# Mirendil

**Canonical:** https://apis.io/providers/mirendil/  
**Website:** https://mirendil.com/  
**APIs profiled:** 0

Mirendil is a frontier AI research lab founded by veterans of Anthropic, xAI, Google DeepMind, and OpenAI and led by CEO Behnam Neyshabur and CTO Harsh Mehta. The company is building self-accelerating AI R&D: training frontier models that are exceptional at AI research and then redesigning the entire research loop around them to make it faster, more capable, and more autonomous. Its stated goal is to put frontier AI R&D in everyone's hands so people closest to a problem can stay on it, with applications spanning drug discovery, chemistry, biology, materials science, and robotics. Mirendil raised a $200M seed round at roughly a $1B valuation co-led by Andreessen Horowitz and Kleiner Perkins with participation from Nvidia. As of mid-2026 the company has no public API, developer portal, SDK, or documentation surface.

## Kin Score — 5.0 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 5.0).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| 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)

- **Mirendil Domain Security** — TLSv1.3 · DMARC

## Tags

Company, Artificial Intelligence, Machine-Learning, Research Lab, Frontier Models, AI Research

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