# Minersai

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

MinersAI applies artificial intelligence and machine learning to geoscience data for mineral exploration, mining operations, public geological authorities, and mining & minerals investors. Founded and run by geologists (CEO Tomi de Lophem, CTO Mason Dykstra) and backed by Speedinvest and the Creative Destruction Lab, MinersAI structures, cleans, QCs, feature-engineers, and standardizes geochemical, geophysical, and remote-sensing datasets, then applies anomaly detection, heatmap generation, dimensionality reduction, and geostatistical interpolation to surface high-potential exploration targets. Its "geologists-in-the-loop" approach keeps domain experts central rather than replacing their expertise. The platform is delivered as a gated web application (app.minersai.com); there is no public developer API surface at this time.

## Kin Score — 12.3 / 100 (emerging)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 12.3).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 2.4 |
| Commercial Clarity | 34.2 |
| Access Clarity | 34.2 |

## 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)

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

## Tags

Company, Artificial Intelligence, Machine-Learning, Geoscience, Mineral Exploration, Mining, Geology, Data Standardization

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