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    John Snow Labs - Finance and Legal NLP

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    Deployed on AWS
    Free Trial
    State-of-the-Art Natural Language Processing libraries and Python notebooks tuned for the Finance and Legal domains.
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    Overview

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    John Snow Labs - Finance and Legal NLP Libraries are designed to help organizations extract insights from unstructured documents and enable faster, more accurate data analysis. Finance and Legal NLP is a cutting-edge natural language processing solution designed specifically for the Financial and Legal domains, leveraging advanced machine learning algorithms and a vast domain knowledge base.

    About the offer

    This product includes a package of Natural Language Processing Python libraries specific for the Finance and Legal domains. It allows quick and easy text annotation with pre-trained DL models, rules, and prompts but also NLP model testing, training, and tuning.

    There is no limit on the number of documents, models, or pipelines that can be used with this subscription: the software is licensed on a per-server basis.

    What is included

    • Spark NLP, Spark NLP: Enterprise's premier NLP library offers scalable, trainable versions of the latest research, with 700+ embeddings, 11,000+ pretrained models. It excels in tasks like Entity Recognition, Information Extraction, Text Classification, Translation, and more.
    • Finance NLP software and models, enabling financial text classification, financial sentiment analysis, financial Named Entity Recognition (e.g. organizations, products, revenue, profit, losses, trading symbols, etc.), Entity-linking for normalizing NER entities and linking them to databases such as Edgar, Crunchbase, and Nasdaq, Assertion Status for inferring temporality and Relation Extraction financial De-identification and more.
    • Legal NLP software and models, covering Named Entity Recognition, Information Extraction on clauses, Legal Clause Classification, Legal Relationship Extraction, Entity Linking, Legal De-identification Assertion Status, and Relation Extraction. It includes access to over 300+ new state-of-the-art models available in multiple languages.
    • Visual NLP (OCR) software and models, enabling form understanding, table detection and extraction, noisy image enhancement, visual document classification, visual entity recognition, DICOM to text, signature detection, and image de-identification.
    • Full access to all Finance, Legal and Visual models and pipelines published on the NLP Models Hub (currently 1,000+ and counting).
    • Ready-to-use Jupyter notebooks that will help you get started with text and image analysis on all major NLP tasks such as text classification, sentiment analysis, named entity recognition etc.
    • John Snow Labs python library for text understanding that can be used to test models and pipelines with one line of code.
    • Spark NLP Display library for out-of-the-box annotation display on top of textual content.

    Who is this offer for

    • Teams of python developers that need to extract entities and relations from text, image, and pdf documents;
    • Data scientists who deal with NLP problems;
    • Machine learning engineers who need to test/train/tune NLP models;
    • Scientific researcher groups who need to extract meaning from unstructured, natural language documents;
    • And anyone else interested in text and image analysis, image digitization, data extraction, document labeling and/or NLP model training.

    Target verticals

    The Spark NLP and Visual NLP libraries included in this offer are general and can be applied to any domain to documents written in over 250 languages. The Finance and Legal libraries contained pretrained resources specific for the Finance and Legal domains. The NLP Models Hub contains over 12k pre-trained models and pipelines for general-purpose documents. It also contains 1000+ specialized pre-trained models for the Finance and Legal verticals.

    About the Trial

    John Snow Labs introduces a flexible pay-as-you-go of our most popular NLP libraries subscription ready to process and extract your financial and legal texts in just a few minutes. Start an instance when you are ready to process your data, and stop the instance to not incur any more charges.

    Technical Specifications

    • Recommended memory: 32GB RAM
    • Recommended vCPU:8 vCPUs
    • Operating System:Ubuntu 20.04

    Included integrations

    • Jupyter Lab is preinstalled and running on port 5000. Password: INSTANCE_ID

    3 Easy Steps to get started

    1. Subscribe to the product on the AWS Marketplace.
    2. Deploy it on a new machine.
    3. Access the welcome page for a guided experience on http://INSTANCE_IP.

    Highlights

    • The most widely used NLP library in the enterprise, available as a turnkey package for data scientists including Spark NLP, Finance and Legal NLP, Visual NLP, plus visualization and model testing libraries.
    • Access to 1000+ pre-trained models covering entity recognition, entity linking, relations, assertions, text classification, and de-identification, all tuned for the Financial and Legal verticals.
    • State-of-the-Art visual form and document understanding - enabling entity extraction, table extraction, key-value extraction, document classification, and de-identification.

    Details

    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    Ubuntu 20.04

    Deployed on AWS
    New

    Introducing multi-product solutions

    You can now purchase comprehensive solutions tailored to use cases and industries.

    Multi-product solutions

    Features and programs

    Financing for AWS Marketplace purchases

    AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
    Financing for AWS Marketplace purchases

    Pricing

    Free trial

    Try this product free for 30 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.

