Our mission is to build the systems and technologies that enable financial intelligence to transcend institutions and borders, understand how time, risk, and value shape markets, and extend to everyone the power to understand and shape our financial future.

Financial markets run on a continuous chain:

Data  ->  Research  ->  Decision  ->  Risk  ->  Execution  ->  Feedback

For most developers and organizations, that chain is fragmented across data vendors, notebooks, backtesting tools, broker APIs, execution services, and internal infrastructure.

QuantDinger brings the chain into one open system.

It gives developers, quantitative researchers, and AI agents a shared foundation for researching markets, building strategies, validating evidence, controlling risk, and operating across crypto, equities, futures, and forex.

QuantDinger is not a black-box trading bot, a strategy marketplace, or another charting application. It is an extensible financial infrastructure layer designed to support the full lifecycle of systematic trading.

The next generation of financial software will be operated by both people and AI agents. QuantDinger is designed to become the infrastructure those agents can safely use.

• Agents can discover market context, generate research, and build strategy logic.
• Reproducible experiments separate ideas from evidence.
• Deterministic controls govern risk, permissions, and execution.
• Paper-first workflows keep operators in control before capital is deployed.
• Audit trails and observability make every critical action inspectable.

Describe an idea
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Research and generate
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Backtest and validate
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Apply risk controls
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Execute, monitor, and improve

Financial systems should not require blind trust. Open source makes the infrastructure inspectable, deployable, and adaptable to different markets, brokers, models, and operating requirements.

Our engineering principles are straightforward:

• Open by default — inspect the system, extend it, and operate it on your own infrastructure.
• Reproducible by design — keep research inputs, experiments, and results comparable.
• Safe at the boundary — separate AI assistance from deterministic execution controls.
• Observable in production — keep orders, positions, risk, logs, and system health visible.
• Composable at every layer — bring your own data, models, brokers, strategies, and agents.

The core financial operating system: market connectivity, research, strategy runtime, backtesting, AI workflows, risk controls, and execution infrastructure.

Python   Apache-2.0   Self-hosted   Multi-market

The browser workspace for research, strategy development, portfolio operations, and system observability.

Vue   Research workspace   Trading operations

The mobile and lightweight web client for markets, strategies, positions, execution status, and alerts.

Vue   Mobile   Lightweight web

git clone https://github.com/OpenByteInc/QuantDinger.git
cd QuantDinger

Continue with the QuantDinger installation guide, inspect the architecture, and adapt the platform to your own research and execution environment.

We welcome contributions across market and broker integrations, strategy tooling, agent interfaces, infrastructure, security, testing, documentation, and developer experience.

Explore the platform  |  Report an issue  |  Contact support