# Stem AI

**Canonical:** https://apis.io/providers/stem/  
**Website:** https://stemai.vc/  
**APIs profiled:** 0

StemAI (Stem AI SAS) is a Paris-based accelerator and early-stage investment program for founders building LLM-powered products. Its stated thesis is that large language models are already capable enough to build great products today, so the program backs product and user experience rather than research breakthroughs. Each accepted company receives a $250,000 SAFE investment, $350,000 in partner cloud credits, recurring checkpoints with AI advisors, help accessing follow-on funding, and a founder summit hosted in Paris. The program is led by Nicolas Granatino, with a board that includes Mehdi Ghissassi (AI71) and Severine Gregoire (Zebox Ventures), and advisors in residence drawn from Hugging Face, Datadog, InstaDeep, Dust, Photoroom, Helsing, Nabla, QuantHouse and Parrot. StemAI is a private company whose shares are quoted on the secondary markets (Forge, Hiive, EquityZen). It publishes no API, SDK, developer portal or machine-readable specification of any kind.

## Kin Score — 7.6 / 100 (minimal)

Scored 2026-08-17 under rubric 0.11.0. Trend: flat (+0.0 from 7.6).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Commercial Clarity | 13.2 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | 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 |

## Security (1)

- **Stem Domain Security** — TLSv1.3

## Tags

Company, Venture Capital, Accelerator, Artificial Intelligence, Large Language Models, Startups, France, Investment

---

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