Amazon Lookout for Equipment website screenshot

Amazon Lookout for Equipment

Amazon Lookout for Equipment uses machine learning to analyze sensor data from your industrial equipment and detect abnormal patterns that signal potential failures. It helps you avoid unplanned equipment downtime by identifying potential equipment failures before they occur.

Amazon Lookout for Equipment publishes 1 API on the APIs.io network: Datasets API. Tagged areas include Equipment Monitoring, Industrial IoT, Machine-Learning, and Predictive Maintenance.

The Amazon Lookout for Equipment catalog on APIs.io includes 1 JSON-LD context and 2 Spectral governance rulesets.

Amazon Lookout for Equipment’s developer surface includes authentication, developer portal, documentation, support, engineering blog, developer console, signup flow, and 14 more developer resources.

49.9/100 developing ▬ flat Agent 29/100 agent aware Full breakdown ↓
scored 2026-08-21 · rubric v0.12.0
AccessFreemiumSelf serve⚡ Free to try
1 APIs 5 Features 4 Use Cases
Equipment MonitoringIndustrial IoTMachine-LearningPredictive Maintenance

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-08-21 · rubric v0.12.0
Composite quality — 49.9/100 · developing
Contract Quality 17.3 / 25
Developer Ergonomics 9.5 / 20
Access Clarity 10.3 / 20
Operational Transparency 3.4 / 13
Contract Governance 3.5 / 12
Discoverability 5.9 / 10
Agent readiness — 29/100 · agent aware
Machine-Readable Contract 18 / 18
Agentic Access Contract 10 / 10
Documented Reversibility 0 / 6
MCP Server 0 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 7 / 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/amazon-lookout-for-equipment: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

APIs 1

Individual APIs this provider publishes, each with its own machine-readable definition.

Amazon Lookout for Equipment Datasets API

Equipment sensor dataset management

Postman Collections 1

Ready-to-run Postman collections for exercising this provider's APIs.

Open Collections 3

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

API Collection

OPEN COLLECTION

Pricing Plans 1

Published pricing tiers and plan structures.

Rate Limits 1

Documented rate limits and quota policies.

FinOps 1

Cost, billing, and metering signals for API financial operations.

Features 5

Notable capabilities this provider offers.

Anomaly Detection

Detect abnormal equipment behavior using ML models trained on equipment sensor data.

Predictive Maintenance

Predict equipment failures before they occur to reduce unplanned downtime.

No ML Expertise Required

Automatically build ML models from historical sensor data without data science expertise.

Multi-Sensor Support

Analyze data from hundreds of sensors simultaneously to detect complex failure patterns.

Real-Time Inference

Run continuous inference on streaming sensor data for real-time failure detection.

Semantic Vocabularies 1

JSON-LD contexts and semantic vocabularies used across these APIs.

Amazon Lookout For Equipment Context

2 classes · 7 properties

JSON-LD

Spectral Rules 2

Spectral governance rulesets for linting and validating these APIs.

Amazon Lookout for Equipment API Rules

5 rules · 4 warnings 1 info

SPECTRAL

Amazon Lookout for Equipment API Rules

24 rules · 9 errors 15 warnings

SPECTRAL

JSON Schema 2

Standalone JSON Schema definitions for this provider's data models.

Dataset

5 properties

JSON SCHEMA

Model

7 properties

JSON SCHEMA

JSON Structure 2

JSON Structure definitions describing this provider's data shapes.

Examples 2

Example request and response payloads for these APIs.

Security Posture 4

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

Amazon Lookout For Equipment Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Amazon Lookout For Equipment Vulnerability Disclosure

security.txt · contact published

SECURITY

Amazon Lookout For Equipment Trust Center

PCI DSS, HIPAA, FedRAMP, GDPR, FIPS 140

SECURITY

Agentic Access 1

Recommended x-agentic-access execution contracts for AI agents.

Amazon Lookout For Equipment Agentic Access

8 operations · 4 acting

8 operations · 4 acting

AGENTIC

Use Cases 4

What developers build with this provider.

Manufacturing Predictive Maintenance

Detect early warning signs of equipment failures in manufacturing machinery.

Energy Sector Monitoring

Monitor industrial equipment in power plants, wind turbines, and oil refineries.

Mining Equipment Health

Track the health of heavy mining equipment to prevent costly breakdowns.

HVAC System Monitoring

Detect anomalies in HVAC systems to prevent equipment failures in buildings.

