# Andesite

**Canonical:** https://apis.io/providers/andesite/  
**Website:** https://andesite.ai/  
**APIs profiled:** 0

Andesite is a cybersecurity company building a Human+AI Security Operations Center (SOC) platform that connects human analysts, AI agents, and security data to automate and accelerate threat detection, investigation, and response. Its Decision Fabric connects data silos and organizational context, while Evidentiary AI provides audit trails for every AI-driven action. Andesite deploys as SaaS or self-managed, carries FedRAMP High Authorization and SOC 2 Type II compliance, and is a General Catalyst portfolio company operating in the defense and government sector.

## Kin Score — 12.4 / 100 (emerging)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 12.4).

| Facet | Score |
|---|---|
| Discoverability | 57.4 |
| Contract Quality | 0.0 |
| Governance | 18.2 |
| Contract Governance | 18.2 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 7.1 |
| Commercial Clarity | 10.5 |
| Access Clarity | 10.5 |

Regulatory layer — **Government & Public Sector**: 27.8 (matched via tags).

## 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 (2)

- **Andesite Domain Security** — TLSv1.2 · DMARC
- **Andesite Trust Center** — FedRAMP High, SOC 2 Type II

## Tags

Company, Defense Government, Cybersecurity, Security Operations, Artificial Intelligence, Threat Detection, SOC, Compliance

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