85Score
TradingAgentsTauricResearch/TradingAgentsA multi-agent research desk: analyst agents argue the bull and bear case, a risk agent signs off before any trade idea moves.
★ 118k stars · Intermediate · updated 2026-10
AI Agents deep dive
FinRobot Review | AI Agents That Write the Analyst Report You Never Read
FinRobotAI4Finance-Foundation/FinRobotFinRobot is a free, Apache-licensed AI agent platform from the 
AI4Finance Foundation that pulls financial statements and drafts equity research reports with valuations, charts and a bull versus bear debate. It fits investors and analysts who want a first draft of company research fast. The catch: it needs several paid data and AI keys, it does not place trades, and public user feedback is nonexistent.
Think of it as a junior analyst team in a box: one pulls the filings, one runs the spreadsheet, one writes the memo, and two argue bull and bear before a judge signs off.
Read the transcript
Give it a ticker. Get back a multi-page analyst report with a valuation, charts and a bull versus bear debate. Sounds like a Wall Street desk in a box, right? Here's the catch.
FinRobot is a free, Apache-licensed AI agent platform from the AI4Finance Foundation, the group behind FinRL. Think of a junior analyst team: one pulls the filings, one runs the spreadsheet, one writes the memo, and two argue before a judge signs off.
Five things we like.
One, it pulls real financial statements from Financial Modeling Prep.
Two, it builds a DCF valuation, which estimates what a company is worth from its future cash.
Three, the math runs in plain Python, so the AI can't invent the numbers. That's the right instinct.
Four, reports export to HTML or PDF with more than fifteen chart types.
Five, a desktop app for Apple Silicon Macs adds data from Finnhub and SEC EDGAR.
Two cautions. It needs several paid data and AI keys. And we found zero independent user reviews, so test it on a company you already know cold.
Best for long-term investors who want a fast first draft of research. It doesn't trade. Scroll down for setup steps and alternatives.
This is education, not financial advice. Your market edge starts with the right tool. Stay alpha.
FullStack Alpha Editorial Team
Reviewed by Jay Rocco, Chief Editor
What Is FinRobot and What Does It Actually Do?
The project is a repo (a project's folder of code on 
GitHub) from the AI4Finance Foundation, the same group behind FinRL and FinGPT. It uses large language models (the AI behind 
ChatGPT and Claude) as a team of agents (AI workers that each handle one task) to research public companies. Give it a ticker and it produces a multi-page report.
The workflow mirrors a sell-side desk. First it fetches income statements, balance sheets and cash flows from 
Financial Modeling Prep. Then it builds three-year projections, a DCF valuation (an estimate of what a company is worth based on its future cash) and a peer comparison. Finally, specialized agents write the investment thesis, risks and valuation summary into an HTML or PDF report with more than 15 chart types.
One design choice deserves credit. The README says every financial figure comes from plain Python math, while the AI only handles reasoning and writing. That matters, because language models are notorious for inventing numbers. Keeping the arithmetic out of the chatbot's hands is the right instinct.
There are three flavors. An open-source Python framework, a web app that runs on your machine, and FinRobot Desktop, a native app for Apple Silicon Macs that adds debate agents, LBO and Monte Carlo analysis, and data from FMP, Finnhub, yfinance, 
SEC EDGAR and others with automatic failover. A commercial 
FinRobot Pro lives at finrobot.ai.
Why should a retail investor care? Because the hardest part of fundamental research is not the insight, it is the hours of copying numbers into a spreadsheet before insight is even possible. Hand that part to a machine and you get more time for the questions that matter: is this business getting better or worse, and what is the market already pricing in?
Community Score
78 / 100
- Adoption · How many people starred it
- 23.5 / 30
- Maintenance · How recently the code was updated
- 25 / 25
- Community sentiment · What traders say on Reddit and Hacker News
- 8 / 20
- Builder activity · How many people built their own copy
- 11 / 15
- License clarity · Whether you are clearly allowed to use it
- 10 / 10
GitHub data checked 2026. Community read: not enough independent discussion yet.
- Stars
- 8,327
- Forks (people who built on it)
- 1,402
- Written in
- Python
- License
- Apache-2.0
- Last update
- 2026-10-24
- Markets
- Stocks
- Skill level
- Advanced
Works with
Is FinRobot Right for You?
Good fit if you are
- Long-term investors who want a structured first draft of company research before reading the 10-K themselves
- Finance students learning how DCF models, comps and analyst reports fit together
- Developers building AI research tools who want a working agent pipeline to study and extend
- Analysts who want to speed up the boring data-gathering part of coverage
Skip it if you are
- You want a trading bot. This tool writes research, it does not execute trades.
- You are not comfortable with conda, Python environments and juggling several API keys
- You trust AI-written reports without checking sources. Do not.
The jargon, in plain English
- AI agent
- An AI worker given one job and tools to do it, such as fetching data or writing a section.
- Large language model (LLM)
- The type of AI behind ChatGPT and Claude, trained on huge amounts of text to read and write.
- DCF valuation
- Estimating what a company is worth today by adding up the cash it should earn in future years, discounted for time and risk.
- Comps
- Comparing a company's valuation with similar companies to see if it looks cheap or expensive.
