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Fincept Terminal

Desktop terminal for financial research with analytics, 37 AI agents, 100+ data connectors, paper trading and broker integrations. Free open-source AGPL-3.0 edition plus paid Enterprise plans.

FinanceData analysis

What it does

Fincept Terminal is a desktop application for financial research, written in C++20 with a Qt6 interface and embedded Python for analytics, shipped as a single binary. The GitHub repository holds the open edition under AGPL-3.0, which the README says is free for personal use, learning and academic research. A separate proprietary Enterprise edition is aimed at firms. The open build lists analytics such as DCF, portfolio optimisation, VaR and Sharpe, derivatives pricing and fixed income, plus an 18-module QuantLib suite. It also has 37 agents for trader and investor work, economic analysis and geopolitics, with support for your own LLM provider (OpenAI, Anthropic, Gemini, Groq, DeepSeek, OpenRouter or Ollama). Other parts are more than 100 data connectors, paper trading with 16 broker integrations, and a visual node editor with MCP tools and an AI Quant Lab. Installers are listed for Windows x64, Linux x64 and macOS on Apple Silicon. The README says the open repository now ships one release a month because the team works mainly on Enterprise, and that the open build's real cost is your own data and LLM bills. Enterprise adds private datasets, managed live routing, SSO/SAML, audit logs and RBAC, with its own installers behind an Enterprise login.

Capabilities

  • Financial analytics including DCF, portfolio optimisation, VaR/Sharpe and fixed income
  • 37 AI agents for trader and investor work, economic analysis and geopolitics
  • 100+ data connectors such as FRED, IMF, World Bank and Yahoo Finance
  • Paper trading and 16 broker integrations
  • Visual node editor with MCP tools and an AI Quant Lab
  • Native C++20 and Qt6 desktop app with embedded Python

When to use it

  • You want an open-source desktop terminal for market and economic research and can bring your own data and LLM keys
  • You are a student, hobbyist or academic exploring quantitative analysis and AI agents
  • A firm needs private datasets, access controls and support, which the Enterprise edition covers