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AntWorks CMR - Document Cognition SmartLabTest

Vendor Analysis

by Mike Smart

published on Apr 09, 2020

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Report Overview:

NelsonHall’s AntWorks CMR report is a functional “lab” test evaluation of the AntWorks CMR document cognition platform.

Who is this Report for:

NelsonHall’s AntWorks CMR report is a functional “lab” test evaluation of the AntWorks CMR document cognition platform, designed for:

  • Sourcing managers monitoring the capabilities of existing suppliers of Document Cognition platforms and identifying vendor suitability for document cognition RFPs
  • RPA and intelligent automation center of excellence personnel evaluating document cognition platform capability
  • Vendor marketing, sales, and business managers looking to benchmark their platforms against their peers
  • Financial analysts and investors covering intelligent automation and Document Cognition platforms.

Scope of this Report:

The report provides a comprehensive and objective analysis of AntWorks CMR’s capabilities, including:·      Designing the document cognition models

  • Designing the document cognition models
  • Document Ingestion
  • Document verification
  • Testing.

This report provides the quantitative results of the SmartLabTest comparing the platform’s performance for each document type. This report includes:

  • The SmartLabTest results
  • Analysis of the platform’s strengths & weaknesses
  • Identification of the key features of each platform
  • An evaluation of comparative platform maturity

Key Findings & Highlights:

This NelsonHall vendor assessment tested AntWorks CMR’s capabilities in ingesting and interpreting:

  • Structured documents such as mortgage applications and ACORD filings
  • Semi-structured documents such as invoices and purchase orders
  • Highly unstructured documents such as resumes.

The KPIs assessed for each document type included:

  • Proportion of fields correctly recognized
  • Accuracy of extraction of recognized fields
  • Proportion of fields overall that 100% accurate and require no manual intervention.

AntWorks' CMR encompasses multi-format data ingestion, fractal network-driven learning for natural language understanding using combinations of supervised learning, deep learning, and adaptive learning, and accelerators. Current industry accelerator modules include financial document API, mortgage API, invoicing, and trade finance, amongst others.

CMR aims to be a business user friendly way of introducing document cognition with its Content-based Object Retrieval (CBOR) to "lift and associate all the content" to capture the documents' data and perform training in production for continuous improvement using ML integrated into the recognition engine.

AntWorks has stressed the differentiation of its fractal analysis-based CMR compared to that of traditional OCR leveraging neural network-based ML, highlighting fractal analysis' higher quality pattern recognition (leading to higher accuracy of captured content, in particular with handwritten forms); being zone and template independent (and therefore more able to adjust to changes in document templates); the ability to utilize JIT pattern recognition methods, rather than sequential and linear character matching; and the lack of requirement for a predefined font library.

Table of contents:

Table of contents:

  • Introduction
  • SmartLabTest Methodology
  • SmartLabTest Results & Competitor Benchmarks
  • 3.1 CMR Results
  • 3.2 CMR Benchmarked vs. Competitor Platforms
  • Key Capability Assessments
  • 4.1 Assessment of Document Cognition Model Building Capability
  • 4.2 Assessment of Quality Assurance Capability
  • 4.3 Assessment of Data Extraction Capability
  • Strengths and Challenges
  • 5.1 Strengths
  • 5.2 Challenges
  • NelsonHall Buyer Recommendation
  • CMR Platform Features
  • 7.1 User Functionality
  • 7.2 Point Solutions Leveraging CMR
  • CMR Strategy
  • CMR Outlook
  • Appendix: About AntWorks

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