Nasdaq Boardvantage: AI-driven governance on PostgreSQL and Microsoft Foundry | BRK137
Dec 9, 2025•Channel
AI Analysis
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Video Overview
Video Details
Published6 months ago
Duration38:22
Video IDBkOcPQntsk4
Languageen
CategoryScience & Technology
PrivacyPublic
Made for KidsNo
Video TypeRegular Video
Performance Metrics
Views428
Likes12
Comments0
Engagement Rate2.80%
Likes per 100 views2.80
Comments per 1K views0.00
Video Tags
#brk137#innovate with azure ai apps and agents:azure postgresql#innovate with azure ai apps and agents:microsoft foundry#nasdaq boardvantage: ai-driven governance on postgresql and microsoft foundry | brk137#unify your data platform#f5n1#ignite#ignite 2025#microsoft#microsoft ignite#microsoft ignite 2025#ms ignite#ms ignite 2025#msft ignite#msft ignite 2025
Description
Trusted by nearly half of Fortune 100 companies, Nasdaq Boardvantage powers secure, intelligent board operations. In this deep dive session, explore how Azure Database for PostgreSQL and MySQL, Microsoft Foundry, Azure Kubernetes Service (AKS), and API Management create a resilient architecture that safeguards confidential data while unlocking new agentic AI capabilities.
To learn more, please check out these resources:
* https://aka.ms/ignite25-plans-MicrosoftFabricAIDataSolutionsPlan
𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀:
* Charles Feddersen
* Mohsin Shafqat
𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:
This is one of many sessions from the Microsoft Ignite 2025 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com
BRK137 | English (US) | Innovate with Azure AI apps and agents, Azure PostgreSQL, Microsoft Foundry
Breakout | Advanced (300)
#MSIgnite, #Unifyyourdataplatform
Chapters:
0:00 - Overview of NASDAQ Board Vantage using Azure open-source databases
00:09:15 - NASDAQ’s cloud journey and regulatory compliance using Azure
00:12:08 - Benefits of Azure adoption: scalability, reduced infrastructure management, and use of Azure AI Foundry
00:14:26 - Evaluating AI opportunities leads to Smart Document Summarization and AI Meeting Minutes features
00:22:33 - Storing extracted data in PostgreSQL with PG Vector for efficient hybrid search
00:23:09 - Generating finalized meeting minutes by matching agenda sections with relevant data
00:29:29 - Challenges with existing microservices and introduction of fan-in fan-out orchestration approach
00:31:53 - Detailed chat assistant architecture using Azure functions and vector database
00:33:39 - Using Azure AI Foundry and Prompt Flow to address determinism and hallucination challenges