PostgresML

Overview

PostgresML bridges machine learning with PostgreSQL databases, offering in-database model building, training, and deployment. It simplifies ML/AI workflows and delivers superior performance over microservices with support for over 50 algorithms.

From the official site

Run embeddings, vectors, and open-source LLMs on GPU-backed Postgres. Build RAG and ML apps with SQL or the Python and JavaScript SDKs.

The text above is quoted from this tool’s official website — the vendor’s own words.

Key points from the official site

• subtitles Embeddings
• manage_search RAG
• Embeddings

The points above are quoted from this tool’s own website sections and feature lists — vendor copy, not our review.

How to use it

1. Open postgresml.org, register and review the available capabilities and quotas
2. Create a project or obtain access credentials from the documentation
3. Complete a minimal call in your local or test environment using the examples
4. Once validated, integrate into the real project and expand usage gradually