From Fragmented Capability to Unified Investigation: A Critical Review of Artificial Intelligence Across the Police Investigation Lifecycle

Abstract: Criminal investigation still relies on manual complaint registration, hours of Closed-Circuit Television (CCTV) review and hand-drafted case files. Artificial intelligence (AI) has been applied to parts of this work, such as crime prediction, criminal network analysis, Automatic Number Plate Recognition (ANPR), face recognition and language-based reporting, but these tools remain disconnected. This paper reviews twenty studies published between 2022 and 2026 and identifies nine recurring gaps, including the absence of end-to-end integration, limited explainability, dataset bias and weak coupling with legal procedure. It then proposes Kaval AI, an officer-in-the-loop investigation assistant that connects seventeen modules through one shared case record, from Malayalam and English voice intake to Bharatiya Nyaya Sanhita (BNS) section prediction and charge sheet drafting, with every suggestion confirmed by an officer. The requirements, architecture, database design and a planned evaluation are presented; as a design-stage proposal, the paper reports no experimental results.

Keywords: Police Investigation, Crime Prediction, Graph Neural Networks, Number Plate Recognition, Face Recognition, Knowledge Graphs, Explainable AI, Bharatiya Nyaya Sanhita, Kaval AI