A financial terminal built by India-based Fincept Corporation for portfolio managers, hedge fund analysts, and independent traders. It is a desktop application for Mac, Windows, and Linux that brings real-time market data, technical indicators, and analytics such as DCF valuation and portfolio optimization into a single workspace. What sets it apart is its suite of AI agents modeled on the investment philosophies of well-known investors including Warren Buffett, Benjamin Graham, and Peter Lynch. The core product is released as open source under AGPL-3.0, with a separate commercial license available under a dual-licensing model. The first release went public in September 2024, and development has continued since.
Key Features
- AI agents modeled on investment philosophies: Alongside agents that reproduce the thinking of Buffett, Graham, and Lynch, the terminal ships with many other roles such as traders, economists, and geopolitical analysts. The aim is “agentic research” that assembles sourced research notes rather than chat replies
- Bring your own LLM: Supports OpenAI, Anthropic, Gemini, Groq, DeepSeek, OpenRouter, and locally run Ollama. Because you supply your own API keys, you can also keep everything on your own machine
- Over 100 data connectors: Ships with a wide range of built-in sources spanning public statistics, market data, and crypto, including FRED, the IMF, the World Bank, DBnomics, Yahoo Finance, Polygon, and Kraken
- Serious analysis and validation tools: Covers DCF valuation, portfolio optimization, VaR and Sharpe ratio calculations, and derivatives pricing. A Quant Lab handles backtesting and factor discovery
- Paper trading and broker integration: Test strategies with simulated trades first, then connect a brokerage account on higher plans to place live orders and run algorithmic strategies
- Open source and lightweight: A single-binary native application written in C++20 and Qt6, with no Electron dependency. The source is published on GitHub, so you can build it yourself
Pricing
| Plan | Monthly price | What’s included |
|---|---|---|
| Open Source Edition | Free | Desktop and browser access. Public market data sources, standard usage limits |
| Exclusive | $99 | 400 AI credits, 1 portfolio / 3 watchlists / 1 paper account, 1 year of price history. Market data, charts, news, backtesting |
| Exclusive+ | $199 | 2,000 AI credits, 10 portfolios / 25 watchlists / 5 paper accounts, 5 years of price history, 1 linked broker account, AI research and agent teams, derivatives |
| Exclusive Pro | $299 | 5,000 AI credits, unlimited portfolios, watchlists, and price history, unlimited broker accounts, live order placement and production algo deployment |
Paid plans are billed monthly with no annual lock-in, and choosing quarterly billing gives a 15% discount. If you run out of AI credits, you can top up with add-on packs ranging from $29 to $149. The open-source edition is free for personal and academic use, but commercial distribution or deployment requires a separate Enterprise license, which is worth checking before you commit.
Pricing is current as of August 2026. Check the official site for the latest information.
Pros & Cons
✅ Pros
- The open-source edition is free, so you can try the core terminal features at no cost
- Because you bring your own LLM API key, you control both model choice and cost. With Ollama you can keep everything local
- More than 100 built-in data sources, from public statistics to crypto, cut down significantly on data-collection groundwork
- DCF, portfolio optimization, and backtesting all live in one application, so there is less jumping between tools
- Built as a native app, it stays responsive and runs on Mac, Windows, and Linux alike
⚠️ Cons
- Paid plans start at $99 per month, which is steep for individual use, and the gap from the free edition is large
- It targets professional analysts and traders, so it is hard to get value from without background knowledge of financial terminology and metrics
- Using the AI features requires a separate LLM API key, and those usage fees are on you
- The AGPL-3.0 license means commercial embedding or redistribution needs licensing review
- Development moves quickly, so behavior can change between versions and production use warrants its own validation
Comparison with Similar Services
| Criteria | FinceptTerminal | OpenBB | TradingView | Bloomberg Terminal |
|---|---|---|---|---|
| Delivery | Desktop app (OSS + paid tiers) | OSS + cloud edition | Web service | Dedicated terminal and software |
| Free option | Open-source edition | Open-source edition | Free plan available | None |
| AI agents | Many agents, including ones modeled on investment philosophies | AI features (plan dependent) | Some AI features | Proprietary AI and analytics |
| Bring your own LLM | Yes (OpenAI / Anthropic / Ollama, etc.) | Yes | No | No |
| Main strength | Analysis through agent operation in one place | Python-based analysis and extensibility | Charting and community | Data coverage and industry standard status |
Who Is It For
- Independent traders who cannot justify an expensive financial terminal but want something close to a professional analysis environment
- Analysts who research across multiple data sources and want to reduce collection and cleanup work
- People who want generative AI in their investment research but prefer to decide which models to use and where data lives
- Engineering-minded investors who want to keep everything local, or read the code to verify behavior
- Anyone moving backtesting and portfolio optimization out of spreadsheets and into a purpose-built tool
Summary
FinceptTerminal combines an open-source financial terminal with AI agents and more than 100 data connectors, landing squarely on the research side of the toolset. Since the free open-source edition covers the core features, the sensible first step is to install it locally and check whether the data sources you rely on are available. Agent teams, broker integration, and live order placement sit behind the paid tiers, so weigh the features you need against the $99-per-month starting price. Also factor in that using the AI features requires an LLM API key of your own.