AI analysis of digital service record books for evaluation of rewards, medals, etc.

AI analysis of digital service record books for evaluation of rewards, medals, etc.

Objective

To develop an interactive, metadata-driven document processing system that streamlines the management of police service records. This system enables power users to define document templates specifying key fields and validation rules, while automating document classification and text extraction using OCR and vision AI. By providing an intuitive review interface that displays the original scanned document alongside a dynamic, editable form, the system facilitates rapid and accurate digitization of various records such as promotions, awards, charge memos, transfers, and complaints. The goal is to convert unstructured paper documents into clean, auditable digital records that can be easily stored, searched, and shared, enhancing operational efficiency and compliance.

Scope

The solution supports end-to-end digitization workflows starting with user uploads of scanned documents, which are automatically classified into predefined document types or manually corrected as needed. Text extraction is performed using configurable OCR engines optimized for English documents, and the extracted data is mapped into structured fields based on active templates managed by power users. The system features a two-pane review UI allowing officers or clerks to validate and correct extracted information with real-time feedback and validation rules. Finalized records are serialized into standardized JSON format and securely stored in a MongoDB database, enabling quick retrieval and audit trails. Initial implementation covers key document categories—Promotions, Awards, Charge Memos, Transfers, and Complaints—with flexibility to add more templates and improve OCR performance over time. System administration includes monitoring OCR accuracy, template versioning, and classification effectiveness to ensure continuous enhancement.