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 an important input for investment research, revealing management’s strategic direction, forward guidance, competitive position and analyst Q&A. These insights come in many formats: text transcripts, audio recordings, and accompanying financial charts.
This article discusses the development of a multi-modal retrieval-augmented generation (RAG) investment agent designed to analyze earnings calls. This highlights how traditional analysis methods fail to capture subtle information in audio, text and visual data. The author presents a solution that uses AI to autonomously process this multi-modal information, significantly increasing 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.
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Published via Towards AI
