About the offer

NLP Lab (Annotation Lab) is a Free End-to-End No-Code platform for document labeling and AI/ML model training. It enables domain experts - nurses, doctors, lawyers, accountants, investors, etc. – to extract meaningful facts from text documents, images or PDFs and train models that will automatically predict those facts on new documents. This is done by using state-of-the-art Spark NLP pre-trained models or by tuning models to better handle specific use cases.

Based on an auto-scaling architecture powered by Kubernetes, it can scale to many teams and projects. Enterprise-grade security is provided for free including support for air-gap environments, zero data sharing, role-based access, full audit trails, MFA, and identity provider integrations. It allows powerful experiments for model training and finetuning, model testing, and model deployment as API endpoints.

There is no limitation on the number of users, projects, tasks, models, or training that can be run with this subscription.

Healthcare and Visual features are available via BYOL.

Included Features:

• Annotation support for Text, Image, Audio, Video and HTML content;
• High productivity annotation UI with keyboard shortcuts and pre-annotations;
• Support for text annotation in 250+ languages;
• Out-of-the-box support for the following NLP tasks: Classification, Named Entity Recognition, Assertion Status, and Relation Extraction;
• Support for projects and teams – 30+ project templates; unlimited projects and users, project import, export and cloning, project grouping;
• Task assignment, tagging, and comments; duplicate tasks identification; task searching and filtering;
• Consensus analysis and Inter Annotator Agreement charts;
• Performance dashboards;
• Enterprise-level security and privacy: role-based access control, role-based views, annotation versioning, full audit trail, Single Sign on;
• AI-Assisted Annotation: never start from scratch but reuse existing models to pre-annotate tasks with the latest Spark NLP models for classification, NER, assertion status, and relation detection;
• Full Models Hub integration – you can explore available models and embeddings, download them with the click of a button and reuse those in your project configuration.
• Train Classification, NER, and Assertion Status models – use default parameters or easily tune them on the UI for different experiments;
• Active Learning automatically trains new versions of your models once new annotations are available;
• API access to all features for easy integration into custom data analysis pipelines;

Features available with BYOL – Healthcare NLP

• Access to 550+ Healthcare pre-trained models;
• Model tuning - Build your models on existing pre-trained models
• Programmatic labeling via dictionary and regex-based rules;

Features available with BYOL – Visual NLP

• Pre-annotate PDF and image tasks with Visual NER models;
• Tune Visual NER models for your data;
• Annotate directly on the PDF/image;
• Automatic text recognition;

Who is this offer for

• Domain experts who want to test DL models on their data and tune/train new models via an easy-to-use UI, without writing a line of code;
• Data labeling teams who want to optimize the efficiency and speed of their day-to-day work with preannotations;
• 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 NLP Lab is a domain-agnostic tool that can be used to annotate documents in any vertical. Its integration with the NLP Models Hub facilitates access to over 12k pre-trained models for general-purpose text documents and taxonomies.

3 Easy Steps to get started

1. Subscribe to the product on the Azure Marketplace.
2. Deploy it on a new machine.
3. Access the login page for a guided experience at "http://INSTANCE_IP".
   For the first login use "admin" and your SUBSCRIPTION_ID as credentials to login.