# Derq

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

Derq is an MIT spinoff (founded 2016, with operations in Dubai and Detroit) building AI-powered intelligent transportation systems that help cities, departments of transportation, and infrastructure operators prevent crashes and improve traffic flow. Its hardware-agnostic platform ingests data from video cameras, radar, LiDAR, signal controllers, and connected/V2X infrastructure, then runs real-time edge computer vision and machine learning to detect, track, and predict the movement of vehicles, pedestrians, and cyclists. Derq surfaces safety and traffic intelligence — crashes, near misses, violations, conflicts, counts, and ATSPMs — through its dashboard and via APIs to third-party systems. Flagship products include Derq SENSE (real-time traffic detection and V2X perception) and Derq INSIGHT (road safety and traffic management analytics).

## Kin Score — 8.5 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 8.5).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 7.1 |
| Commercial Clarity | 10.5 |
| Access Clarity | 10.5 |

## 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)

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

## Tags

Company, Intelligent Transportation, Road Safety, Traffic Analytics, Computer-Vision, V2X, Smart Cities, Machine-Learning

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