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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

DeepTagger is an innovative, no-code platform that utilizes artificial intelligence to transform various document types, such as PDFs, images, and Word files, into organized and actionable data using a user-friendly "highlight-and-label" system. Users simply upload their documents, select the relevant data points, and train the model through examples instead of relying on rigid templates, after which they can execute predictions, export their findings, and improve accuracy. The platform is designed to manage intricate structures, such as line items within invoices and tables within other tables, while also accommodating scanned documents and low-resolution images thanks to its powerful optical character recognition (OCR) capabilities. Additionally, DeepTagger includes functionalities for splitting multi-document PDFs, understanding intent and context, and position-aware extraction to differentiate repeated phrases for more precise data retrieval. Its pricing model is based on usage and offers a free tier for processing up to 200 documents, while higher subscription levels provide access to enhanced features, including batch prediction, nested schemas, priority support, a multi-tenant architecture, and compliance suitable for enterprise needs. Overall, DeepTagger stands out as a versatile solution for those looking to streamline their document processing and data extraction workflows.

Description

Let's be honest, creating boilerplate for validation, casting, and business logic in MongoDB can be tedious. This is the reason Mongoose was developed. Imagine we have a fondness for adorable kittens and wish to log every kitten we encounter in MongoDB. The first step is to incorporate Mongoose into our project and establish a connection to the test database hosted on our local MongoDB instance. We have an active connection to the test database located at localhost, and now it’s essential to set up notifications for successful connections or any errors that may arise. In Mongoose, documents correspond directly to the documents stored in MongoDB; each document is essentially an instance of its corresponding Model. Furthermore, subdocuments refer to documents that are nested within others, allowing for intricate data structures. Mongoose provides two main concepts for handling subdocuments: arrays of subdocuments and individual nested subdocuments, making it flexible for various data representations. With Mongoose, managing complex relationships and data structures becomes significantly easier, allowing developers to focus more on their application logic rather than the underlying database mechanics.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Dash
Microsoft Word
MongoDB
ShipFast
StarfishETL

Integrations

Dash
Microsoft Word
MongoDB
ShipFast
StarfishETL

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

DeepTagger

Country

United States

Website

deeptagger.com

Vendor Details

Company Name

Mongoose

Country

United States

Website

mongoosejs.com

Product Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Product Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

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Alternatives

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