AI CFO India: A Deterministic-First, Retrieval-Grounded Multi-Agent Architecture for Explainable, Compliance-Safe Portfolio Intelligence for Indian Retail Investors
This paper presents AI CFO India, a deterministic-first, retrieval-grounded multi-agent architecture for explainable and compliance-safe portfolio intelligence for Indian retail investors. The system separates deterministic financial computation from AI-generated explanation. Seven independent deterministic agents compute portfolio findings, while a single isolated LLM-based Explainability and Synthesis Agent provides grounded narration. A retrieval-based knowledge base and hard compliance engine are used to reduce hallucination and prevent directive or advisory language. The implementation uses FastAPI, PostgreSQL, pgvector, and a React/TypeScript frontend. An implementation-level evaluation reports 65 passing automated tests covering unit, integration, resilience, and compliance behaviour.
Authors
- Sakshi Satish Patole
Institutions
- Rajarshee Chhatrapati Shahu Maharaj Government Medical College and CPR Hospital Kolhapur (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-08-27
- DOI
- https://doi.org/10.5281/zenodo.22125738
- Primary Topic
- Explainable Artificial Intelligence (XAI)
- Type
- preprint