Document and Evidence Automation1. Automates classification of all incoming documents for Guardia Civil to expedite digital evidence workflows.
2. Enables automated tagging by case type, date, officer ID, and urgency, ensuring consistent document processing for law enforcement operations.
3. Reduces manual errors in document sorting, automating access to relevant evidence and reports within government police databases.
4. Supports compliance, traceability, and rapid retrieval, optimizing automated document and evidence handling in law enforcement.
### 2. Trigger Conditions
1. Document upload to central repository, shared mailbox, or evidence management portal triggers automation.
2. Automated detection of new files in monitored folders (cloud/local) initiates categorization.
3. Receipt of scanned evidence via email/PDF upload triggers automatable tagging.
4. Scheduled or on-demand batch processing automates backlog categorization.
### 3. Platform Variants
#### 3.1. Microsoft Power Automate
- Feature/Setting: "AI Builder—Document Processing" for automating extraction and tagging; configure with model trained on police forms.
- Feature/Setting: "Document Text Detection" automates text extraction and lends metadata for automated tagging; set up with government service account.
- Feature/Setting: "Smart Document Understanding"; automate pipelines to classify incoming evidence docs by legal type.
- Feature/Setting: “New File in Folder” automates trigger and routes file to “Formatter” and “Filter” steps for automated tagging.
- Feature/Setting: "Document Understanding" module; automates classification using pre-trained models on evidence templates.
- Feature/Setting: "AnalyzeDocument" API automates text and key-value extraction for evidence form tagging.
- Feature/Setting: Parser rule builder automates zone-based metadata extraction and auto-tags document batches.
- Feature/Setting: Automated Document Classification engine; configure with law enforcement taxonomies for automated case categorization.
- Feature/Setting: "Drive trigger" script automates labeling and tagging of incoming shared police document folders.
- Feature/Setting: “Watch Files,” “Text Parser,” automates detection and document categorization workflows.
- Feature/Setting: “Automations—Content Review”; set rules to auto-tag uploaded files with police case info.
- Feature/Setting: “Auto-tagging rules” for new notes or scanned docs automate evidence categorization.
- Feature/Setting: “Database item created” trigger automates entry tagging by officer, case, or evidence type.
- Feature/Setting: “Custom Skills”—set automation to tag police documents using AI-based content classifiers.
- Feature/Setting: Use “Action Wizard” to automate metadata assignment during PDF upload.
- Feature/Setting: “Intelligent Metadata Layer”—automates recognition and tagging of uploaded evidence.
- Feature/Setting: “Automate Tagging” flow with custom columns for police document routing.
- Feature/Setting: “Rule-based Actions”—automatically categorize and tag incoming law enforcement docs.
- Feature/Setting: “Workflow Automation” for automating document classification in law enforcement repositories.
- Feature/Setting: “Capture and Classify” module for automated extraction and systematic tagging of scanned police evidence.
### 4. Benefits
1. Automates manual sorting, enabling instant access to critical police evidence.
2. Automation standardizes metadata, bolstering compliance and record integrity.
3. Batch automating reduces processing time and labor costs.
4. Minimizes risk of lost or misfiled documents through automated workflows.
5. Real-time document automation supports situational readiness for law enforcement.
6. Automatedly enables audit trails and automation logs for forensic traceability.
7. Automatable integration with case management and notification systems.
8. Automation ensures security and consistency in handling sensitive documents.
9. Automates user assignment, versioning, and role-based access for document security.
10. Facilitates efficient future automating of advanced analytics or AI-driven insights.