- SEC EDGAR
- The free US government database of company filings like annual and quarterly reports.
- API key
- A password your code uses to pull data from a service or talk to an AI model.
- Equity research report
- The kind of document a Wall Street analyst writes on a stock: business, numbers, valuation, risks and a view.
What Do Traders Say About FinRobot?
The repo has more than 8,000 GitHub stars and about 1,400 forks (copies people build on), and its last code push was days ago. Yet our search found no relevant public discussion from users on 
Reddit or 
Hacker News. No reviews, no complaints, no success stories.
That silence is common for academic and foundation projects. Developers star them to study later, few post results. For you, it means the README and sample reports are the only evidence, so judge it by running it on a company you already know well and checking every claim.
What they like
- Active maintenance with recent commits
- Apache 2.0 license, free to use and modify
- Numbers computed in code, not invented by the AI
What they complain about
- No relevant public user discussion found
- Several separate API keys required
- Desktop app is Apple Silicon only and not yet notarized
How Do You Set Up FinRobot Safely?
Plain steps, fake money first. Keep your keys in a private settings file, never pasted into the code.
- 01Create a Python 3.10 environmentThe README uses conda: create an environment named finrobot with Python 3.10 and activate it.
- 02Install the packageClone the repo and run pip install -U finrobot, or pip install -e . from inside the folder.
- 03Add keys to the config files, not codeRename OAI_CONFIG_LIST_sample to OAI_CONFIG_LIST and add your OpenAI key. Rename config_api_keys_sample to config_api_keys and add
Finnhub, FMP and 
SEC API keys. - 04Start the equity research web appCopy the example config.ini, then run ./deploy.sh start. The app opens at a local address on port 8001.
- 05Test on a company you knowGenerate a report for a stock you follow closely and compare its numbers with the actual filings before trusting any output.
- 06Keep it as research, not ordersThe project's own disclaimer says it is not a recommendation for live trading. Use reports as a starting point for your own analysis.
What Do You Need to Run FinRobot?
A computer with Python and conda
The framework and web app run locally in a Python 3.10 environment. The Desktop app needs an M1 or newer Mac.
An AI model API key
The agents need a language model to reason and write. You pay per use.
OpenAIFinancial data API keys
Reports are built from financial statements, filings and market data.
Optional sentiment data
Adds a retail sentiment section to reports.
Adanos
What Are the Risks of Using FinRobot?
Confident prose, uncertain judgment
A polished 13-chapter report feels authoritative. The thesis is still an AI's opinion built on projections, and projections are guesses.
Key sprawl and running costs
OpenAI, FMP, Finnhub and SEC API each need their own account. Free tiers run out, and AI usage bills grow with every report.
No trading, no track record
It does not execute trades, and there is no public evidence that its reports lead to better decisions.
Desktop app friction
The Mac app is
Apple Silicon only and not yet Apple-notarized, so macOS may flag it as damaged until you run a Terminal command to clear it.Thin public feedback
No independent user discussion was found, so bugs and limits will be yours to discover.
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What Are the Best FinRobot Alternatives?
- 85ScoreTradingAgentsTauricResearch/TradingAgents
84Score
Vibe-TradingHKUDS/Vibe-TradingA multi-agent research workspace from HKU with built-in backtest engines and trade-journal analysis.
★ 37k stars · Intermediate · updated 2026-10
Claude- Codex
Local models
83Score
AI Hedge Fundvirattt/ai-hedge-fundInvestor-persona agents debate a stock, then a portfolio agent makes the call. A teaching project, not a fund.
★ 64k stars · Intermediate · updated 2026-10
Gemini
DeepSeekShould You Use FinRobot? Our Verdict
This is the most practical AI research tool in the AI4Finance family. It turns a ticker into a structured analyst-style report with real valuation math, and it keeps the numbers out of the chatbot's hands. For investors who already do fundamental work, that is hours of grunt work handed to a machine.
But a faster first draft is not a better decision. It will not trade for you, it costs real money in API calls, and nobody has publicly shown it improves results. Use it to build the folder, then read the filings yourself. The edge is still in the judgment, not the formatting.
A sensible routine: run a report on three companies you already own, mark every number you can verify against the 10-K, and note where the narrative overreaches. If it passes that audit, keep it in your research process as the first-draft machine. If it fails, you learned that for the cost of a few API calls.
More FinRobot Questions, Answered
What is FinRobot?
It is an open-source AI agent platform from the AI4Finance Foundation that drafts equity research reports. It pulls financial statements, builds valuations and peer comparisons, and writes the analysis with language models.
Is FinRobot free?
The open-source framework is free under the Apache 2.0 license. You still pay for the API keys it needs, such as OpenAI and Financial Modeling Prep, and a commercial FinRobot Pro is offered separately at finrobot.ai.
Can FinRobot trade stocks for me?
No. It generates research reports and analysis. Its disclaimer says the code is not a recommendation for live trading.
Does FinRobot work with ChatGPT or Claude?
The README names OpenAI as the model provider and says the platform supports plug-and-play use of other models. OpenAI is the only provider named explicitly in setup.
What data does FinRobot use?
Financial Modeling Prep, Finnhub, SEC filings and yfinance, with the Desktop app adding Adanos sentiment and automatic failover between seven providers.