DeepTagger

What is DeepTagger?

DeepTagger is an advanced text processing solution designed to enhance the extraction of data from various document types, including PDFs, images, and text files. It utilizes augmented text processing techniques, employing position markers to ensure precise data extraction, even in cases where specific terms may appear multiple times within a document. This capability allows users to obtain exactly what they need without the common pitfalls associated with traditional data extraction methods.

Key features of DeepTagger include:

Intelligence Built In:

The K-Score validation system provides confidence ratings for each field, ensuring reliable results.

True Nested Structures:

Capable of extracting complex data, such as job duties from employment histories, which many competitors struggle to handle.

Learning That Improves:

Each validation serves as training data, continuously enhancing extraction accuracy over time.

Transparent Per-Token Pricing:

Users pay only for the tokens processed during extraction, with no hidden fees or per-seat charges.

DeepTagger Features

DeepTagger offers advanced augmented text processing that utilizes position markers to accurately extract information from documents, ensuring precision even when the same name appears multiple times. This capability allows users to retrieve complex data structures, such as lists of job duties for each employment history, which many traditional solutions struggle to handle.

Key features and functionalities of DeepTagger include:

K-Score validation system providing confidence ratings for each field, ensuring reliable results.

Continuous learning from validation data to enhance extraction accuracy over time.

Transparent per-token pricing model with no hidden fees, allowing users to pay only for the tokens processed during extraction.

Real-time tracking of usage and costs through an intuitive dashboard.

Why DeepTagger?

DeepTagger offers a range of benefits that make it a superior choice for organizations dealing with document-heavy workflows. Its augmented text processing utilizes position markers to ensure precise data extraction, even in complex documents where the same information may appear multiple times. This level of precision is crucial for maintaining data integrity and reliability.

Additionally, DeepTagger's K-Score validation system provides confidence ratings for each extracted field, allowing users to trust the accuracy of their data. The platform's ability to handle true nested structures means it can extract complex data, such as job duties from employment histories, which many competitors struggle with. With continuous learning from validation data, DeepTagger improves its extraction accuracy over time, ensuring that users benefit from an increasingly efficient system.

Transparent per-token pricing with no hidden fees

Consumption-based model that allows users to pay only for tokens processed

Real-time tracking of usage and costs through an intuitive dashboard

Volume discounts automatically applied as usage increases

How to Use DeepTagger

To get started with DeepTagger, you can process up to 200 documents for free, with no credit card required. The process is simple and consists of three main steps: uploading your documents, annotating the data you need, and training the AI with just a few examples.

Here’s a quick guide on how to use DeepTagger:

Upload

your documents (PDF, images, or text).

Annotate

by selecting the data you need.

Train

our AI with just a few examples.

Extract

data from new documents automatically.

Validate

and improve the extraction process continuously.

Ready to see what DeepTagger can do for you?[@portabletext/react] Unknown block type "span", specify a component for it in the `components.types` propand experience the benefits firsthand.