Vision & Language Services
Rekognition, Comprehend, Textract, Translate, Kendra
AWS provides pre-built vision and language AI services that require no ML expertise. You call an API with your image or text and receive structured insights. These are ideal for adding AI capabilities to existing applications without building models from scratch.
Key Points
- Amazon Rekognition: detect objects, scenes, faces, text, celebrities, inappropriate content in images/video
- Rekognition Video: real-time video analysis for streaming, or batch on S3 stored video
- Rekognition Custom Labels: train a custom image classifier with your own labelled images (few hundred images enough)
- Amazon Textract: go beyond OCR — extract text AND structure (tables, forms, key-value pairs) from PDFs/images
- Textract Queries: ask questions about a document in natural language ("What is the invoice total?")
- Amazon Comprehend: NLP — detect sentiment, entities, key phrases, language, PII, and custom classifiers
- Comprehend Medical: clinical NLP — extract diagnoses, medications, dosages, conditions from medical text
- Amazon Kendra: intelligent enterprise search — connect SharePoint, S3, Salesforce; NLP ranking over 40+ connectors
- Amazon Translate: neural machine translation; Custom Terminology for brand-specific terms
- Amazon Macie: uses ML to automatically discover, classify, and protect sensitive PII data in S3
| Service | Input | Output | Exam Tip |
|---|---|---|---|
| Rekognition | Image / Video | Labels, faces, text, moderation flags | Use for content moderation, identity verification |
| Textract | PDF / Image | Structured text, tables, forms, key-value pairs | "Structured" extraction = Textract, not Rekognition |
| Comprehend | Text (any) | Sentiment, entities, key phrases, PII | Comprehend = NLP on text; not for images |
| Kendra | Enterprise docs | Relevant passages with NLP ranking | Intelligent search, not raw full-text search |
| Translate | Text in language A | Text in language B | Custom Terminology preserves brand names |
Real-World Example
The NHS uses Amazon Textract to digitise millions of paper patient records, extracting structured medical data that feeds into analytics. This replaced a manual data-entry process that took weeks and introduced transcription errors.