QuantPilot is organized around two AI workflows: Trading Strategies and Research Projects. Together, they help users move from idea exploration to strategy development without forcing both kinds of work into the same flow.
Why QuantPilot has two workflows
The product separates strategy creation from research so users can stay focused on the kind of work they are doing.
Trading Strategies is for building and iterating on executable strategy logic.
Research Projects is for investigating markets, testing ideas, and gathering evidence before strategy work begins.
Each workflow has its own saved chats, workspace defaults, and supporting tabs.
Trading Strategies
Use this workflow when you want to:
turn an idea into strategy logic
work directly with QuantScript
validate and save strategy changes
manage versions and review diffs
Choose Trading Strategies when the main goal is to create, refine, or maintain strategy behavior.
Research Projects
Use this workflow when you want to:
explore a market question or thesis
connect AI to data tools
investigate evidence before writing strategy logic
keep research work separate from execution-oriented strategy iteration
Choose Research Projects when the main goal is to learn, evaluate, compare, or frame ideas before converting them into strategy logic.
How the workflows relate
In practice, many users move between both workflows:
Start in Research Projects to investigate a market idea.
Move into Trading Strategies when you are ready to express that idea as strategy logic.
Return to research when you need more evidence, new data, or a different angle.
This separation keeps research context from getting mixed with strategy implementation details too early.