#219 Avthar Sewrathan: How to Build Smarter AI Applications with PostgreSQL

This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.

NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.

In this episode of the Eye on AI podcast, Avthar Sewrathan, Lead Technical Product Marketing Manager at Timescale joins Craig Smith to explore how Postgres is transforming AI development with cutting-edge tools and open-source innovation.

With its robust, extensible framework, Postgres has become the go-to database for AI applications, from semantic search to retrieval-augmented generation (RAG). Avthar takes us through Timescale's journey from its IoT origins to disrupting the way developers handle vector search, embedding management, and high-performance AI workloads—all within Postgres.

We dive into Timescale's tools like PGVector, PGVector Scale, and PGAI Vectorizer, uncovering how they aid developers to build AI-powered systems without the complexity of managing multiple databases. Avthar explains how Postgres seamlessly handles structured and unstructured data, making it the perfect foundation for next-gen AI applications.

Learn how Postgres supports AI-driven use cases across industries like IoT, finance, and crypto, and why its open-source ecosystem is key to fostering collaboration and innovation.

Tune in to discover how Postgres is redefining AI databases, why Timescale's tools are a game-changer for developers, and what the future holds for AI innovation in the database space.

Don't forget to like, subscribe, and hit the notification bell for more AI insights!

Stay Updated:

Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Introduction to Avthar and Timescale

(02:35) The origins of Timescale and TimescaleDB

(05:06) What makes Postgres unique and reliable

(07:17) Open-source philosophy at Timescale

(12:04) Timescale's early focus on IoT and time series data

(16:17) Applications in finance, crypto, and IoT

(19:03) Postgres in AI: From RAG to semantic search

(22:00) Overcoming scalability challenges with PGVector Scale

(24:33) PGAI Vectorizer: Managing embeddings seamlessly

(28:09) The PGAI suite: Tools for AI developers

(30:33) Vectorization explained: Foundations of AI search

(32:24) LLM integration within Postgres

(35:26) Natural language interfaces and database workflows

(38:11) Structured and unstructured data in Postgres

(41:17) Postgres for everything: Simplifying complexity

(44:52) Timescale's accessibility for startups and enterprises

(47:46) The power of open source in AI