Government Projects

Petition AI (Grievance Redressal) modernizes how public grievances are received, reviewed, and processed within the police department by using AI-assisted analysis to extract key issues and claims, highlight investigative gaps, verify supporting documents, and generate clear, structured summaries for officers. This drastically reduces the time senior officers spend on review—from 30–45 minutes per case to just 5–10 minutes—while improving consistency, accuracy, and prioritization across cases. The system streamlines triaging without replacing human judgment, ensuring officers retain full decision-making authority, with AI acting purely as a support layer to enhance speed, standardization, and reliability. The result is a transparent, auditable, and citizen-centric grievance redressal workflow that improves turnaround times, accountability, and overall operational efficiency.

The Police LLM Core Services form the foundational digital backbone for all present and future police applications in Andhra Pradesh. This unified platform ensures that administrative systems and advanced investigation tools operate on clean, structured, and consistent data. It includes centralized core data for personnel, units, and jurisdictions; shared platform services like logging, notifications, and access control; common user management with secure authentication and single sign-on; and reusable AI services such as prompt management, RAG, and AI agents. Together, these services enable scalable, governed, and interoperable solutions across the police ecosystem.

Digital Evidence AI enables secure, end-to-end handling of lawful data requests by automating the extraction of case details from SHO and IO letters, generating operator-specific official formats under Section 91 CrPC, and tracking request status through a centralized dashboard. Incoming responses are systematically linked to the relevant cases and archived in a structured, searchable repository. Serving as an AI Nodal Officer for Section 94 BNSS compliance, the system also automates the creation and tracking of legally compliant notices to telecom operators, banks, and payment gateways, enabling faster and error-free digital evidence collection. Together, these capabilities ensure complete traceability, regulatory compliance, and audit readiness while significantly reducing manual coordination. By standardizing workflows and automating documentation, the platform allows officers to focus more on core investigative work while maintaining legal rigor and accountability.

CognitiveNet AI (Evidence-Based Investigation) is an AI-driven evidence analysis platform built to handle complex investigative data at scale. It ingests and processes diverse sources such as Call Detail Records, Internet Protocol Detail Records, bank statements, FIRs, and subscriber lists, extracting structured insights, linking entities, and supporting investigative analysis with a clear audit trail from raw documents to conclusions. Serving as a unified AI workbench that replaces multiple licensed tools, the platform consolidates disparate data sources into a single environment and generates natural language narratives along with behavioral pattern insights for Investigating Officers. By minimizing manual data handling, improving analytical accuracy, and ensuring end-to-end traceability of evidence across the investigation lifecycle, the system enables faster intelligence generation without compromising evidentiary integrity.

The Investigation Co-Pilot for POCSO cases assists officers in handling sensitive investigations with greater structure, consistency, and care by analyzing multiple evidence sources—including FIRs, CDRs, statements, and reports—to extract relevant facts, timelines, and relationships. In addition to organizing investigative insights while preserving full human oversight and legal responsibility, the platform functions as a training and compliance assistant that guides officers through legal procedures by suggesting relevant sections of law (BNS, POCSO, IT Act), validating Case Diaries, and flagging missing or weak evidence to strengthen case quality and improve conviction outcomes. Designed for auditability and compliance, the system ensures every investigative step is traceable and documented, while reducing cognitive load and manual effort so officers can focus on timely, accurate, and sensitive case handling.

Docs2Data transforms manual document handling into an intelligent, automated data extraction system by using LLM-powered vision to understand 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, ensuring high accuracy, consistency, and reliability of records. Serving as a digitization engine, the platform converts decades of paper-based personnel and service records into a searchable digital knowledge base through AI-powered OCR and semantic search, significantly reducing administrative overhead. By eliminating repetitive manual entry, minimizing errors, and accelerating large-scale digitization, Docs2Data enables structured data readiness and operational efficiency across police systems.

Public WhatsApp groups often surface local incidents faster than traditional channels, but the information is noisy, repetitive, and fragmented. This system automatically collects updates from multiple groups, filters law-and-order–relevant content, removes duplication, resolves conflicts, and categorizes incidents such as crimes and agitations into structured incident reports. A centralized dashboard presents actionable updates mapped to specific police jurisdictions, enabling real-time situational awareness and helping officers 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.

News360 AI provides police leadership with a single, reliable morning brief tailored to each district by aggregating police-relevant news from trusted English and Telugu sources, organizing and summarizing key developments, and presenting them through a web dashboard with optional PDF reports and WhatsApp digests based on SP preferences. As an automated news monitoring system, it continuously tracks state- and district-level coverage across vernacular and English media, translates content, and links related stories to build a coherent narrative timeline of events. By replacing fragmented news tracking with a consistent, contextual daily intelligence feed, the platform enables faster situational awareness, more informed decision-making, and proactive response planning across districts.

AI Foundation (Core Services Platform) serves as the common backbone for all AI systems, providing shared services such as prompt management, observability, access control, and governance. It standardizes how AI models are used, monitored, and secured across applications, ensuring consistent behavior and controlled outputs. The platform centralizes authentication, logging, and policy enforcement, enabling secure data handling and audit-ready operations. By offering reusable AI components and APIs, it allows teams to rapidly build, deploy, and scale new AI use cases without duplicating core capabilities. This foundation ensures reliable, secure, and scalable AI adoption while supporting faster innovation across departments.