Presented by:

Noor Aftab is a recognized leader in AI and data, known for driving innovation at the intersection of AI, automation, and cloud computing. As a Senior Program Manager at Amazon Web Services (AWS) and an IBM Influencer, she develops AI-powered solutions that enhance enterprise scalability and decision-making.

A sought-after speaker, Noor has delivered talks at PyData Global, IBM TechXchange, and IEEE, sharing insights on AI-driven transformation, intelligent automation, and data-driven innovation. She has led the development of AI solutions like Ticket Copilot, integrating machine learning and automation to optimize workflows.

Beyond her work at AWS, Noor leads the IBM Women in AI user group, is a Community Manager at AI Camp, and serves on the NumFOCUS CoC Working Group, where she supports inclusivity in open-source AI and data science communities. Her expertise in AI and data solutions positions her at the forefront of industry advancements, helping organizations harness AI.

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Postgres is widely used for structured data storage and querying, but with the rise of AI-driven applications, traditional search mechanisms often fall short. Vector search—critical for recommendation systems, chatbots, and AI-enhanced retrieval—has emerged as a game-changer. But when should developers extend Postgres with AI-powered search engines like FAISS and Pinecone, and when should they rely on Postgres-native extensions such as pgvector?

This session will explore:

How AI-powered search enhances Postgres applications Postgres vs. FAISS vs. Pinecone: Key differences in search performance & scalability Real-world use case: How Ticket Copilot integrates AI-powered retrieval with Postgres Choosing the right tool: When to use Postgres-native extensions vs. external vector databases By the end, attendees will understand how to integrate AI-driven search while leveraging Postgres' strengths, ensuring high-performance, scalable, and intelligent applications.

Date:
Duration:
20 min
Room:
Conference:
Postgres Conference 2025
Language:
Track:
Variants and Cloud
Difficulty:
Medium