# PostgresML

**Canonical:** https://apis.io/providers/postgresml/  
**Website:** https://postgresml.org  
**APIs profiled:** 0

PostgresML brings machine learning and AI into PostgreSQL. Using the open-source pgml extension it runs embedding generation, LLM inference, vector search, and classic supervised learning (regression, classification, clustering) directly inside the database, so applications index, filter, and rank vectors and generate fact-based, real-time outputs without operating a separate ML or vector stack. It is consumed as SQL over the Postgres wire protocol and through the first-party Korvus SDK (Python, JavaScript, Rust, and C bindings), which unifies the entire RAG pipeline into a single database query. PostgresML Cloud offers managed serverless and dedicated Postgres databases with the extensions pre-installed, and PgCat provides connection pooling, sharding, and failover. There is no REST/HTTP API; authentication is a standard PostgreSQL connection string. Backed by Amplify Partners.

## Kin Score — 24.1 / 100 (emerging)

Scored 2026-08-19 under rubric 0.12.0. Trend: flat (+0.5 from 23.6).

| Facet | Score |
|---|---|
| Discoverability | 57.4 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 2.6 |
| Developer Ergonomics | 45.2 |
| Commercial Clarity | 44.7 |
| Access Clarity | 44.7 |

## Agent readiness — 8.5 (agent-aware)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | yes |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (2)

- **Postgresml Authentication** — connection-string · 1 scheme
- **Postgresml Domain Security** — TLSv1.3

## Tags

Company, Ai Ml, Machine Learning, Vector Search, Embeddings, PostgreSQL, RAG, LLM, Database

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/postgresml/). Scores are computed from the provider's own public artifacts under a published rubric.