Showing 3 open source projects for "workflow management"

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  • 1
    Claude for Financial Services

    Claude for Financial Services

    Reference agents, skills, and data for the financial-services

    Claude for Financial Services is an open-source collection of AI agents, plugins, and workflow templates designed to transform Claude into a specialized assistant for financial services professionals. The project targets domains such as investment banking, equity research, private equity, and wealth management by providing reusable prompts, structured workflows, and domain-specific analytical skills. It supports deployment either as Claude Cowork plugins or through the Claude Managed Agents API, allowing organizations to integrate the same logic into internal systems and automation pipelines. ...
    Downloads: 3 This Week
    Last Update:
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  • 2
    QuantDinger

    QuantDinger

    AI-driven, local-first quantitative trading platform for research

    QuantDinger is a local-first, open-source quantitative trading platform designed to bring AI-assisted analysis, strategy development, backtesting, and live execution into a self-hosted workspace where data and API credentials remain under your control. Unlike cloud-locked quant services, it lets users run the entire trading workflow on their own infrastructure using Docker, with a PostgreSQL database backend, a Python backend API, and a web frontend UI that supports visualization and strategy management. Traders and researchers can develop custom strategies in Python, run historical backtests, analyze performance, and connect to supported exchanges for live trading, making it suitable for equities, crypto, forex, and futures markets in a local environment. ...
    Downloads: 5 This Week
    Last Update:
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  • 3
    Qbot

    Qbot

    AI-powered Quantitative Investment Research Platform

    Qbot is an open source quantitative research and trading platform that provides a full pipeline from data ingestion and strategy development to backtesting, simulation, and (optionally) live trading. It bundles a lightweight GUI client (built with wxPython) and a modular backend so researchers can iterate on strategies, run batch backtests, and validate ideas in a near-real simulated environment that models latency and slippage. The project places special emphasis on AI-driven strategies —...
    Downloads: 40 This Week
    Last Update:
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