Text analytics & NLP · Explosion AI

spaCy

Open-source Python library for industrial-strength natural language processing and production NLP pipelines.

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spaCy is built for putting NLP into production rather than for research prototyping, which shows in its design: fast Cython-based tokenization, pretrained pipelines for 70+ languages covering named entity recognition and dependency parsing, and a component system that serializes cleanly for deployment. It integrates transformer models through the spacy-transformers extension when accuracy matters more than speed, and supports training custom pipeline components on domain-specific text. It's maintained by Explosion AI, a company that also sells Prodigy, a separate paid annotation tool, but spaCy itself is free and open source under the MIT license with no paid tier. It's the common choice when a team needs NLP that runs reliably in a service rather than a notebook.

At a glance

Vendor Explosion AI
Pricing model Open source + paid options
Free tier Yes
Deployment Self-hosted
Open source Yes (MIT)
Best for Teams putting NLP into a production service rather than a research notebook.

Pricing

Free and open source; Explosion AI separately sells the Prodigy annotation tool, but spaCy itself has no paid tier.

Pricing has not been verified yet — see the vendor's site.

Features

  • Pretrained pipelines for 70+ languages
  • Named entity recognition and dependency parsing
  • Transformer model integration via spacy-transformers
  • Custom pipeline component training
  • Fast Cython-based tokenization
  • Production-ready model serialization and packaging

Integrations

Profile last reviewed September 21, 2026

Head to head

Alternatives

NLTK Open-source Python library and teaching toolkit for classic natural-language-processing tasks and research. Gensim Open-source Python library for unsupervised topic modeling and document-similarity analysis using vector-space methods. Hugging Face Transformers Open-source Python library providing pretrained transformer models for text, vision and audio tasks.

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Terms to know

Natural language query Asking a data question in plain language and getting an answer without writing code or a query language. Named Entity Recognition (NER) An NLP technique that locates and classifies names of people, organizations, places, and other entities within text. Text analytics The techniques used to extract structured information and insight from unstructured text, from keyword counts to deep NLP.

Related guides

How to analyze text data From word counts and topic models to LLM classification — matching the method to the question instead of reaching for the newest tool by default. How to choose a text analytics or NLP tool Pick an NLP library or platform by whether your team writes code, what task you're actually doing, and whether you need a pretrained model or a custom one.