Scalability and Performance Benchmarking of LangChain, LlamaIndex, and Haystack for Enterprise AI Customer Support Systems
Year: 2024
Type: conference-paper
Abstract: The growing complexity of enterprise applications, fueled by advancements in Artificial Intelligence (AI), demands robust frameworks capable of leveraging Large Language Models (LLMs) to process vast datasets, automate decision-making, and improve customer interactions. This article conducts an in-depth evaluation of three leading LLM frameworks, LangChain, LlamaIndex, and Haystack each known for their strengths in handling different aspects of AI-driven workflows. LangChain excels in building complex, multi-component AI applications with advanced memory and context management [1], while LlamaIndex is optimized for large-scale data indexing and real-time retrieval [2], making it invaluable for high-speed query processing. Haystack, with its modular and open-source architecture, focuses on precise information retrieval and question-answering (QA) systems [3], offering powerful search capabilities for enterprises requiring high accuracy.
Institution: Birla Institute of Technology and Science, Pilani
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4402339038