DEBUG: PAGE=domain, TITLE=View all Vendors,ID=1466,TEMPLATE=vendors
toggle expanded view
VENDORID = 928
VENDOR = AntWorks
VENDORparam = antworks
Title = NelsonHall research on: AntWorks
Description = Browse all NelsonHall's research related to AntWorks on the global BPS market.

Search within reports for: AntWorks

action=something else...array(7) { ["program"]=> int(-1) ["analyst"]=> int(-1) ["industry"]=> int(-1) ["serviceline"]=> int(-1) ["vendor"]=> int(928) ["country"]=> int(-1) ["application"]=> int(-1) } array(1) { ["vendor"]=> string(3) "928" }
from:
until:

Document Cognition SmartLabTest Evaluation

Market Analysis

by Mike Smart

published on Apr 09, 2020

Access to this report is restricted to logged in clients with access. Login to get full access

Report Overview:

NelsonHall's SmartLabTest evaluation of the Document Cognition Platforms consists of 44 pages.

All significant document cognition platform vendors were invited to take part in the NelsonHall SmartLabTest. Of those invited to the project, five platform vendors were in a position to build and submit suitable cognition models for testing against a common set of criteria.

Who is this Report for:

NelsonHall’s Document Cognition SmartLabTest report is a functional “lab” test evaluation of document cognition platforms, 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.

This market analysis complements NelsonHall’s Intelligent Automation Platform evaluation.

Scope of this Report:

Each document cognition platform was lab tested by NelsonHall using a SmartLabTest to evaluate its capability to recognize fields and accurately ingest field across a range of structured, semi-structured, and unstructured documents.

NelsonHall’s SmartLabTest testing comprised four main stages:

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

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

The platforms lab tested are:

  • ABBYY FlexiCapture
  • AntWorks CMR
  • Automation Anywhere
  • LTI Mosaic
  • UiPath.

All relevant platform vendors were invited to take part in the NelsonHall SmartLabTest.

Key Findings & Highlights:

One of the key challenges for enterprises in moving to end-to-end intelligent automation is their ability to ingest and interpret documents. Automation is great but it needs digital inputs to feed it and so the race is on between the leading intelligent automation platforms to develop document cognition functionality.

However, it’s important to recognize that at this stage of the market, it’s not a case of one-size fits all. In fact, it’s absolutely crucial that organizations select the most effective document cognition platform for their processes and document types.

To assist organizations in this, NelsonHall has completed a SmartLabTest evaluation of document cognition platforms. This first-of-a-kind evaluation goes beyond the usual analyst reviews of functionality to test each platform’s ability on real documents in a lab environment.

Within the assessment, NelsonHall tested each platform's ability to ingest and interpret:

  • 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

The result is an invaluable tool for buyers looking to select a document cognition platform capable of ingesting their types of documents with a high degree of accuracy and a low level of exception-handling.

Table of contents:

Table of contents:

  • Introduction
  • Summary of SmartLabTest Results
  • Summary of Platform Strengths
  • Document Cognition Processes
  • Document Cognition Platform Handling of Field Types

Login to get full access:

close