Title:
Creating an AI Agent Using Unique Language Attributes

Authors:
Michael Sirkovich, Menachem Domb, Israel

Abstract:

This paper presents a Hebrew-first local LLM chat agent that combines Retrieval-Augmented Generation (RAG), citation-aware document answering, controlled web search, and full right-to-left (RTL) user interaction. Unlike cloud-only assistants, the default response path operates locally, supporting privacy, predictable operating costs, and deployment in environments where documents should remain on-premises. The system integrates document upload and indexing, hybrid semantic and lexical retrieval, reranking, source citation construction, streaming responses, and PDF export. The revised manuscript positions the system against local RAG baselines and Hebrew-capable cloud alternatives. It clarifies that the current evaluation is a preliminary system-oriented assessment focused on grounded Hebrew document question answering, lookup, summarization, citation behavior, and latency. The main contribution is a practical architecture for private, transparent, Hebrew-oriented RAG assistance rather than a new foundation model.

DOI: http://dx.doi.org/10.51505/ijaemr.2026.11401