This document discusses intelligent document processing solutions and how they can help organizations overcome challenges with unstructured and diverse documents. It introduces a predictive artificial intelligence approach that can handle unprecedented document variation with high accuracy. Examples are given of how one insurance company was able to automate document processing, reduce costs by $3 million, and improve turnaround times from 48 hours to 8 hours by implementing this solution. The key advantage highlighted is its ability to learn from data and continuously improve over time.

1. The FUTURE of
Intelligent Document
Processing
©2021 Infrrd Inc. All rights reserved.

2. Uniform
Diverse
Structured Unstructured
2
The PROBLEM with real-life documents is that many are
unstructured and diverse, and OCR cannot process them…
Where do your
documents fit?
Low
Variation,
Highly
Structured
High
Variation,
without
Structure
ALL of your
Documents
Individual
Document

3. Uniform
Diverse
Structured Unstructured
3
Holding you back from getting the OUTCOMES you need
STUCK!
OCR +
Manual
Corrections
Faster Processing
Higher Accuracy
More
Automation
Transformative
Customer Experience
ALL of your
Documents
Individual
Document

4. What if a SOLUTION could help with all your
document processing needs
4
Individual Document
Function: Classify + Clean + Extract + Understand
Uniform
Diverse
Structured Unstructured
ALL
Enterprise
Documents
Business
Value
Created
OCR
Coded
Templates
OCR +
Learned
Templates
Prediction-based
IDP
Function: Extract
Function: Extract + Preprocess

5. What Makes Us DIFFERENT
Our AI-first approach is based on predicting the values of
extraction rather than simply ‘extracting’ them from a
specified location. With prediction we can handle
unprecedented variation with exceptional accuracy.
5
Coded Templates
Document
Template
OCR
Learned Templates
Document
Template
OCR
OCR Corrections
Machine
Learning
Prediction Platform
Document
NLP Tagging*
Computer
Vision*
Language
Model
Statistical
Model
Visual Model
Prediction
Extraction Results
Conformal & Controller
Model*
Prediction
Predictive Model
Historical Data
* Patent Pending IP

6. Prediction drives BOLD OUTCOMES
6
Documents Classification Data Extraction QA
LEARNING
Data Ingestion Decision Action
Prediction impacts the entire process—
not just extraction.
• Processing speed; eliminate manual bottlenecks
• Automated classification
• Straight-through processing
• Learning loop improves performance
How can this impact your Business Process?

7. Documents Systems
We go DEEP into IDP
IDP
Pipeline
Pre-
processing
Extraction Post
Processing
1 2 3 4
Analytics
IDP
Technology
Platform

8. Problem: HIGH VARIATION
Requires Human Cognition
8
X X X = 21,000
Document
Variations
CARRIERS COLLATERAL TYPES DOCUMENT TYPES
DATA
ELEMENTS
Template-based technology
cannot tackle unstructured &
non-standard documents

9. 9
CUSTOMER SUCCESS
Large insurance
company
$3M
SAVED
CLIENT
• Specialty provider of collateral protection insurance (2,100 providers)
CHALLENGE
• Employee training times and high staff turnover lead to high costs.
• Need to reduce cost while improving SLAs (from 48 hrs. to 8 hrs.) and
scalability
HOW WE HELPED
• We trained our ML models on hundreds of representative samples.
• Our system can process 2,100 providers x 10 variations =
21,000 possible variations
• Automatic classification, extraction, and validation, all in one platform.
on automation
investment of $0.5M
6X
ROI
Investment
recovered in
60DAYS
50%
REDUCTION
in overall
processing
time
OUTCOMES

10. Customers That TRUST Us
10

11. Customers choose us because competition
struggles with VARIATION
11
CLIENTS COMPETITORS
✓ Templates unmanageable
✓ Templates unmanageable
✓
Don’t have an end-to-end
solution
✓ Doesn’t do unstructured docs
✓ Can’t get it to work
✓ Templates unmanageable
Hidden
Large Partner

12. 12
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INTELLIGENT
WORK