutos serán Q&A abierto con casos reales de la audiencia.
Arquitectura completa: agentes de Power BI end-to-end en producción: https://learn.microsoft.com/en-us/power-bi/developer/mcp/mcp-servers-overview/?wt.mc_id=youtube_27346_organicsocial_reactor
📌 Este evento es parte de una serie, aprende más aquí: https://aka.ms/PBIMCP
0:05 Introducción y bienvenida
0:51 Inicio de la sesión: Saga de agentes y Power BI
2:44 ¿Qué es Power BI Desktop Bridge?
4:50 Requisitos e instalación de Bridge
8:40 Funcionamiento y automatización
12:41 Gestión de costos y presupuestos
16:23 Resultados y diseño del modelo semántico
19:28 Caso práctico: Agente de datos end-to-end
28:56 Manos a la obra: Configuración en VS Code
38:42 Estructura del archivo Agent.md
48:43 Validación y autocorrección del modelo
54:48 Fase de construcción del modelo semántico
1:05:04 Validación de modelo y resolución de errores
1:22:04 Diseño de visualizaciones y fase final
1:38:21 Capturas de pantalla y revisión de errores
1:43:33 Conclusiones y cierre de la saga
[eventID:27346] Arquitectura completa: agentes de Power BI end-to-end en producción](https://i.ytimg.com/vi/ZmQiivL32y4/mqdefault.jpg)