Agentic AI and SLM Optimization_By Nano i Tech

BACKGROUND

This project redefines automation in the insurance sector. The primary objective is to overcome the structural limitations of public, general purpose LLMs such as variable latency and high scaling costs—by engineering native, intelligent agentic AI workflows. This academic industrial synergy aims to build an architecture capable of orchestrating specialized sub-agents and eliminating interpretative rigidities, thereby ensuring fluid, accurate, and high precision semantic data extraction and comparison for the professional market. Nano-i-Tech leads the initiative, leveraging industrial expertise to accelerate innovation by evolving the Navisio AI ecosystem.

CHALLENGE

The central challenge focuses on a targeted transition toward proprietary Small Language Models (SLMs) and/or agentic workflows, securely hosted and vertically trained on the financial and insurance domain. By optimizing Navisio AI’s deep reasoning pathways, the research introduces an advanced orchestration framework built upon three pillars: extraction reliability, domain specific fine tuning, and granular governance control. The ultimate result is the transformation of the platform into an AI native engine where validation cycles and the alignment of similar concepts are no longer hindered by rigid defensive approaches but are empowered for immediate decision making fluidity.

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