# Oumi

**Canonical:** https://apis.io/providers/oumi/  
**Website:** https://oumi.ai  
**APIs profiled:** 0

Oumi (Open Universal Machine Intelligence) is an open-source, Apache-2.0 platform for ML engineers and researchers to train, fine-tune, evaluate, and deploy foundation models (LLMs and VLMs) through a single unified interface. It ships as a Python library and a first-party command-line tool (train, evaluate, infer, launch, deploy, analyze, synth, tune) covering the full model development lifecycle — data synthesis, supervised fine-tuning, DPO/preference learning, evaluation judges, quantization, hyperparameter tuning, and inference across local, cloud, and HPC targets. A hosted managed platform (platform.oumi.ai) adds a Free/Pro/Enterprise product layer, and an oumi-mcp Model Context Protocol server exposes Oumi to MCP-capable assistants such as Claude and Cursor. Backed by Obvious Ventures.

## Kin Score — 23.1 / 100 (emerging)

Scored 2026-08-17 under rubric 0.11.0. Trend: flat (+0.0 from 23.1).

| Facet | Score |
|---|---|
| Discoverability | 57.4 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Operational Transparency | 21.1 |
| Developer Ergonomics | 63.0 |
| Commercial Clarity | 23.7 |

Regulatory layer — **Health**: 7.5 (matched via tags).

## Agent readiness — 10.8 (agent-aware)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| MCP Server | yes |
| Auth Clarity | no |
| 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).

## MCP servers (1)

- **oumi-mcp.yml**

## Security (1)

- **Oumi Domain Security** — TLSv1.3 · HSTS · DMARC

## Tags

Company, Economic Health, Artificial Intelligence, Machine Learning, LLM, Foundation Models, Fine-Tuning, Model Training, Open Source, MLOps, Developer Tools, Inference

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