Year: 2025
Type: conference-paper
Abstract: Software as a Service (SaaS) has become the dominant model in modern software, yet its sprawling, complex codebases pose daunting challenges for developers-especially as new engineers onboard to the project.Traditional keyword-based search and static documentation struggle to address this scale.Meanwhile, recent breakthroughs in Large Language Models (LLMs) offer powerful capabilities in natural language understanding and semantic search.By leveraging these models, it becomes possible to build conversational AI agents that let developers query a SaaS codebase in natural language.In doing so, the agent can surface contextually relevant snippets, streamline problem-solving, and accelerate the onboarding process.This article introduces an AI Agent for conversational Question Answering over SaaS code, using LLMs to streamline information retrieval, accelerate onboarding, and enhance overall productivity.The proposed approach leverages natural language interactions to deliver rapid, relevant answers directly from the codebase, spotlighting the transformative potential of LLM-based solutions in large-scale SaaS environments.
Authors: Olga Cherednichenko, Dmytro Sytnikov, Nazarii Romankiv, Nataliia Sharonova, Polina Sytnikova
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W7084096726
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