Fincept-Corporation/FinceptTerminal

FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive...

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Summary Information

Updated 24 minutes ago
Added to GitGenius on April 25th, 2026
Created on August 29th, 2024
Open Issues & Pull Requests: 10 (+0)
Number of forks: 4,270
Total Stargazers: 30,235 (+0)
Total Subscribers: 167 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 37.3 hours
Mean response time: 4.2 days
90th percentile: 7.3 days
Tracked items: 75

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 11% of issues opened in the past year have been closed. Three people close 100% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 11
New in 7 days: 1
Closed in 7 days: 0
Avg open age: 10 days
Stale 30+ days: 6
Stale 90+ days: 0

Recent activity

Opened in 7 days: 1
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • status:triage (45)
  • type:bug (30)
  • type:feature (5)
  • type:documentation (4)
  • type:performance (4)
  • bug (2)
  • type:enhancement (2)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

Fincept Terminal is a native C++20 desktop application designed as a comprehensive financial intelligence platform comparable to Bloomberg Terminal. Built by Fincept Corporation and available at https://fincept.in, the application provides institutional-grade financial analytics, market data connectivity, and AI-driven investment research tools. The repository is classified across multiple financial domains including Financial Terminal, Market Data, Real-time Data, Charting Tools, Financial Analytics, Investment Platform, Trading Platform, and Stock Market analysis.

The application is built with Qt6 for its user interface and rendering, incorporates embedded Python for analytics capabilities, and delivers professional terminal-class performance as a single native binary. The platform supports multi-asset analytics including DCF models, portfolio optimization, and risk metrics such as Value at Risk and Sharpe ratios across equity, fixed income, derivatives, portfolio, and alternative asset classes. A distinctive feature is its integration of 37 AI agents spanning Trader/Investor frameworks named after renowned investors like Buffett, Graham, Lynch, and Munger, alongside Economic and Geopolitics frameworks. These agents support local LLM deployment and integrate with multiple AI providers including OpenAI, Anthropic, Gemini, Groq, DeepSeek, MiniMax, OpenRouter, and Ollama.

The platform connects to over 100 data sources including DBnomics, Polygon, Kraken, Yahoo Finance, FRED, IMF, World Bank, and AkShare, with optional alternative data overlays such as Adanos market sentiment. Real-time trading capabilities span cryptocurrency through Kraken and HyperLiquid WebSocket connections, equity markets, and algorithmic trading with a paper trading engine. The application integrates with 16 broker platforms including Zerodha, Angel One, Upstox, Fyers, Dhan, Groww, Kotak, IIFL, 5paisa, AliceBlue, Shoonya, Motilal, Interactive Brokers, Alpaca, Tradier, and Saxo. Additional features include a QuantLib suite with 18 quantitative analysis modules, global intelligence capabilities for maritime tracking and geopolitical analysis, a visual node editor for automation workflows, and an AI Quant Lab supporting machine learning models and reinforcement learning trading strategies.

The repository overlaps with contributors from openclaw/openclaw and mattpocock/skills projects.

As of June 2026, the project has transitioned to monthly updates due to funding constraints, with the team focusing on a subscription-based private edition and a new project called Quantcept available on npm. The open-source repository remains publicly available and will not be deleted. The application is distributed through pre-built installers for Windows x64, Linux x64, and macOS Apple Silicon, with version 4.1.0 being the latest release. The codebase requires exact pinned versions of dependencies including CMake 3.27.7, Ninja 1.11.1, Qt 6.8.3, and Python 3.11.9 for successful compilation from source.