    John Snow Labs - Finance and Legal NLP

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (108)

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    • ...
    Dimension
    Cost/hour
    m5.2xlarge
    Recommended
    $47.52
    r5a.2xlarge
    $47.52
    m5d.4xlarge
    $95.04
    r5n.metal
    $570.24
    m5dn.16xlarge
    $380.16
    r5a.4xlarge
    $95.04
    r5n.12xlarge
    $285.12
    m5a.large
    $11.88
    c5.18xlarge
    $427.68
    m5a.8xlarge
    $190.08

    Vendor refund policy

    No Refunds

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    Vendor terms and conditions

    Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

    Content disclaimer

    Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.

    Usage information

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    Delivery details

    64-bit (x86) Amazon Machine Image (AMI)

    Amazon Machine Image (AMI)

    An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

    Version release notes

    Version 6.4.1 of John Snow Labs - Finance and Legal NLP features the following versions of the NLP libraries:

    Implements AWS Compliance requirements

    Additional details

    Usage instructions

    No sensitive information related to you or your organization will be managed or stored by the Finance and Legal NLP library on the instance(s) where you deploy the product. It is the user's responsibility to safely manage sensitive documents processed using the Finance and Legal NLP libraries. The software does not call home - all document processing is done locally and documents are not copied nor shared outside of the running instances.

    Data Encryption: This solution does not encrypt data within the running instance.

    Cryptographic keys: Finance and Legal NLP product does not use credentials and cryptographic keys.

    Usage instructions: On instance startup, navigate to http://<PUBLIC_IP_OF_INSTANCE> for information about the included libraries and links to ready-to-use notebooks for the most popular tasks. Click on one of the library boxes to navigate to your John Snow Labs - NLP Jupyter server and run the notebooks on your data. The password for connecting to Jupyter Lab is the instance id. To run one of the notebooks, just click on it to open it and then click Run.

    Resources

    Vendor resources

    Support

    Vendor support

    support@johnsnowlabs.com 

    AWS Marketplace Slack Channel:

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

    Product comparison

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    Updated weekly

    Accolades

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    Top
    10
    In Image, Text
    Top
    10
    In Software Development, Data Analysis
    Top
    100
    In Databases & Analytics Platforms, Data Integration

    Overview

     Info
    AI generated from product descriptions
    Domain-Specific Pre-trained Models
    Access to 1000+ pre-trained models tuned for Finance and Legal verticals, covering entity recognition, entity linking, relations, assertions, text classification, and de-identification tasks.
    Scalable NLP Library
    Spark NLP library offering 700+ embeddings and 11,000+ pretrained models with support for entity recognition, information extraction, text classification, and translation across multiple languages.
    Visual Document Processing
    Visual NLP (OCR) software enabling form understanding, table detection and extraction, document classification, entity recognition, signature detection, and image de-identification on unstructured documents.
    Finance Domain NLP Capabilities
    Finance NLP models supporting financial text classification, financial sentiment analysis, financial Named Entity Recognition, entity-linking to databases such as Edgar and Crunchbase, and financial relation extraction.
    Legal Domain NLP Capabilities
    Legal NLP models covering Named Entity Recognition, clause information extraction, legal clause classification, legal relationship extraction, entity linking, and legal de-identification across 300+ state-of-the-art models in multiple languages.
    Document Structure Analysis
    Breaks documents into constituent parts and identifies structural elements including headers, tables, and body text
    Vision Transformer Technology
    Utilizes next-generation vision transformer models for extraction from images, PDFs, and tables
    Multi-Format Data Ingestion
    Ingests and preprocesses complex natural language data from any document type and file layout
    Vector Database and LLM Integration
    Compatible with any embedding model, vector database, and LLM framework with API client libraries in multiple languages including Python and Javascript
    Adaptive Preprocessing Strategies
    Provides diverse preprocessing strategies tailored to different document types with enhanced models for table extraction, document hierarchy, and element classification
    Data Ingestion and Integration
    Ingestion of clinical and claims data, ADTs, social determinants of health, pharmacy data from multiple source systems including EHRs and HL7 formats into a unified enterprise data asset
    Data Quality Monitoring
    Automated data quality monitoring that detects anomalies in volume or quality and alerts support teams for proactive issue resolution
    Data Normalization and Deduplication
    Proprietary Master Patient Index (MPI) for member matching, data deduplication, and normalization to a common dataset with Natural Language Processing engine for unstructured data processing
    Predictive Analytics Engine
    Training dictionary-powered predictive analytics and next best-action algorithms for identifying patients most impacted by value-based care programs
    Compliance and Security Certification
    HITRUST CSF certification and HIPAA compliance for healthcare data handling and storage

    Contract

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    Standard contract
    No
    No

    Customer reviews

    Ratings and reviews

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    4
    3 ratings
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    1 AWS reviews
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    2 external reviews
    External reviews are from G2 .
    Noorain Fatima

    AI medical assistant has transformed clinical reports and now speeds up patient data analysis

    Reviewed on Apr 11, 2026
    Review from a verified AWS customer

    What is our primary use case?

