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features
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support

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Description

Utilize UBIAI's advanced labeling platform to accelerate the training and deployment of your personalized NLP model like never before! When handling semi-structured documents such as invoices or contracts, it is essential to maintain the original layout for optimal model training. By integrating natural language processing with computer vision, UBIAI’s OCR functionality empowers you to execute named entity recognition (NER), relation extraction, and classification tasks directly on native PDF files, scanned images, or smartphone pictures, all while preserving critical layout details, which leads to a remarkable enhancement in your NLP model's performance. With the UBIAI text annotation tool, you can carry out NER, relation extraction, and document classification seamlessly within the same user-friendly interface. Unlike many other platforms, UBIAI offers the capability to create nested and overlapping entities that encompass multiple relationships, thereby enriching your data annotation process. This unique feature not only simplifies your workflow but also enhances the depth of insights your model can achieve.

Description

dOCR is an innovative API and dashboard designed for extracting data from documents. Users can upload various formats such as PDFs, images, scans, or Word files, and in return, dOCR provides structured JSON containing the necessary fields instead of unrefined OCR text. With support for over 15 predefined document types—including invoices, receipts, bank statements, pay stubs, W-2s, 1099s, driver’s licenses, passports, and utility bills—it also accommodates custom document types. Developers can seamlessly integrate the service via a REST API, which offers features like webhooks, IP allowlisting, and options for processing modes that prioritize either quality or speed; meanwhile, non-developers can utilize the web dashboard for ad-hoc data extraction. The system is powered by advanced vision LLMs such as Claude Opus and Gemini, eliminating the need for users to create or manage complex parsing pipelines. Additionally, dOCR provides a free tier that allows for the extraction of up to 50 pages each month. This makes it an accessible option for both technical and non-technical users alike.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

No images available

Integrations

Innovatiana Yes 

Integrations

Innovatiana No 

Pricing Details

$299 per month
Free Trial No 
Free Version Yes 

Pricing Details

$49/month
Free for 50 pages/month; paid
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

UBIAI

Founded

2020

Country

United States

Website

ubiai.tools/

Vendor Details

Company Name

dOCR, Inc.

Website

docr.dev

Product Features

Data Labeling

Human-in-the-loop No 
Labeling Automation No 
Labeling Quality No 
Performance Tracking No 
Polygon, Rectangle, Line, Point No 
SDK No 
Supports Audio Files No 
Task Management No 
Team Collaboration No 
Training Data Management No 

OCR

Batch Processing No 
Convert to PDF No 
ID Scanning No 
Image Pre-processing No 
Indexing No 
Metadata Extraction No 
Multi-Language No 
Multiple Output Formats No 
Text Editor No 
Zone Selection Tool No 

Product Features

OCR

Batch Processing No 
Convert to PDF No 
ID Scanning No 
Image Pre-processing No 
Indexing No 
Metadata Extraction No 
Multi-Language No 
Multiple Output Formats No 
Text Editor No 
Zone Selection Tool No 

Alternatives

Alternatives

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