Digital Evidence Management

Facial recognition utilizes AI to compare images of missing persons with datasets, such as surveillance footage or social media posts. It speeds up identification and improves accuracy.

Facial attribute prediction analyzes features like age, gender, and emotions to provide additional insights, even from incomplete or blurry data.

Drones cover large areas quickly, provide aerial views, and use thermal imaging to detect body heat, making them invaluable in challenging terrains or disaster zones.

Predictive analytics analyzes patterns in data to prioritize leads and focus resources, such as identifying likely locations in human trafficking cases.

When implemented responsibly, with robust safeguards, facial recognition can comply with regulations and ethical standards.

Many technologies are scalable, making them accessible to agencies of all sizes, regardless of their varying budgets and resources.

Common challenges include integration with legacy systems, training personnel, and ensuring compliance with legal frameworks.

Yes. Corrections facilities use VIDIZMO Digital Evidence Management System for managing surveillance footage from facility cameras, documenting inmate incidents, and preserving evidence for internal investigations and legal proceedings. Chain of custody tracking ensures admissibility.

CaseBot uses retrieval-augmented generation (RAG), meaning every answer is grounded in actual evidence data with source citations. Confidence scoring flags low-certainty responses, and human-in-the-loop checkpoints ensure investigators verify AI-surfaced findings before acting on them.

Redactor is built into the Digital Evidence Management System, giving agencies a single-platform workflow for evidence management and FOIA redaction. Evidence custodians locate files, apply AI-powered redaction with exemption codes, review, and disclose without transferring files to a separate tool.