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UBIAI
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Data labeling (3)

UBIAI

Labeling data for natural language processing and machine learning projects.

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Starting price Free + from $74/mo

Tool Information

The UBIAI Text Annotation Tool is designed to make natural language processing and machine learning more accessible and affordable for everyone.

UBIAI offers a handy AI Builder, which is an engine that empowers users to create smart document applications. With this tool, you can easily annotate documents, whether they are in PDF, image, or text format. Its robust features cover everything from document classification and auto-labeling to named entity recognition (NER) and OCR annotation, making it a versatile choice for various projects.

One of UBIAI's standout features is its OCR annotation capability, which allows users to extract data from scanned documents and images. This is especially helpful because it cuts down on costs and hurdles when it comes to accessing valuable data locked in these formats. Plus, the auto-labeling function, powered by large language models, simplifies the data labeling process, saving you both time and effort when preparing your datasets.

Collaboration is another key aspect of UBIAI. The tool is tailored for teams, enabling easy assignment of tasks, tracking progress, and measuring performance. This makes it not just user-friendly but also efficient for collaborative projects. Additionally, UBIAI supports annotation in various languages and formats, including handwritten, scanned, and digital documents, ensuring that you can work seamlessly across diverse content types.

Whether you're in banking, finance, healthcare, insurance, legal, or technology, UBIAI is built to meet your specific needs. Its features can help streamline processes related to data annotation and training, addressing everything from semantic analysis to fraud detection, and even speeding up diagnosis and treatment times in healthcare settings.

In summary, the UBIAI Text Annotation Tool is an exceptional resource, particularly known for its OCR capabilities, collaborative features, and support for advanced deep learning model training. This makes it a fantastic option for anyone involved in NLP and ML projects across a broad spectrum of industries.

Pros and Cons

Pros

  • Supports training of Spacy
  • Applicable in financial
  • and text documents
  • Progress tracking feature
  • OCR annotation feature
  • Helps streamline data annotation
  • and PDF formats in multiple languages
  • Supports annotation across industries
  • Enables fine-tuning on annotated data
  • Efficient workflow efficiency
  • Can annotate native and scanned PDFs
  • Supports import of pre-annotated data
  • Supports regex annotation
  • Data analyst technologies compatible
  • Multi-lingual annotation feature
  • and digital documents
  • Suitable for banking
  • Supports semantic search for legal industries
  • Supports annotation in multiple languages
  • Supports secure data retention with daily snapshots
  • and technology industries
  • Assists in semantic analysis and fraud detection needs
  • BERT
  • Document classification feature
  • finance
  • Document classification support
  • Supports user feedback and needs
  • Offers a discount for students/researchers
  • Training support for chatbots and virtual assistants
  • Performance measurement feature
  • Can visualize healthcare machine learning
  • Supports over 20 languages
  • images
  • Supports handwritten
  • healthcare
  • Supports training hi-tech NLP models
  • Named entity recognition (NER)
  • Auto-labeling feature
  • and technology industries
  • healthcare
  • Designed to handle complex data
  • Helps accelerate ML model training
  • legal
  • and GPT models
  • scanned
  • OCR coordinates for each word available
  • Supports text
  • Easy assignment of tasks
  • Offers pay as you go options
  • image
  • Connects with APIs for predictions
  • Supports data labeling with large language models
  • legal
  • Intuitive UI
  • Can handle PDFs
  • insurance
  • Enables training chatbots and virtual assistants
  • Can extract data from scanned documents and images
  • Can handle various document types
  • State-of-art deep learning models training
  • Supports process scanned documents
  • Enables training of deep learning models
  • Significant discounts for researchers and students
  • Offers model fitting or auto-annotation
  • Supports team collaboration
  • Supports various export formats
  • Allows labeling and training simultaneously
  • Data scientists tools support

Cons

  • No teamwork for personal plan
  • Vague feature instructions
  • Details on on-premise package lacking
  • No visible API support
  • Table extraction only available in PRO
  • Limited uploading of OCR documents
  • Uncertain multilingual support
  • Costly for average teams
  • Limited uploads for non-OCR documents

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