CMR+

Extension in the form of SDK framework

Really Intelligent Document Processing

Extension in the form of SDK framework

CMR+ offers a comprehensive SDK (Software Development Kit) framework tailored to empower power programmers with extensive capabilities for document automation.

Our SDK framework provides a powerful set of tools, libraries, and APIs (Application Programming Interfaces) that enable power programmers to integrate our document processing functionality seamlessly into their existing software solutions or develop custom applications from scratch. This level of flexibility allows programmers to leverage CMR+’s advanced features while maintaining control over the development process.

With the SDK, power programmers can access and utilize the core functionalities of CMR+ programmatically. This includes the ability to extract data from documents, classify documents based on predefined criteria, perform advanced document analysis, and generate structured outputs.

Our SDK offers robust documentation, code samples, and developer-friendly resources to facilitate quick and efficient integration. The well-documented APIs and libraries provide a clear understanding of the available methods and parameters, ensuring a smooth development experience for power programmers.

Additionally, the SDK framework is designed to be highly customizable and extensible. Power programmers can tailor the document processing workflows to their specific requirements and business logic, making it ideal for building complex document automation solutions. The SDK supports integration with .NET, allowing programmers to work with the preferred development environment.

Moreover, our SDK framework is regularly updated and maintained, ensuring compatibility with the latest technological advancements and industry standards. This provides power programmers with access to cutting-edge features, improvements, and security updates, ensuring the longevity and reliability of their applications.

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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

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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.