# Calibrate Ventures

**Canonical:** https://apis.io/providers/calibrate-ventures/  
**Website:** https://www.calibratevc.com  
**APIs profiled:** 0

Calibrate Ventures is a Pasadena, California venture capital firm backing visionary technical founders scaling deep tech to transform industries such as transportation and logistics, food and agriculture, healthcare, manufacturing, security, and warehousing. The firm invests in AI, computer vision, machine learning, robotics, and automation startups, partnering with founders to turn a technical breakthrough into scalable commercial advantage and drawing on decades of combined investment and company-building experience. This profile was surfaced as a portfolio-adjacent company in the API Evangelist network and enriched from the firm's public web presence.

## 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)

- **Calibrate Ventures Domain Security** — TLSv1.3 · DMARC

## Tags

Company, Venture Capital, Deep Tech, Artificial Intelligence, Robotics, Automation, Machine-Learning, Computer-Vision

---

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