Plumerai

Plumerai builds AI software for intelligent cameras that pairs tiny on-device edge AI models with cloud Vision Language Models (VLMs). Its Video Intelligence products cover detection of people, vehicles, animals and packages, Familiar Face Identification, cross-camera Re-Identification, noise-robust motion detection, VLM-based video search, and custom AI notifications. The Plumerai Inference Engine is a deep-learning model compiler and runtime optimized for CPU inference on Arm Cortex-M / Cortex-A, RISC-V and x86_64. Plumerai integrates via SDKs (C++, C, Python, Rust, Java) rather than a hosted REST API, with the same unified API running from microcontrollers to servers. Plumerai also maintains the open-source Larq ecosystem for training and running Binarized Neural Networks.

Plumerai is profiled on the APIs.io network. Tagged areas include Company, Ai Ml, Edge AI, Computer-Vision, and Embedded.

Plumerai’s developer surface includes documentation, API reference, getting-started guide, engineering blog, support, and 6 more developer resources.

🌐 Visit website 📡 Source on GitHub

10.8/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-08-21 · rubric v0.12.0

0 APIs

Company Ai Ml Edge AI Computer-Vision Embedded Machine-Learning Inference Camera

Kin Score

Kin Score How this is scored →
scored 2026-08-21 · rubric v0.12.0

Composite quality — 10.8/100 · minimal

Contract Quality 0.0 / 25

Developer Ergonomics 4.8 / 20

Access Clarity 0.0 / 20

Operational Transparency 0.3 / 13

Contract Governance 0.0 / 12

Discoverability 5.7 / 10

Agent readiness — 0/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/plumerai: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

Get Started 1

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

SDKs

SDKs

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 1

Status, limits, changes, and where to get help

Support

Support

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: plumerai
name: Plumerai
description: Plumerai builds AI software for intelligent cameras that pairs tiny on-device edge AI models with cloud Vision
  Language Models (VLMs). Its Video Intelligence products cover detection of people, vehicles, animals and packages, Familiar
  Face Identification, cross-camera Re-Identification, noise-robust motion detection, VLM-based video search, and custom AI
  notifications. The Plumerai Inference Engine is a deep-learning model compiler and runtime optimized for CPU inference on
  Arm Cortex-M / Cortex-A, RISC-V and x86_64. Plumerai integrates via SDKs (C++, C, Python, Rust, Java) rather than a hosted
  REST API, with the same unified API running from microcontrollers to servers. Plumerai also maintains the open-source Larq
  ecosystem for training and running Binarized Neural Networks.
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://plumerai.com/assets/images/logo_wordmark.png
url: https://raw.githubusercontent.com/api-evangelist/plumerai/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- partech
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-20'
tags:
- Company
- Ai Ml
- Edge AI
- Computer-Vision
- Embedded
- Machine-Learning
- Inference
- Camera
tags_raw:
- Company
- Ai/Ml
- Edge AI
- Computer Vision
- Embedded
- Machine Learning
- Inference
- Cameras
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://plumerai.com/
- type: Documentation
  url: https://docs.plumerai.com
- type: APIReference
  url: https://docs.plumerai.com/video_intelligence/cpp/
- type: GettingStarted
  url: https://docs.plumerai.com/video_intelligence/integration_checklist/
- type: Blog
  url: https://blog.plumerai.com
- type: Support
  url: https://www.plumerai.com/contact_us
- type: GitHubOrganization
  url: https://github.com/larq
- type: Packages
  url: packages/plumerai-packages.yml
- type: SDKs
  url: packages/plumerai-packages.yml
- type: LLMsTxt
  url: llms/plumerai-llms.txt
- type: DomainSecurity
  url: security/plumerai-domain-security.yml
x-enrichment:
  date: '2026-07-20'
  status: enriched
  artifacts_added: 3
  pass: local-v1

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