Name in original language
Gestão de Prova Pericial com Inteligência Artificial Vestível
Initiative overview
This initiative introduces wearable artificial intelligence into forensic workflows within a public forensic laboratory in Brazil. The technology enables continuous audiovisual recording, automatic transcription, and structured organisation of forensic examinations in real time. It was developed to address inefficiencies in traditional forensic processes, which rely heavily on manual documentation and are time-consuming and prone to information loss. The primary objective is to improve the reliability, traceability, and efficiency of forensic evidence production. By integrating AI into the examination process, the initiative enhances documentation quality and supports forensic experts in capturing detailed, contextualised information without interrupting their workflow. This contributes to stronger chain of custody practices and more transparent judicial processes.
The initiative is currently active and being progressively expanded within the laboratory. It is expected to evolve through increased adoption, refinement of AI capabilities, and integration with digital forensic systems. The model is scalable and can be replicated across different forensic domains and jurisdictions, particularly in contexts facing high demand and limited human resources.
Results, outcomes and impacts
Preliminary results based on approximately 55 forensic examinations show significant improvements: up to 67% reduction in examination time, 75% reduction in pre-report preparation time (from 2 hours to 30 minutes), and up to threefold increase in processing capacity per forensic expert. These results were measured through comparative time analysis between traditional and AI-supported workflows. The initiative reduces backlog, improves efficiency, and enhances the reliability and timeliness of forensic evidence delivered to the justice system.
Challenges and lessons learned
Key challenges included adapting workflows to integrate AI without disrupting established forensic procedures, ensuring data security, and maintaining the central role of the forensic expert in decision-making. Initial resistance to technological change was addressed through training and gradual implementation. Lessons learned highlight the importance of human-centred design, clear governance, and incremental adoption. Successful implementation requires institutional support, capacity-building, and alignment with legal and ethical standards, particularly regarding transparency and accountability in the use of AI.
