CMR+

Multi-format ingestion

Really Intelligent Document Processing

Multi-format ingestion

CMR+ can process a wide range of data types within a single platform. We support diverse datatypes, filetypes, languages, and industries, making CMR+ highly versatile and capable of handling various use cases.

When it comes to datatypes, CMR+ supports a comprehensive set of data inputs. This includes traditional text-based inputs, such as checkboxes and barcodes, which can be seamlessly processed and extracted by CMR+. By accommodating these diverse datatypes, we ensure that you can capture and utilize data from a variety of sources, enhancing the flexibility and applicability of CMR+.

In terms of filetypes, CMR+ boasts extensive compatibility. Whether you’re dealing with common file formats such as PDF, Microsoft Office documents (Word, Excel, PowerPoint), or image files (JPEG, PNG), CMR+ can efficiently process and extract data from these files. Additionally, CMR+ supports more specialized file formats, including scanned documents (in image or PDF format), allowing for comprehensive coverage across various document types.

Language diversity is another area where CMR+ excels. We support a wide range of languages that use the Latin script, including but not limited to English, Spanish, French, German, etc and are building Japanese capabilities. This multilingual capability enables you to process documents in different languages without the need for separate solutions or language-specific configurations. CMR+ utilizes advanced natural language processing techniques to ensure accurate extraction and understanding of textual data across diverse languages.

Moreover, CMR+ is designed to cater to multiple industries and use cases. Whether you’re in finance, healthcare, legal, insurance, or any other industry, CMR+ is flexible and adaptable to meet your specific needs. The platform can handle industry-specific document formats, extract relevant data fields, and integrate with industry-specific systems or workflows. This versatility allows us to serve a wide range of use cases, from invoice processing and contract management to banking risk analysis and policy management automation.

See It For Yourself

Don’t take our word for it. Nothing beats a demo tailored to your business needs.

Request a Demo

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
Arrow top
Arrow top
Arrow top

Machine Learning

Reports & Analytics

Workflow Management

Queue, exeption
& approval management

Arr

Data Transport & Mobilisation

RPA, APIs & Micro-services

Arr

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.

Read More

Ready to start your automation journey?

You’re in the right place. We’re here to help you and we would love to hear from you.

    Youtube Linkedin-in

    AntWorks 2023 © All Rights Reserved

    Privacy Policy | Terms of Use

    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.