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

9.1/100 minimal ▬ flat Agent 0/100 human only Front door AI 6/6 dominant library Full breakdown ↓
scored 2026-09-25 · rubric v0.23.0

0 APIs

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

Kin Score

Kin Score How this is scored →
scored 2026-09-25 · rubric v0.23.0

Composite quality — 9.1/100 · minimal

Contract Quality 0.0 / 21

Developer Ergonomics 4.0 / 17

Access Clarity 0.0 / 17

Operational Transparency 0.3 / 11

Contract Governance 0.0 / 10

Discoverability 4.7 / 9

Regulatory Posture 0.8 / 15

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

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. 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. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Plumerai Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

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.
deliveryModel:
  model: library
  open_source: false
  commercial: false
  callable_host: false
  label: Library · distributed through package registries, no callable service
  confidence: low
  source:
  - none
  generated: '2026-08-28'
  method: derived
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
- Computer-Vision
- Machine-Learning
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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