Building A Multi-Modal Investment Agent for Earnings Call Analysis

Author(s): Farhad Malik Originally published on Towards AI. A Working Investment Agent To Process Transcripts, Audio, and Charts with AI to Generate Insights Earnings calls are a key input to investment research, revealing management’s strategic direction, forward guidance, competitive positioning, and analyst Q&A. These insights arrive in multiple formats: text transcripts, audio recordings, and accompanying financial charts. main application — by authorThis article discusses the development of a multi-modal Retrieval-Augmented Generation (RAG) investment agent designed to analyze earnings calls. It highlights how traditional analysis methods fail to capture nuanced information across audio, text, and visual data. The author presents a solution that utilizes AI to autonomously process this multi-modal information, thereby significantly enhancing the efficiency of investment research. Key functions include extracting insights from financial transcripts, audio recordings, and visual charts, facilitating quicker and more accurate investment decisions. Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Published via Towards AI