BALANCECHEAT / AI Income Statement Model
Build a P&L forecast you can question.
Bring your own AI to explore the assumptions behind revenue, operating costs and profit. Edit the connected income statement, then review each direct AI change in the model.
Your model · Your AI · You stay in control
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Open the full financial model →Continue with your AI in the full model
This is a focused preview with sample data. Open the full financial model, choose AI, and connect your own provider to analyze or edit your model. Your saved models are unchanged by this preview.
A useful starting prompt
Try this with your provider in the full model:
Explain which assumptions drive EBITDA in Base. Propose a cost plan and ask before changing methods.
Start with the drivers behind profit
An AI-assisted income statement is useful when you need to turn a written operating plan into specific assumptions. Ask your provider to identify revenue growth, staffing costs, gross margin and operating expenses before it proposes edits. BalanceCheat calculates the resulting earnings through the existing model engine.
Use the P&L to separate operating performance from financing and tax effects. Higher EBITDA does not necessarily mean higher net income, and neither measure substitutes for cash.
Review the assumption, follow the result
If your AI changes salary growth, the salary input is a pending review item. Personnel expense, EBIT and taxes recalculate from that input. Those downstream effects do not create a separate queue of approvals. Accept keeps the input; Undo restores it.
Use Simple for a common forecast assumption across years. Switch to Advanced yourself when you need different methods or annual inputs. Ask the AI to explain the method it is proposing.
Bring Your Own AI
Connect a compatible AI client to work with a structured financial model. ChatGPT, Claude and Gemini offer external connections where their product, region and plan allow them. Your own API key remains an advanced option for chat inside BalanceCheat. BalanceCheat provides the calculation engine; your connected AI provides the intelligence.
Your financial model stays stored in your browser. When you use AI, your prompt and the requested model context are sent to your provider. The relay does not retain provider keys. External connections temporarily hold tool requests and results while your browser executes them.