# Product Science

**Canonical:** https://apis.io/providers/product-science/  
**Website:** https://www.productscience.ai  
**APIs profiled:** 0

Product Science provides end‑to‑end orchestration for decentralized foundation model training, enabling enterprises, research labs, and public institutions to train specialized AI models across fragmented, geo‑distributed resources. Their hardware‑agnostic approach leverages GPUs, ASICs, and other accelerators with configurable data sovereignty, aiming to lower barriers for frontier AI development and promote scalable, trustless training environments.

## Kin Score — 3.0 / 100 (minimal)

Scored 2026-10-31 under rubric 0.25.0.

| Facet | Score |
|---|---|
| Discoverability | 48.2 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Access Clarity | 0.0 |

Regulatory layer — **AI & Biometrics**: 5.5 (matched via residual_tags).

## Agent readiness — 3.1 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | documented |
| 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 |
| Delegated Identity | no |
| Protected Resource Metadata | no |
| Dynamic Client Registration | no |
| Agentic Commerce | no |
| Pagination Ratio | na |
| Operation Distinctiveness | na |

## Security (1)

- **Product Science Domain Security** — TLSv1.3 · HSTS · DMARC

## Tags

Company, AI, Decentralized-Training, Infrastructure, Frontier-AI

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