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aifi

Python ★ 21 updated 17d ago

💰 AIFi (AI Finance) is an agent-first workspace for compounding investment research and insight.

AIFi is an agent-based investment research workspace that collects filings, earnings, news, and market signals into a reusable research folder, letting each new analysis build on past work.

HTMLCodexAI agentssetup: moderatecomplexity 2/5

AIFi is an investment research workspace that uses AI agents to help users research stocks and financial assets. Instead of starting each analysis from scratch, AIFi breaks investment research into small, reusable AI skills that collect and organize financial data, things like company filings, earnings reports, news articles, market signals, competitor comparisons, and risk evidence. The results are saved under a research folder so future analysis can build on previous work rather than repeating it.

The core idea is compounding research: each time you analyze a company, the findings are stored and can be reused in later queries. This means your tenth analysis of a stock starts from a richer base of context than your first.

Users interact with AIFi through natural language commands run inside Codex. For example, you can ask it to analyze why a stock has recently moved in price, update your existing research with the latest earnings and news, or compare multiple companies and summarize the bull, base, and bear cases for each. The project states it is designed for research and decision support, helping investors think through a position, and is explicitly not for autonomous trading or financial advice.

This makes AIFi useful for individual investors, analysts, or portfolio managers who want a structured, reusable system for tracking and deepening their understanding of individual stocks or sectors over time. Each new research session builds on what came before, so the accumulated research grows alongside continued use. Documentation is offered in both English and Simplified Chinese.

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