FinRobot

Why we included this project

FinRobot bundles large language models into what amounts to a working equity research desk, so you don't have to build the agent plumbing yourself. Its multi-agent setup splits a research request across specialized roles, with some agents gathering data, others running analysis and building models, and one drafting the report. Separate bull, bear, and judge agents then debate the investment case. What keeps the output honest is that valuations like DCF, LBO, WACC, and comps run through deterministic Python compute with provenance tracking, while the LLM handles only the reasoning and the narration. Teams building tools around market data, valuation, or investment research will find ready-made agents, data providers with failover, and a desktop app that turns the workflow into a traceable analyst-style report. It is a practical starting point for automating financial analysis without hand-rolling an agent scaffold.