Developers are under increasing pressure to deliver AI systems such as search engines, access augmented generation (RAG) and AI agents. But this often involves managing complex workflows across multiple tools: embedding rendering, data processing, and real-time synchronization.

New specialized vehicles appear every day, increasing the infrastructure burden and requiring new expertise, but few have the operational maturity or flexibility needed for production.

Pgai Vectorizer integrates the entire embedding process into PostgreSQL, allowing developers to create, store and manage vector embeddings alongside relational data without the need for external tools or additional infrastructure.

It integrates the entire AI workflow into PostgreSQL along with the full pgai suite, simplifying complex workflows into a single system. This allows developers to create state-of-the-art AI applications with fewer resources using familiar SQL commands.

“(I feel) pgai Vectorizer is a game changer. “Pgai Vectorizer promises to streamline our entire AI workflow, from rendering deployment to real-time synchronization, by integrating everything directly into PostgreSQL, allowing us to deliver AI applications faster and more efficiently,” said MarketReader CTO Web Begole. “The need for external tools and expertise makes it easier for our team to focus on innovation rather than infrastructure.”

Thousands of developers already use the pgai suite of AI tools, and with pgai Vectorizer they now have even greater power to streamline workflows and accelerate AI development.