Tax Advisor AI: An Agentic RAG Framework for Indian Income Tax Guidance using Knowledge Graphs and Hybrid Retrieval
  • Author(s): Rehan Rajesh; Nivin Roy; Harikrishnan S; Gautham P; Priya Jose
  • Paper ID: 1715545
  • Page: 2581-2588
  • Published Date: 27-03-2026
  • Published In: Iconic Research And Engineering Journals
  • Publisher: IRE Journals
  • e-ISSN: 2456-8880
  • Volume/Issue: Volume 9 Issue 9 March-2026
Abstract

Starting off, understanding India’s tax law from 1961 isn’t simple - for regular folks or businesses. Because updates happen all the time, things get harder. Then there’s the split setup now: one old method, one new. That adds confusion. On top of that, sorting out deductions listed in Chapter VI-A involves subtle differences people miss. Most search tools just hunt for words, so they miss what someone actually means to ask. Meanwhile, big AI models talk well but make up rules that don’t exist - like mixing up how much you can claim under Section 80C compared to 80CCD Meet Tax Advisor AI - a smart tool built just for Indian tax questions. It gives clear answers backed by law, each one linked to real sources. At its core runs something new: Agentic RAG, not your usual search setup. Instead of just pulling documents, it thinks through problems step by step using ReAct logic, guided by the DeepSeek R1T engine. Queries get split into smaller pieces so nothing gets missed. For finding facts, it uses two methods at once - deep meaning scans plus keyword matching - blended smartly with RRF scoring. Beneath the surface lies a Neo4j graph, a web of connections that prevents conflicting rules from colliding. This system, when new information arrives, taps into live web sources, specifically the Tavily API, to ensure it reflects the latest official pronouncements. Tests demonstrate its ability to translate complex legal language into straightforward financial advice, outperforming simpler data retrieval techniques.

Keywords

Agentic RAG, Knowledge Graphs, DeepSeek, Indian Taxation, Hybrid Retrieval, Neo4j, Natural Language Processing, FinTech, Legal Tech.

Citations

IRE Journals:
Rehan Rajesh, Nivin Roy, Harikrishnan S, Gautham P, Priya Jose "Tax Advisor AI: An Agentic RAG Framework for Indian Income Tax Guidance using Knowledge Graphs and Hybrid Retrieval" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 2581-2588 https://doi.org/10.64388/IREV9I9-1715545

IEEE:
Rehan Rajesh, Nivin Roy, Harikrishnan S, Gautham P, Priya Jose "Tax Advisor AI: An Agentic RAG Framework for Indian Income Tax Guidance using Knowledge Graphs and Hybrid Retrieval" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1715545