AI Agent for conversational Q&A over SaaS codebase using large language models

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.

Publication Details

Published
2025-05-16
DOI
https://doi.org/10.31110/colins/2025-2/006
Primary Topic
Mycotoxins in Agriculture and Food
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI Agent for conversational Q&A over SaaS codebase using large language models

Mycotoxins in Agriculture and Food
article

AI Agent for conversational Q&A over SaaS codebase using large language models

article en

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.

Openalex Percentile: Top 33%
Mycotoxins in Agriculture and Food
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.