AI 4 Andhra Police
Modernizing Law Enforcement with AI.
A comprehensive initiative to enhance public safety, optimize resource allocation, and improve response times through data analytics and predictive modeling.
Proactive Policing
From reactive processes to intelligence-driven operations
Intelligence-Driven Systems
AI4AndhraPolice is a comprehensive artificial intelligence initiative aimed at modernizing the Andhra Pradesh Police by integrating advanced AI technologies into everyday policing operations. The project focuses on enhancing decision-making, improving response times, and strengthening operational efficiency.
By applying AI to real-world law enforcement workflows, AI4AndhraPolice supports a shift from reactive processes to proactive, data-informed policing. The initiative emphasizes practical, deployable solutions that assist officers with timely insights while maintaining human oversight and ethical governance.
Various Projects
Core components of the modernization drive
Petition Management System (PMS)
The Petition Management System (PMS) modernizes how public petitions are received, reviewed, and resolved within the police department. Using AI-assisted analysis, the system automatically extracts key issues from petitions, identifies required supporting evidence, checks evidence completeness, and generates structured summaries for officers. PMS reduces manual effort, improves consistency, and ensures faster triaging of cases without replacing human judgment. Officers retain full decision-making authority, while AI acts as a reliable assistant to enhance accuracy, speed, and standardization. The result is a transparent, auditable, and citizen-centric petition workflow that improves resolution timelines and accountability.
Section 91 CrPC Request Management
This platform enables secure, end-to-end management of Section 91 CrPC requests for telecom and banking data. AI automatically extracts case details from SHO and IO request letters, generates operator-specific official formats, and tracks request status through a centralized dashboard. Incoming responses are intelligently mapped to corresponding cases and archived in a structured, searchable manner. The system ensures full traceability, regulatory compliance, and audit readiness while significantly reducing manual coordination. By standardizing workflows and automating documentation, officers can focus on investigations while maintaining legal rigor and accountability.
CDR & IPDR Analysis System
The CDR & IPDR system is an AI-driven document analysis platform designed to handle complex evidence at scale. It ingests and parses diverse document types such as Call Detail Records, Internet Protocol Detail Records, bank statements, FIRs, and subscriber lists. AI extracts structured insights, links entities, and supports investigative analysis while maintaining a clear audit trail from raw documents to conclusions. The platform minimizes manual data handling, improves accuracy, and ensures traceability of evidence throughout the investigation lifecycle. It enables faster intelligence generation without compromising evidentiary integrity.
Investigation Co-Pilot for POCSO
The Investigation Co-Pilot for POCSO cases assists officers in managing sensitive investigations with greater structure, consistency, and care. The system analyzes multiple evidence documents—including FIRs, CDRs, statements, and reports—using AI to extract relevant facts, timelines, and relationships. It supports investigators with organized insights while preserving full human oversight and legal responsibility. Designed for auditability and compliance, the platform ensures that every investigative step is traceable and documented. By reducing cognitive load and manual work, it helps officers focus on timely, accurate, and sensitive case handling.
Docs2Data
Docs2Data transforms manual document handling into an intelligent, automated data extraction system. Using LLM-powered vision capabilities, the platform understands both visual layouts and textual content in scanned PDFs and images. Documents are automatically classified, key fields are extracted, and data is validated against predefined schemas before secure storage. This ensures high accuracy, consistency, and reliability of records. Docs2Data eliminates repetitive manual entry, reduces errors, and accelerates digitization of service records and official documents, enabling structured data readiness across police systems.
WhatsApp Summary
Public WhatsApp groups often surface local incidents faster than traditional channels but are noisy, repetitive, and fragmented. This system automatically collects updates from multiple groups, removes duplication, resolves conflicts, and summarizes information into structured incident reports. A centralized dashboard presents actionable updates, allowing officers to quickly assess, verify, and escalate critical events through the hierarchy. By converting unstructured public chatter into organized intelligence, the platform ensures timely awareness while reducing information overload and improving operational responsiveness.
District News Digest
The District News Digest provides police leadership with a single, reliable morning brief tailored to each district. The system aggregates police-relevant news from trusted English and Telugu sources, organizes and summarizes key developments, and presents them on a web dashboard. Optional PDF reports and WhatsApp summaries are generated based on SP preferences. By replacing fragmented news tracking with a consistent daily digest, the platform enables faster situational awareness, informed decision-making, and proactive response planning across districts.