CMR+

Really Intelligent Document Processing

Gen AI Powered • Low Code • IDP Platform
Use Cases
Business Benefits
Process Flow
Success Stories
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What do our customers achieve from CMR+

Explore our Case Studies

Business Benefits

Enhanced Productivity and Efficiency

CMR+ streamlines workflows, eliminates manual data entry, and frees up employees to focus on higher-value tasks.

Scalability and Growth

CMR+ can handle increasing document volumes and adapt to evolving business needs, supporting organizational growth.

Compliance and Security​

CMR+ ensures data privacy, adheres to regulatory requirements, and provides audit trails for document processing activities.

Time and Cost Savings

CMR+ automates manual document processing tasks, reducing human error and saving valuable time and resources.

Improved Confidence in Accuracy

CMR+'s advanced algorithms and machine learning capabilities enhance data extraction accuracy, minimizing the risk of errors and improving overall data quality.

The CMR Process Flow

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Success Stories

Our customers have spoken on
Gartner® Peer Insights™

AntWorks CMR+ Intelligent Document Process with Gartner

Intelligent Document Processing

Gartner Score
“ Using CMR+ creates value-added work for skilled workers. A lot of the manual back and forth, such as emailing Excel files and PDFs, is now gone… leaving more time for employees to tackle jobs that demand more skill. ”

Rick Koo

Digital Technology Leader, Mercer

Mentioned in the 2022 Gartner®
Market Guide for Intelligent
Document Processing Solutions*

Challenger in Document Oriented
Text Analytics Platforms Wave
2020 & 2022

Major Contender in Everest
Group® IDP PEAK Matrix 2023

Leader for the Second Year in a
Row in ISG’s IDP Provider Lens™

Tech Partners

Integrations and Connectors

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The CMR Process

Input Sources & Document Types

  • Auto Ingestion
  • Image
  • Jpeg, TIFF, PDF
  • MS Word
  • RPA
  • DMS

Document Optimisation & Indexing

  • Noise Reduction
  • Orientation/Skew Correction
  • Background suppression
  • Classification & Indexing

Data
Extraction

  • Structured
  • Un-structured
  • Natural Language
  • Handwritten

Data
Enrichment

  • Business Rules
  • Look ups
  • API

Human in the Loop

  • Verification
  • Training
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Machine Learning

Reports & Analytics

Workflow Management

Queue, exeption
& approval management

Arr

Data Transport & Mobilisation

RPA, APIs & Micro-services

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Client Systems

Training as a part of the workflow

CMR+ integrates training as a part of the workflow, allowing the ML models to learn and improve as it processes more and more documents. By incorporating feedback, corrections, and iterative learning, the models continually refine their algorithms and enhance their accuracy. This capability ensures that CMR+ provides increasingly accurate and efficient document processing results over time, aligning closely with your organization’s specific needs and evolving document patterns.

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    Training as a part of the workflow

    CMR+ integrates training as a part of the workflow, allowing the ML models to learn and improve as it processes more and more documents. By incorporating feedback, corrections, and iterative learning, the models continually refine their algorithms and enhance their accuracy. This capability ensures that CMR+ provides increasingly accurate and efficient document processing results over time, aligning closely with your organization’s specific needs and evolving document patterns.
    CMR+ offers the capability to incorporate training as part of the workflow, allowing the machine learning (ML) models to continuously learn and improve as they process more and more documents.

    The training component of CMR+ enables you to provide feedback and corrections to the ML models based on the results of document processing. This feedback loop helps the models identify and correct any errors or inaccuracies in the extracted data, classifications, or predictions. By incorporating training into the workflow, the ML models can learn from these corrections and adjust their algorithms accordingly, leading to improved accuracy and performance over time.

    The process of training the ML models within CMR+ is typically straightforward and user-friendly. When discrepancies or errors are identified and flagged during document processing, citizen developers can provide the correct information or annotations. The platform then leverages this feedback to refine the underlying ML models, updating their knowledge and enhancing their ability to accurately process similar documents in the future.

    Additionally, CMR+ employs advanced techniques such as active learning, which optimizes the training process by intelligently selecting specific documents for human review. By focusing training efforts on the most challenging or uncertain cases, the ML models can learn more effectively and efficiently, saving time and resources while improving performance.
    Furthermore, the training component can be integrated into an iterative workflow, where the ML models are continuously retrained as new labeled data becomes available. This ongoing learning approach ensures that the models stay up-to-date with evolving document patterns, industry-specific terminology, or changes in document formats. As a result, the performance and accuracy of the models steadily improve with each iteration.

    The training-as-part-of-workflow capability in CMR+ offers several advantages. It enables the ML models to adapt and learn from real-world scenarios, allowing for continuous improvement and refinement. This iterative learning process ultimately enhances the accuracy, reliability, and efficiency of the document processing workflows, ensuring that the models align closely with the specific requirements and nuances of your organization.