Lingua
Enterprise-grade language detection for high-accuracy NLP and RAG pipelines.
Enterprise-grade natural language processing to extract insights and relationships from unstructured text.
Amazon Comprehend is a fully managed Natural Language Processing (NLP) service that uses machine learning to uncover valuable insights and connections in unstructured data. By 2026, it has solidified its position as the backbone for automated enterprise compliance and customer intelligence, leveraging advanced deep learning architectures for high-accuracy sentiment analysis, entity recognition, and key phrase extraction. The service operates on a serverless model, abstracting the complexity of training and deploying complex NLP models. For highly specialized domains, Comprehend provides 'Custom Classification' and 'Custom Entity Recognition,' allowing organizations to train models on proprietary datasets with zero machine learning expertise required. It integrates natively with the AWS ecosystem, enabling real-time stream processing via Amazon Kinesis and batch processing of petabyte-scale data stored in S3. Its 2026 evolution includes enhanced PII (Personally Identifiable Information) detection capabilities that support global data privacy regulations (GDPR, CCPA) across more than 30 languages, and a specialized 'Comprehend Medical' branch that maps clinical text to standardized ontologies like ICD-10-CM and RxNorm, making it indispensable for healthcare and legal-tech sectors.
Identifies sentiment specifically associated with individual entities within a sentence, rather than just an overall document score.
Enterprise-grade language detection for high-accuracy NLP and RAG pipelines.
Massively multilingual sentence embeddings for zero-shot cross-lingual transfer across 200+ languages.
Universal cross-lingual sentence embeddings for massive-scale semantic similarity.
The open-source multi-modal data labeling platform for high-performance AI training and RLHF.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Automated identification and masking of sensitive data like SSNs, credit card numbers, and addresses.
Enables users to build custom NLP models using their own labels without writing code, utilizing transfer learning.
Natively processes multi-page PDF, Word, and Image files (via OCR integration) to extract text and structure.
An automated workflow to update custom models with new data periodically to ensure accuracy over time.
A HIPAA-eligible sub-service trained on medical datasets to extract medication, dosages, and conditions.
Automatically identifies the primary language of a document across 100+ languages.
Support teams are overwhelmed by thousands of daily emails requiring manual sorting.
Registry Updated:2/7/2026
Data scientists need access to raw customer logs but must comply with privacy laws.
Companies lack a quantifiable way to measure brand sentiment across millions of social mentions.