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What is Parascript?

Parascript software streamlines the processing of mortgage and loan documents, enhancing both speed and precision while also automating tasks related to insurance documents, facilitating the intake and analysis of healthcare insurance information. This automation of document processing significantly boosts efficiency, improves data accuracy, and lowers operational costs. Driven by advanced data science and machine learning, Parascript adapts and optimizes itself for a variety of document-centric tasks, including classification, separation, and data entry for financial transactions. Furthermore, this innovative software handles an impressive volume, processing over 100 billion documents annually across sectors such as banking, government, and insurance. Its capabilities not only transform workflows but also redefine how organizations manage large-scale document operations.

What is Grooper?

Most document AI asks you to trust it. You feed it documents, it returns answers, and when a number is wrong, "the model said so" is the only explanation available. Grooper was built for organizations that can't accept that. Grooper is an intelligent document processing (IDP) platform built on one premise: you stay in control. You control the method: about 57 extraction techniques across rule-based and AI families, chosen per field, so an invoice number can use a pattern that returns the same answer every time while the messy handwriting beside it uses AI. You control the AI's input: ReadScope lets you set the scope of what the AI reads, per field. The model can't misread what it was never shown. And you control the evidence: every value keeps its receipt. Click any number to see the exact spot on the page it came from, the method that produced it, what the AI was shown, and who checked it. A number without its source is a rumor; Grooper's numbers show their work. One system covers the whole job: scanning, OCR across 6 engines, document separation, classification, extraction, validation against your systems of record, human review with the source highlighted, redaction, and delivery. Extend it yourself through 61 documented extension points, and drive it with your own AI agents through MCP, the open protocol, instead of a captive vendor copilot. Deploy it your way: on your hardware, with AI models on GPUs you own so regulated content never leaves the building; in your own cloud tenant; or hosted and managed by BIS. Customers publish the results: 62% of invoices in a 2,000-a-day AP operation flow through with zero human touches, and Del Norte Credit Union eliminated 97.5% of manual data entry. Behind Grooper is BIS, an Oklahoma City company founded in 1986: self-funded, no outside investors, and sole author of every line of the code. Your documents. Your models. Your rules.

Media

Media

Integrations Supported

ARGO

Integrations Supported

Amazon Web Services (AWS)
Azure AI Document Intelligence
Box
CMIS
IBM FileNet Content Manager
Laserfiche
Microsoft 365
Microsoft Azure
Microsoft Excel
Microsoft OneDrive
Microsoft Outlook
Microsoft Power BI
Microsoft SharePoint
Microsoft Word
Nuxeo
OnBase
OpenText ECM

API Availability

Has API

API Availability

Has API

Pricing Information

Available Upon Request

Pricing Information

Subscription pricing based on volume.
Free Trial Offered?

Supported Platforms

SaaS
Windows

Supported Platforms

SaaS
Windows
On-Prem

Customer Service / Support

Standard Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Parascript

Date Founded

1996

Company Location

United States

Company Website

www.parascript.com

Company Facts

Organization Name

BIS

Date Founded

1986

Company Location

United States

Company Website

grooper.com

Categories and Features

AI Insurance

Not specified

Claims Processing

Forms Management

Data Entry

Abbreviation Detection
Data Capture and Transfer
Data Cleansing
Data Entry Verification

Data Extraction

Document Extraction
Image Extraction

Robotic Process Automation (RPA)

Attended Automation
Image Recognition
Optical Character Recognition
Unattended Automation

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Process/Workflow Automation
Rules-Based Automation

Data Extraction

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

Electronic Data Capture

Data Entry
Document Imaging

Machine Learning

ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Statistical / Mathematical Tools
Templates
Visualization

Natural Language Processing

In-Database Text Analytics
Named Entity Recognition
Parsing
Sentence Segmentation
Stemming/Lemmatization
Tokenization

OCR

Batch Processing
Convert to PDF
ID Scanning
Image Pre-processing
Indexing
Metadata Extraction
Multi-Language
Multiple Output Formats
Text Editor
Zone Selection Tool

Text Mining

Document Filtering
Language Detection
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis

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