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What is Hyland IDP?
Hyland Intelligent Document Processing leverages artificial intelligence to enhance document capture, classification, and data extraction, significantly boosting efficiency, precision, and processing speed. By utilizing AI, Hyland IDP continuously learns and adapts, leading to a substantial decrease in both time and costs associated with document management, while also minimizing exceptions and operational bottlenecks. This innovative approach not only streamlines workflows but also ensures a higher level of reliability in document handling.
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.
Integrations Supported
Box
Microsoft Outlook
Microsoft SharePoint
OnBase
Accela
Adobe Acrobat Sign
Deltek Acumen
Ellucian
Google Drive
Integrations Supported
Box
Microsoft Outlook
Microsoft SharePoint
OnBase
Amazon Web Services (AWS)
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided
Pricing Information
Subscription pricing based on volume.
Free Trial Offered?
Supported Platforms
SaaS
Supported Platforms
SaaS
Windows
On-Prem
Customer Service / Support
Standard Support
Web-Based 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
Hyland
Date Founded
1991
Company Location
United States
Company Website
www.hyland.com/en/solutions/products/intelligent-document-processing
Company Facts
Organization Name
BIS
Date Founded
1986
Company Location
United States
Company Website
grooper.com
Categories and Features
Intelligent Document Processing
Not specified
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
Intelligent Document Processing
Not specified
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
