# Amazon SageMaker

**Canonical:** https://apis.io/providers/amazon-sagemaker/  
**Website:** https://aws.amazon.com/  
**APIs profiled:** 9

Amazon SageMaker is a fully managed machine learning platform that enables developers and data scientists to build, train, and deploy machine learning models at scale. SageMaker removes the heavy lifting from each step of the machine learning process, providing built-in algorithms, managed Jupyter notebooks, distributed training, automatic model tuning, and one-click deployment to production endpoints with auto-scaling.

## Kin Score — 64.4 / 100 (strong)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 64.4).

| Facet | Score |
|---|---|
| Discoverability | 75.9 |
| Contract Quality | 69.8 |
| Governance | 25.0 |
| Contract Governance | 25.0 |
| Operational Transparency | 52.6 |
| Developer Ergonomics | 71.4 |
| Commercial Clarity | 76.3 |
| Access Clarity | 76.3 |

## Agent readiness — 26.5 (agent-aware)

| Dimension | Value |
|---|---|
| Spec Presence | yes |
| Agentic Access | derived |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | verified |
| Rate Limit Signal | documented |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Freemium — onboarding: unknown, pricing: freemium, trial: no (confidence: medium).

## APIs (9)

- **Amazon SageMaker Runtime API** — The Amazon SageMaker AI runtime API for invoking deployed model endpoints to get real-time inference predictions.
- **Amazon SageMaker Feature Store Runtime API** — Data plane API operations for the Amazon SageMaker Feature Store supporting put, delete, and retrieve operations for ML features.
- **Amazon SageMaker Metrics Service API** — Data plane API operations for Amazon SageMaker Metrics for putting and retrieving metrics related to training runs.
- **Amazon SageMaker Geospatial API** — APIs for creating and managing Amazon SageMaker geospatial capabilities including earth observation jobs and vector enrichment jobs.
- **Amazon SageMaker Edge Manager API** — SageMaker Edge Manager dataplane service for communicating with active edge agents running ML models on edge devices.
- **Amazon SageMaker Endpoints API** — Operations for managing SageMaker endpoints.
- **Amazon SageMaker Models API** — Operations for managing SageMaker models.
- **Amazon SageMaker Notebook Instances API** — Operations for managing SageMaker notebook instances.
- **Amazon SageMaker Training Jobs API** — Operations for managing SageMaker training jobs.

## Agentic access (1)

- **Amazon Sagemaker Agentic Access** — 13 operations · 13 acting

## Security (3)

- **Amazon Sagemaker Domain Security** — TLSv1.3 · HSTS · DMARC
- **Amazon Sagemaker Vulnerability Disclosure** — security.txt · contact published
- **Amazon Sagemaker Trust Center** — PCI DSS, HIPAA, FedRAMP, GDPR, FIPS 140

## Plans (1)

- **Amazon Sagemaker Plans Pricing**

## Use cases (8)

- **Generative AI Applications** — Build custom generative AI applications using proprietary data with foundation model fine-tuning.
- **ML Model Development** — Train and deploy ML models across the entire machine learning lifecycle from exploration to production.
- **Data Analytics** — Query and analyze data across unified sources with built-in SQL analytics and data processing.
- **Enterprise AI Governance** — Manage data and AI artifacts with fine-grained security controls and compliance tooling.
- **Computer Vision** — Build and deploy computer vision models for image classification, object detection, and segmentation.
- **Natural Language Processing** — Train and deploy NLP models for text classification, entity recognition, and language generation.
- **Fraud Detection** — Build real-time fraud detection models with low-latency inference endpoints.
- **Predictive Maintenance** — Deploy ML models on edge devices for predictive maintenance use cases.

## Tags

Artificial Intelligence, Inference, Machine-Learning, MLOps, Training

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