Auto Doc ID
Description
The purpose of the tool is to convert inbound images into a standard format that is required for downstream processing for auto document classification and OCR/Data Extraction. After all document processing is completed and we are preparing the final output the images are converted back into a searchable PDF. Auto Doc ID provides suggestions to operators to decrease turn around time and increase quality.
Detailed example
Suggested doc ID. It provides document type suggestions in the ImageSort application to guide operators. D3P does not perform content-based analysis but makes technical image-quality determinations, such as: - Detecting and correcting image orientation (auto-rotation) - Identifying and removing image noise (de-speckling) - Determining and correcting crooked images (de-skewing) - Detecting whether images are in color, grayscale, or black-and-white - Preparing images for annotations by adjusting size and margins without altering the original text - All inbound images are standardized into TIF IV format for consistent downstream processing. It does not interpret meaning, generate content, or make adjudicative decisions.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
- Time savings and higher quality - Improved OCR/Data Extraction Accuracy - clearer, properly aligned images increase recognition success for auto classification of Document ID. - Standardization for Automation - converting all documents into TIF IV ensures reliable document classification and processing. - Reduced Manual Corrections - automated alignment, noise removal, and skew correction minimize human intervention. - Preservation of Original Document Integrity - annotations are applied without altering original text, supporting compliance and readability. • Overall, the impacts are limited to operational efficiency and data accuracy. Correct extraction reduces manual data entry for document classification. The AI has no role in determining eligibility, adjudicating claims, or making benefit decisions"
Controls / human review
ATO: Not reported; PIA: Not published