Your financial model has answers it is not showing you.
Model Maestro does not read your Excel file like a document. It traces the logic inside it. Every formula. Every tab. Every assumption that someone entered as a number rather than built from first principles.
In M&A due diligence, the distinction between a calculated output and a hardcoded guess dressed up to look like one is often the difference between a deal that closes cleanly and one that surfaces a problem six months later.
Standard AI tools read the surface. The risk lives underneath.
Feed a financial model into most AI tools and they see text — the values in cells, the headings, a summary of what is visible. What they cannot see is how a number was derived: whether a revenue projection was hardcoded or built from a formula chain, whether tab 3 reconciles with tab 11, whether the EBITDA figure is real or a plug.
What standard AI sees
What Model Maestro traces scanning…1 plug flagged
Formula auditing at structural depth.
The VectorSheet Framework is the technical foundation of Model Maestro. It treats a financial model the way an experienced analyst would — as a network of logic, not a collection of numbers.
Traces formula dependencies across multiple sheets and tabs.
Identifies hardcoded values in cells that should be formula-driven.
Detects breaks in logical consistency between connected sections.
Compresses large, complex files without losing structural fidelity.
Surfaces the full logic chain behind any output — not just the output itself.
Learn how VSF™ works →What Model Maestro finds that manual review misses.
Entered, not derived.
Revenue projections. Cost assumptions. Working capital figures. Model Maestro flags every instance where a number has been entered directly rather than derived — and shows you where it sits in the logic chain.
Logic across every tab.
A real acquisition model spans 15, 20, sometimes 30 tabs. Model Maestro follows the logic across all of them, mapping dependencies and flagging where the chain breaks.
Compressed, not truncated.
Enterprise-grade Excel files exceed the context window of standard AI tools. The VectorSheet Framework compresses at scale — the model's structure is preserved, not truncated.
Every assumption, traced.
Every flagged item comes with a full trace: where the assumption originated, what it feeds into, and what changes if the number turns out to be wrong.
What this looks like in a real deal.
A PE analyst is reviewing a target's three-statement model ahead of an LOI. The model spans 22 tabs and the revenue projection shows 18% CAGR for the next five years.
It traces the formula chain behind that 18% figure and finds that three of the five revenue line items are hardcoded — not derived from any underlying volume or pricing assumption.
The model looks sophisticated. The assumptions underneath it are not. This is what Model Maestro surfaces — not a summary of what the model says, but the truth of how it was built.
See what your current process is missing.
Use our integrated Diligenz Chatbot to ask high-level questions like “What is the primary driver of this quarter’s growth?” — and get an answer based on traced Excel antecedents.