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Powerful NLP API for entity recognition, sentiment analysis, syntax parsing, and content classification across many languages.
Azure Cognitive Services offering sentiment analysis, key phrase extraction, entity recognition, and language detection with strong enterprise integration.
Fully managed AWS service for entity extraction, sentiment, topic modeling, and language detection, with custom entity support.
AI‑driven service that extracts entities, keywords, sentiment, emotion, and categories; supports custom models and extensive language coverage.
#6 MeaningCloud
Cloud‑based text analytics platform offering sentiment, topic extraction, language detection, and deep categorization for over 30 languages.
Enterprise‑grade text analytics suite for sentiment, intent, entity extraction, and theme detection, with on‑premise and SaaS options.
Comprehensive analytics tool for text mining, clustering, sentiment, and entity extraction, integrated with SAS analytics ecosystem.
#9 SpaCy
Open‑source industrial‑strength NLP library with fast tokenization, named entity recognition, part‑of‑speech tagging, and dependency parsing.
Python library offering tokenization, stemming, tagging, parsing, and basic sentiment analysis for research and prototyping.
#11 MonkeyLearn
No‑code AI platform for text classification, sentiment analysis, and entity extraction; includes pre‑built models and API.
API suite delivering sentiment, entity, classification, summarization, and language detection with multilingual support.
#13 TextRazor
High‑performance NLP API for entity extraction, taxonomy classification, sentiment, and relation extraction across many languages.
Modular on‑premise version of Rosette offering entity extraction, name matching, and language identification with customizable pipelines.
Customer experience platform with advanced sentiment, intent, and entity extraction, plus visual analytics dashboards.
Domain‑specific entity and sentiment extraction engine, optimized for finance, healthcare, and media content.
Mixed‑methods software combining qualitative data analysis with quantitative text mining, sentiment, and topic modeling.
Visual data science platform with built‑in operators for tokenization, NER, sentiment, and topic modeling.
Open‑source analytics platform offering nodes for language detection, sentiment, entity extraction, and clustering.
Library of pre‑trained language models (BERT, RoBERTa, GPT, etc.) that can be fine‑tuned for sentiment, NER, and classification tasks.
Add‑in for Microsoft Excel that brings sentiment, entity, and theme extraction directly into spreadsheets.