Resources

Get Started 5

Portal, sign-up, and the first successful call

Documentation 1

Reference material describing how the API behaves

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 2

Pagination, idempotency, versioning, errors, and events

Build 2

SDKs, sample code, and the tooling you integrate with

Access & Security 4

Authentication, authorization, and security posture

Operate 3

Status, limits, changes, and where to get help

Commercial 2

Pricing, plans, and the legal terms of use

Company 1

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: amazon-lookout-for-equipment
name: Amazon Lookout for Equipment
description: Amazon Lookout for Equipment uses machine learning to analyze sensor data from your industrial equipment and
  detect abnormal patterns that signal potential failures. It helps you avoid unplanned equipment downtime by identifying
  potential equipment failures before they occur.
type: Index
accessModel:
  pricing: freemium
  onboarding: self-serve
  trial: false
  try_now: true
  public: false
  label: Freemium · Self-serve signup
  confidence: high
  source:
  - plans
  - authentication
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/amazon-lookout-for-equipment.png
tags:
- AWS
- Equipment Monitoring
- Industrial IoT
- Machine-Learning
- Predictive Maintenance
tags_raw:
- AWS
- Equipment Monitoring
- Industrial IoT
- Machine Learning
- Predictive Maintenance
url: https://raw.githubusercontent.com/api-evangelist/amazon-lookout-for-equipment/refs/heads/main/apis.yml
created: '2026-03-16'
modified: '2026-05-19'
specificationVersion: '0.23'
apis:
- aid: amazon-lookout-for-equipment:amazon-lookout-for-equipment-datasets-api
  name: Amazon Lookout for Equipment Datasets API
  description: Equipment sensor dataset management
  humanURL: https://aws.amazon.com/lookout-for-equipment/
  baseURL: https://lookoutequipment.amazonaws.com
  tags:
  - Datasets
  properties:
  - type: OpenAPI
    url: openapi/amazon-lookout-for-equipment-datasets-api-openapi.yml
  - type: Documentation
    url: https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/API_Reference.html
  - type: GettingStarted
    url: https://aws.amazon.com/lookout-for-equipment/getting-started/
  - type: Pricing
    url: https://aws.amazon.com/lookout-for-equipment/pricing/
  - type: FAQ
    url: https://aws.amazon.com/lookout-for-equipment/faqs/
  - type: JSONSchema
    url: json-schema/amazon-lookout-for-equipment-dataset-schema.json
  - type: JSONSchema
    url: json-schema/amazon-lookout-for-equipment-model-schema.json
  - type: JSONLD
    url: json-ld/amazon-lookout-for-equipment-context.jsonld
common:
- type: PostmanWorkspace
  url: https://www.postman.com/kinlaneapi/amazon-lookout-for-equipment/overview
- type: AgenticAccess
  url: agentic-access/amazon-lookout-for-equipment-agentic-access.yml
- type: TrustCenter
  url: security/amazon-lookout-for-equipment-trust-center.yml
- type: VulnerabilityDisclosure
  url: security/amazon-lookout-for-equipment-vulnerability-disclosure.yml
- type: DomainSecurity
  url: security/amazon-lookout-for-equipment-domain-security.yml
- type: Authentication
  url: authentication/amazon-lookout-for-equipment-authentication.yml
- type: Portal
  url: https://aws.amazon.com/lookout-for-equipment/
- type: Portal
  url: https://aws.amazon.com/lookout-for-equipment/
- type: Documentation
  url: https://docs.aws.amazon.com/lookout-for-equipment/
- type: TermsOfService
  url: https://aws.amazon.com/service-terms/
- type: PrivacyPolicy
  url: https://aws.amazon.com/privacy/
- type: Support
  url: https://aws.amazon.com/premiumsupport/
- type: Blog
  url: https://aws.amazon.com/blogs/machine-learning/tag/amazon-lookout-for-equipment/
- type: GitHubOrganization
  url: https://github.com/aws
- type: Console
  url: https://console.aws.amazon.com/lookoutequipment/
- type: Signup
  url: https://portal.aws.amazon.com/billing/signup
- type: Login
  url: https://signin.aws.amazon.com/
- type: StatusPage
  url: https://health.aws.amazon.com/health/status
- type: Contact
  url: https://aws.amazon.com/contact-us/
- type: Features
  data:
  - name: Anomaly Detection
    description: Detect abnormal equipment behavior using ML models trained on equipment sensor data.
  - name: Predictive Maintenance
    description: Predict equipment failures before they occur to reduce unplanned downtime.
  - name: No ML Expertise Required
    description: Automatically build ML models from historical sensor data without data science expertise.
  - name: Multi-Sensor Support
    description: Analyze data from hundreds of sensors simultaneously to detect complex failure patterns.
  - name: Real-Time Inference
    description: Run continuous inference on streaming sensor data for real-time failure detection.
- type: UseCases
  data:
  - name: Manufacturing Predictive Maintenance
    description: Detect early warning signs of equipment failures in manufacturing machinery.
  - name: Energy Sector Monitoring
    description: Monitor industrial equipment in power plants, wind turbines, and oil refineries.
  - name: Mining Equipment Health
    description: Track the health of heavy mining equipment to prevent costly breakdowns.
  - name: HVAC System Monitoring
    description: Detect anomalies in HVAC systems to prevent equipment failures in buildings.
- type: Integrations
  data:
  - name: Amazon S3
    description: Store and access equipment sensor data in S3 for model training and inference.
  - name: AWS IoT SiteWise
    description: Collect and organize equipment sensor data with IoT SiteWise and analyze with Lookout.
  - name: Amazon Kinesis Data Streams
    description: Stream real-time sensor data from equipment to Lookout for Equipment.
  - name: AWS IoT Core
    description: Connect industrial equipment to AWS via IoT Core for data ingestion.
- type: SpectralRules
  url: rules/amazon-lookout-for-equipment-spectral-rules.yml
- type: Vocabulary
  url: vocabulary/amazon-lookout-for-equipment-vocabulary.yaml
- type: Integrations
  url: https://aws.amazon.com/marketplace
integrations:
- name: Sign in
- name: Agent Mode
- name: Why AWS Marketplace?
- name: Get started in AWS Marketplace
- name: Industry
- name: Resources
- name: Become a Channel Partner
- name: Sell in AWS Marketplace
- name: Manage Your Account
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

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