# Aeva

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

Aeva Technologies is a Mountain View, California sensing and perception company that builds 4D LiDAR based on proprietary Frequency Modulated Continuous Wave (FMCW) technology, measuring instant velocity in addition to 3D position for every point in a scene. Its product line spans Atlas and Atlas Ultra long-range automotive-grade sensors, the Omni wide-view short-range sensor, and Eve 1 precision laser speed sensors for factory automation, serving autonomous vehicles, robotics, industrial automation, security, and physical-AI markets. Aeva is a hardware and perception-software provider rather than a web-API company: its developer surface is open-source software on the aevainc GitHub org (the AevaScenes Python SDK and Doppler ICP), the AevaScenes dataset, and product SDK/EULA-gated software delivered with its sensors. No public REST or web API is published.

## Kin Score — 14.3 / 100 (emerging)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 14.3).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 2.6 |
| Developer Ergonomics | 23.8 |
| Commercial Clarity | 21.1 |
| Access Clarity | 21.1 |

## 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)

- **Aeva Domain Security** — TLSv1.2

## Tags

Company, LiDAR, 4D LiDAR, FMCW, Autonomous Vehicles, Robotics, Perception, Sensors, Industrial Automation, Physical AI

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