# Vannevar Labs

**Canonical:** https://apis.io/providers/vannevar-labs/  
**Website:** https://www.vannevarlabs.com/  
**APIs profiled:** 0

Vannevar Labs is a defense technology company building agentic AI for national security and 21st-century conflict, pre-trained for intelligence missions. Its product portfolio spans open-source intelligence and document exploitation (Decrypt, Serra, TIE, Curator), maritime domain awareness (Revere, Foreshadow), information operations (Overwatch, Local), and mission augmentation (Telescope), deployed across U.S. military bases and partner forces. Vannevar Labs operates as a sales-led, ITAR-restricted defense vendor and does not publish a public developer portal or open APIs.

## Kin Score — 3.9 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 3.9).

| 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 | 0.0 |
| Access Clarity | 0.0 |

Regulatory layer — **Government & Public Sector**: 11.1 (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 (1)

- **Vannevar Labs Domain Security** — TLSv1.3 · DNSSEC · DMARC

## Tags

Agentic AI, Artificial Intelligence, Defense, Government, Information Operations, ITAR, Maritime Domain Awareness, National Security, OSINT

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