Learn How Cisco is Leveraging MongoDB Atlas Vector Search Across Numerous Applications

In this MongoDB video, we'll explore how Cisco is revolutionizing its data management and security with MongoDB Atlas Vector Search. Join Distinguished Engineer, Omar Santos, and Lead Data Scientist, Mustafa Kadioglu, as they discuss the role of MongoDB Atlas Vector Search in powering their cutting-edge Generative AI initiatives across the company. This session will explore the outstanding contributions of Vector Search to developer productivity, spotlighting its efficiency in integrating and retrieving data. This presentation will cover how this technology is enabling security, ensuring robust protection for AI-driven applications. Omar and Mustafa from Cisco's team will guide us through the intricacies of integrating AI and ML engineering into their security framework, demonstrating the power of MongoDB in handling complex, dynamic data across various applications. This session promises to be a deep dive into real-world applications of MongoDB, showcasing its performance, security, and ease of integration in enterprise environments.

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⏱️ Timestamps ⏱️
Introduction to Cisco's AI and ML Engineering [00:00:00 - 00:04:55]
- Introduction of Omar and Mustafa from Cisco.
- Overview of Cisco's Security and Trust Organization.
- Discussion on AI integration in Cisco's products and the focus on security during AI experimentation.

Leveraging MongoDB Atlas Vector Search [00:04:55 - 00:09:50]
- Explanation of how Cisco leverages MongoDB Atlas Vector Search for internal applications.
- Details on the numerous AI projects at Cisco and the Innovation Challenge initiative.

Security and Performance with MongoDB [00:09:50 - 00:14:45]
- Insights into the security measures and performance benefits of using MongoDB at Cisco.
- The importance of database encryption and Cisco's partnership with MongoDB.

Mustafa's Presentation on Webex QA Implementation [00:14:45 - 00:19:40]
- Mustafa presents the problem description, proposed solution, and a live demo of the Webex QA implementation.
- Discussion on the use of LLMs to expand capabilities and personalize answers.

Technical Architecture and Key Findings [00:19:40 - 00:24:35]
- Mustafa explains the technical architecture of their solution, including indexing, inference, and caching phases.
- Key findings on latency, caching mechanisms, and the importance of keeping databases up-to-date.

Q&A and Closing Remarks [00:24:35 - 00:29:30]
- Audience Q&A session with Omar and Mustafa.
- Closing remarks and appreciation for the presentation on Cisco's use of AI and MongoDB Atlas Vector Search.

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