# AI use cases for Fincept Terminal (Fincept-Corporation/FinceptTerminal) Repo: [Fincept-Corporation/FinceptTerminal](https://github.com/Fincept-Corporation/FinceptTerminal) | Use cases: 3 | Page: https://dedupedai.com/use-cases/fincept-corporation-finceptterminal/ Fincept Terminal is a native C++20 desktop terminal for financial research with a Qt6 interface and embedded Python analytics. The free AGPL-3.0 open build includes DCF, portfolio optimisation, VaR and Sharpe, derivatives pricing, a QuantLib suite, 37 AI trader, investor and economics agents with your own LLM key, 100+ data connectors, a paper trading engine, broker integrations, a visual node editor and MCP tools. A paid Enterprise edition is sold separately. Not financial advice: paper trade first, and remember you can lose money. This file holds every use case of this repo. Each one starts with a "## " heading and ends with its URL. - Install a free Bloomberg-style research terminal: https://dedupedai.com/use-cases/fincept-corporation-finceptterminal/install-a-free-bloomberg-style-terminal/ - Research markets with 37 AI agents on your own key: https://dedupedai.com/use-cases/fincept-corporation-finceptterminal/research-with-ai-agents-and-your-own-key/ - Practise trades on the built-in paper trading engine: https://dedupedai.com/use-cases/fincept-corporation-finceptterminal/practise-on-the-paper-trading-engine/ ## How to install a free Bloomberg-style research terminal with Fincept Terminal Repo: [Fincept-Corporation/FinceptTerminal](https://github.com/Fincept-Corporation/FinceptTerminal) | Difficulty: Beginner | Time: 30 minutes | Basis: From the README Download the open build and run DCF, portfolio optimisation and risk analytics on your own desktop. **Who it is for:** A finance student or hobby investor who wants institutional style analytics without a terminal subscription. **The problem:** Professional terminals cost thousands a year, and spreadsheets do not cover derivatives or risk models. **The outcome:** A native desktop app with DCF, portfolio optimisation, VaR and Sharpe, derivatives pricing and fixed income tools. ### Steps 1. Download the installer for your platform from the latest GitHub release 2. On Debian or Ubuntu run `sudo apt install ./FinceptTerminal-*.deb`; on Fedora `sudo dnf install ./FinceptTerminal-*.rpm` 3. Launch Fincept Terminal and open the analytics modules 4. Connect free public feeds such as FRED, World Bank or Yahoo Finance first, then add your own keys ### Prompt to paste into your agent ```text Install Fincept-Corporation/FinceptTerminal from the latest release on , run a DCF on with the built-in analytics, and list which data connectors it needed and which ones required my own key. ``` ### Caveat The open build is AGPL-3.0 and ships monthly releases, while the README promotes a paid Enterprise edition. Not financial advice: paper trade first, and remember you can lose money. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/fincept-corporation-finceptterminal/install-a-free-bloomberg-style-terminal/ ## How to research markets with 37 AI agents on your own key with Fincept Terminal Repo: [Fincept-Corporation/FinceptTerminal](https://github.com/Fincept-Corporation/FinceptTerminal) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README Plug your own LLM key or Ollama into the terminal's trader, investor and geopolitics agents. **Who it is for:** An analyst who wants AI agents to draft research inside the same app that holds the data. **The problem:** Copying data between a terminal and a chatbot loses context and wastes time. **The outcome:** Agent research inside the terminal, billed to your own LLM account or run locally. ### Steps 1. Install the terminal as above 2. Add your LLM key (OpenAI, Anthropic, Gemini, Groq, DeepSeek or OpenRouter) or point it at Ollama 3. Pick one of the trader, investor, economic or geopolitics agents and give it a research question 4. Watch your provider's usage page while you test ### Prompt to paste into your agent ```text In Fincept-Corporation/FinceptTerminal, configure and run an investor agent on . Summarise its answer and estimate the token cost of the run. ``` ### Caveat The README warns the open build's real cost is your own data and LLM bills, charged per token with no ceiling. Not financial advice: paper trade first, and remember you can lose money. Risk, credentials: Your LLM and data keys are stored in the app, so protect the machine it runs on. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/fincept-corporation-finceptterminal/research-with-ai-agents-and-your-own-key/ ## How to practise trades on the built-in paper trading engine with Fincept Terminal Repo: [Fincept-Corporation/FinceptTerminal](https://github.com/Fincept-Corporation/FinceptTerminal) | Difficulty: Beginner | Time: 20 minutes | Basis: From the README Use the terminal's paper trading engine with crypto and equity feeds before connecting any broker. **Who it is for:** A beginner who wants to test ideas with live feeds but no real money. **The problem:** Going straight to a live broker turns every mistake into a real loss. **The outcome:** Paper positions tracked against crypto and equity feeds inside the terminal, with no broker connected. ### Steps 1. Install the terminal and open the Trading section 2. Start with the paper trading engine and the crypto or equity feeds 3. Keep broker integrations disconnected while you learn 4. Review results over weeks before considering a live broker ### Prompt to paste into your agent ```text In Fincept-Corporation/FinceptTerminal, set up the paper trading engine with , place three paper trades from my plan , and confirm no broker integration is connected. ``` ### Caveat Paper results ignore real fills and fees, and live trading through a broker is your own risk. Not financial advice: paper trade first, and remember you can lose money. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/fincept-corporation-finceptterminal/practise-on-the-paper-trading-engine/