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Install John Snow Labs’ Software

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One all-inclusive annual subscription

The software is licensed as an annual subscription, which includes:
Software updates

Always stay at the state of the art with new model architectures, models, and capabilities. We’re been releasing software every 2 weeks for the past 6 years.

Model updates

Never go to production with a stale model, or worry about how you prevent drift or retrain on your own. We own, support, and update all the models we license.

Premium Support

Direct access to our data science team. Speak with a practicing data scientist when you’d like to share code or talk through a design issue or model tuning question.

Frequently Asked Questions


Each license includes the software libraries in all supported languages, the pre-trained models that are included with it, premium support, and all updates to the software & models that are released during the subscription period.

Two licensing options are available for the Healthcare NLP, Visual NLP, Finance NLP and Legal NLP libraries:

  • on a pay as you go or
  • monthly/annual subscriptions, payable either once a year in full or each month in advance.

No. There is no limitation imposed on the number of characters, words or documents processed with the free or paid libraries. However, one license only gives you the right to run one Spark job at a given moment.

The software will stop processing documents – for both training and inference. If you choose to buy a license, we will provide you with a new license key. Otherwise, you must uninstall the software. In any case, data you have already processed is yours to keep.

Running the Software

Python, Java, and Scala.

We officially support AWS, Azure, Databricks, Cloudera, Colab, Kaggle and GCP.

Yes. John Snow Labs NLP is used heavily in high-compliance industries like healthcare, life science, finance, and insurance where on-premise deployments are common. Most single-machine, and Kubernetes distributions are supported.

Yes. Make sure to allocate enough memory & compute power for your use case.

Yes. Make sure to allocate enough memory & compute power for your use case.

This depends heavily on your use case. For training custom models based on the BERT family of embeddings, at least 8 cores and 64GB of memory are recommended. For inference, as little as 1 core and 8GB may be enough. Using GPU’s will usually provide faster execution at a higher cost.


The cost depends on which edition(s) you need (Healthcare, Visual, Finance or/and Legal), the level of support (8x5 or 24x7), and the number of licenses you need. Please email us with those details at and we’ll reply with an exact quote.

Online bank transfers (ACH or wire), checks, and all major credit cards as well as AWS or/and Azure credits.

Yes! Please email us to describe your situation and needs.


No. You install and run the software on your infrastructure. The software does not “call home” and no data or results are sent to John Snow Labs.

You do. We will never even see them.

This is not a SaaS solution – instead, you run the software on your infrastructure. Nothing ever gets sent to John Snow Labs or another third party. John Snow Labs NLP is designed for high-compliance, locked-down environments.

No, after an initial installation & downloading of pre-trained models.

Yes, an internet connection is necessary to establish the validity of your license key when starting your Spark session. For airgap deployments contact our sales team at to accommodate your specific needs.



Yes. John Snow Labs NLP is designed to enable you to train & tune your own models for most tasks.

The full list is available here. Expect the list to keep growing over time.


Email , call us at +1-302-786-5227, or start a chat on Paying customers get a private Slack channel, so that you can ask your questions privately.

Same business day 8x5 support is included with all subscriptions. We can also provide 24x7 support for production systems – please email us if you require it.

Yes. The Demos and Notebooks Hub includes links to runnable Google Colab notebooks in Python.