Title: ASTITAVA: An AI-Driven WebGIS for Scalable FRA Monitoring and Decision Support


Authors: Aditya Tiwari, Aryan Singh Bhadoria, Akshay Khanna, Anvesh Trivedi, Nisha Rathi, Ashish Anjana


Published in: Volume 3 Issue 1 Jan June 2026, Page No. 72-75


DOI: 10.63844/IJAITR.v3.i1.2026.72-75 cite


Keywords: AI Agent, Governance Agent, Agent-Based Architecture, AI Pipeline, Cognitive Reasoning, Forest Rights Act, Digital Governance, Explainable AI (XAI)


Abstract: Abstract—We introduce ASTITAVA, a novel governance agent architecture designed to address systemic challenges in implementing the Forest Rights Act (FRA), 2006. We re-frame the complex administrative task as an autonomous agent problem. The agent’s pipeline integrates a multi-stage perception module (OCR/NER) for ingesting and understanding unstructured legacy documents, a cognitive module for spatio-temporal reasoning (PostGIS integration and a Claim Health Scoring Model), and an action module (a hybrid ML-DSS) for optimized policy recommendations. A WebGIS atlas serves as a human-agent interface for explainability and oversight. Piloted on 15,000 claims, the ASTITAVA agent demonstrates a 67% reduction in processing time and 89.2% accuracy in eligibility prediction. This work contributes a tested, scalable framework for a new class of applied AI agents in complex digital governance.


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