    John Snow Labs  is a set of AI software tools and platform mainly for healthcare and life science. I use John Snow Labs  for medical purposes, including a medical chatbot that is used for medical queries and analyzing clinical reports.

    I use the medical chatbot from John Snow Labs to conduct medical queries, ask patients about any concerns they have, and to extract diseases or symptoms. The chatbot will convert text into structured data.

    John Snow Labs can be explored in many ways, including life science, bioinformatics, and genomics. It is also used for drug discovery and research to analyze research papers.

    The chatbot from John Snow Labs will extract diseases; if patients have any kind of diabetes, fever, or symptoms, it can analyze them with the help of that tool, making it very beneficial to use that chatbot.

    John Snow Labs is a set of AI software tools that is very helpful for healthcare and life sciences. In the future, it will assist in bioinformatics and genomics to detect diseases or genes, identify biomarkers, and help in drug development and discovery.

    What is most valuable?

    The best feature of John Snow Labs is the medical chatbot, which allows me to ask for queries, medical queries, and medical terminology. I also use it for clinical reports to generate and convert text into structured data. I can easily generate clinical reports and lab reports.

    Regarding the medical chatbot feature of John Snow Labs, if I input short text, it will convert it into structured data, generating a complete clinical report, which is very beneficial.

    John Snow Labs has positively impacted my organization because there have been many changes since I started using it. The workload is almost very less, and even for the employer, there is less chance to do any work. It is also helpful to get results easily and quickly. Whatever report will be generated takes very less time, and for patients, it is very beneficial to get the report earlier.

    What needs improvement?

    John Snow Labs is working on different algorithms and technical parts, so improvement is required so that the technical aspects will be less, and the algorithms will be easier to understand. It is very difficult for beginners, thus requiring improvement. Moreover, if there is a predominance of Western data, it would be better if it supports Indian data also.

    The user interface of John Snow Labs' software is a bit difficult for beginners to work with. Additionally, more Western data are available compared to India's data, so it would be better to support more Indian data.

    For how long have I used the solution?

    I have been using John Snow Labs for the last six months.

    What do I think about the stability of the solution?

    John Snow Labs is stable because it is designed for large-scale processing and has a good accuracy rate. It is also a faster process.

    What do I think about the scalability of the solution?

    The scalability of John Snow Labs is good because it handles large data and is useful for many users, capable of providing millions of records and data.

    How are customer service and support?

    Customer support for John Snow Labs is very good because via email and phone, I can easily ask questions. If any kind of technical issues arise, I can reach out easily and inquire about product-related questions also.

    How was the initial setup?

    It takes almost 30 minutes to generate any kind of report with John Snow Labs. It helps in queries also to ask if any patients have any kind of doubt or questions in their mind; they can ask quickly also, making it less time-consuming.

    What was our ROI?

    I have seen a return on investment with John Snow Labs because it saves time. The employer is not overwhelmed with work, and they have a lot of time to undertake other tasks. It is indeed a time-saving software that is not time-consuming.

    What's my experience with pricing, setup cost, and licensing?

    The pricing for John Snow Labs is a little bit high, and the licensing procedure is long, so it really requires time to set up.

    What other advice do I have?

    I advise others to use John Snow Labs because it is a time-saving software that allows for easy identification and analysis of medical data, clinical reports, and generation of lab reports, along with assistance for research paper analysis. I rate John Snow Labs at eight out of 10 because some improvements are still required, particularly in the technical work that needs to be focused on.

    Ashpreet S.

    Must try Annotating Tool

    Reviewed on Nov 25, 2023
    Review provided by G2
    What do you like best about the product?
    It is very user friendly and easy to understand in camparison to other competetive products.
    What do you dislike about the product?
    As my use case I did like all the features.
    What problems is the product solving and how is that benefiting you?
    I am using this as an Annotating Tool for image datasets
    Eric L.

    Great annotation tool

    Reviewed on Oct 06, 2022
    Review provided by G2
    What do you like best about the product?
    It makes the annotation process very simple and efficient. Easy to use. Easy to manage the work.
    What do you dislike about the product?
    The review process is a little buggy and non-intuitive. That part of the workflow should be improved.
    What problems is the product solving and how is that benefiting you?
    It solves the problem of establishing ground truth when training or testing a model.
    View all reviews