AWS Amazon Rekognition

Name: Amazon Rekognition API
Brand: Amazon Rekognition
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAI/MLVisionhmac65 EndpointsREST

Install Jentic One Beta

Connect the Amazon Rekognition to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Amazon Rekognition, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Amazon Rekognition API.

Detect labels, scenes, and objects in an image with bounding boxes and confidence via DetectLabels

Compare two faces and return a similarity score using CompareFaces for identity verification

Search a face collection for matches against a probe image with SearchFacesByImage

GET STARTED

Start building with Amazon Rekognition API

Explore with Jentic

View OpenAPI Document

For Agents

Detect labels, faces, text, celebrities, and unsafe content in images and video, and search face collections through Amazon Rekognition.

Use for: I need to detect objects and scenes in an uploaded image, Compare a selfie against a reference photo for identity verification, Search a face collection for the closest match to a probe image, Extract text from a scanned receipt image

Not supported: Does not generate or edit images, run text-only NLP, or transcribe audio - use for image and video analysis (labels, faces, text, moderation, celebrities, PPE) only.

Jentic publishes the only available OpenAPI specification for Amazon Rekognition, keeping it validated and agent-ready. Rekognition is a managed computer-vision service for image and video understanding: face detection, comparison, and search; object, scene, and label detection; text-in-image (OCR); content moderation; celebrity recognition; PPE detection; and stream-based video analysis. The API surfaces 65 operations across synchronous image analysis, asynchronous video jobs, face-collection management, custom Rekognition Custom Labels project lifecycle, and live-stream processors. It is the canonical AWS API for adding vision intelligence to applications.

Use Cases

Patterns agents use Amazon Rekognition API for, with concrete tasks.

★ Identity Verification with Face Match

Verify that a selfie matches a stored ID photo by calling CompareFaces with both image bytes (or S3 object references) and reading the returned Similarity score. Pair with CreateFaceLivenessSession and GetFaceLivenessSessionResults to defend against spoofing using printed photos or replay video. Used in onboarding flows for fintech, ride-share, and marketplaces.

Call CompareFaces with SourceImage of the selfie bytes and TargetImage of the stored ID photo, then return the FaceMatch with the highest Similarity

Image Content Moderation

Filter user-generated content by calling DetectModerationLabels on each upload. Rekognition returns a hierarchy of moderation labels (e.g., 'Suggestive' > 'Female Swimwear or Underwear') with confidence scores so policy engines can block, age-gate, or human-review accordingly. Combine with DetectLabels and DetectText for richer signals.

Call DetectModerationLabels with Image.S3Object pointing to the uploaded image and MinConfidence 80, then route based on returned ModerationLabels

Video Label Detection at Scale

Tag long-form video assets with timestamped labels by starting an async job. StartLabelDetection takes an S3 video object and an SNS topic; when the job completes, GetLabelDetection returns labels with timestamps for every detected object or scene. Useful for media archives, ad insertion, and content discovery.

Call StartLabelDetection with Video.S3Object pointing to the source video and NotificationChannel.SNSTopicArn, then call GetLabelDetection with the returned JobId once the SNS message arrives

AI Agent Vision Tool via Jentic

A multimodal agent uses Jentic to discover Rekognition operations such as DetectLabels and DetectText, load their schemas, and call them when a tool route requires image understanding. Jentic stores AWS credentials in its vault and signs each call with SigV4, so the agent only handles the image bytes (or S3 reference) and the structured response.

Use Jentic to search 'detect labels in an image with rekognition', load DetectLabels, and execute it with the user's image bytes

Key Endpoints

65 endpoints — jentic publishes the only available openapi specification for amazon rekognition, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/#X-Amz-Target=RekognitionService.DetectLabels

Detect labels, scenes, and objects in an image

POST

/#X-Amz-Target=RekognitionService.CompareFaces

Compare two faces and return a similarity score

POST

/#X-Amz-Target=RekognitionService.DetectText

Run OCR and extract words and lines from an image

POST

/#X-Amz-Target=RekognitionService.DetectModerationLabels

Identify unsafe or moderated content categories in an image

POST

/#X-Amz-Target=RekognitionService.IndexFaces

Add faces from an image to a face collection

POST

/#X-Amz-Target=RekognitionService.SearchFacesByImage

Search a face collection for matches to a probe image

POST

/#X-Amz-Target=RekognitionService.StartLabelDetection

Start an asynchronous video label-detection job

POST

/#X-Amz-Target=RekognitionService.GetLabelDetection

Retrieve completed video label-detection results by JobId

POST

/#X-Amz-Target=RekognitionService.DetectLabels

Detect labels, scenes, and objects in an image

POST

/#X-Amz-Target=RekognitionService.CompareFaces

Compare two faces and return a similarity score

POST

/#X-Amz-Target=RekognitionService.DetectText

Run OCR and extract words and lines from an image

POST

/#X-Amz-Target=RekognitionService.DetectModerationLabels

Identify unsafe or moderated content categories in an image

POST

/#X-Amz-Target=RekognitionService.IndexFaces

Add faces from an image to a face collection

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Your AWS access keys are stored once, encrypted, by your own Jentic One instance and used to produce a SigV4 signature per request. The raw secret access key never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'detect labels in an image', and Jentic returns DetectLabels with its input schema for Image, MinConfidence, and Features so the agent calls the right endpoint without browsing the reference docs.

Time to first call

FAQs

Specific to using Amazon Rekognition API through Jentic.

Why is there no official OpenAPI spec for Amazon Rekognition?

AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Amazon Rekognition via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.

What authentication does the Rekognition API use?

Rekognition uses AWS SigV4 HMAC request signing with an AWS access key ID and secret. Through Jentic, AWS credentials are stored in the vault and SigV4 signatures are produced per request, so the agent never sees raw secrets.

Can I run Rekognition on video as well as images?

Yes. Synchronous image operations (DetectLabels, DetectFaces, DetectText, etc.) accept Image bytes or an S3 object. Video operations are asynchronous: call StartLabelDetection, StartFaceSearch, StartContentModeration, or StartCelebrityRecognition with a Video.S3Object and NotificationChannel, then call the matching Get* operation with the returned JobId.

What image formats and sizes are supported?

Rekognition accepts JPEG and PNG. Synchronous calls cap image bytes at 5 MB when passed inline and 15 MB when referenced via S3. Minimum face size for detection is roughly 40x40 pixels. Videos must be H.264 in MP4 or MOV containers and live in S3.

What are the rate limits for Rekognition?

Rekognition enforces per-region transactions-per-second limits per operation; defaults vary (DetectLabels often starts around 50 TPS) and quota increases can be requested. Throttled calls return ProvisionedThroughputExceededException - back off and retry.

How do I detect labels in an image through Jentic?

Search Jentic for 'detect labels in an image with rekognition', load DetectLabels, and execute it with Image bytes (or Image.S3Object) and MinConfidence. Install with pip install jentic; AWS credentials are pulled from your Jentic One instance.

Can I limit what my agent is allowed to do with the Amazon Rekognition API?

Yes. Because you run Jentic One yourself, your own rules decide which Rekognition operations and which AWS credentials the agent may use. You can grant read-only analysis calls such as DetectLabels, DetectText, and DetectModerationLabels while withholding operations that mutate a face collection, like IndexFaces or deleting a collection. The image, video, and collection targets travel in the request body rather than the URL path, so the operator scopes access at the operation level and the agent can only call what you allow.

AWS Amazon Rekognition

Connect the Amazon Rekognition to your agent

Capabilities

Start building with Amazon Rekognition API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs