# Mosaic Ml

**Canonical:** https://apis.io/providers/mosaic-ml/  
**Website:** https://www.mosaicml.com  
**APIs profiled:** 0

MosaicML - now Databricks Mosaic Research - is a machine learning systems company that builds open-source tooling for training and deploying large neural networks and generative AI models faster and at lower cost. Its flagship open-source projects include Composer (a PyTorch library of training speedup methods), LLM Foundry (code for training and finetuning large language models), and Streaming (a library for streaming large datasets from cloud object stores into PyTorch training). MosaicML also shipped a managed training and inference platform driven by the mosaicml-cli (mcli) command-line tool; following the 2023 Databricks acquisition that platform is now offered as Databricks Mosaic AI. The company does not publish a standalone public REST/OpenAPI surface - its developer surface is Python packages, a CLI, and its open-source GitHub repositories.

## Kin Score — 17.7 / 100 (emerging)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 17.7).

| Facet | Score |
|---|---|
| Discoverability | 57.4 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 18.4 |
| Developer Ergonomics | 47.6 |
| Commercial Clarity | 0.0 |
| Access Clarity | 0.0 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| 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).

## Security (1)

- **Mosaic Ml Domain Security** — TLSv1.3 · HSTS

## Tags

Company, Machine-Learning, Artificial Intelligence, Generative AI, Large Language Models, Model Training, Deep Learning, MLOps, Open-Source, PyTorch

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