LLMs Make Spreadsheet Migration Automatic

LLMs matter here because they attack the ugliest part of switching from Excel to a new modeling tool, which is translating a messy, one off spreadsheet into a clean system someone else can trust. Causal already maps live data into its own variables and categories, and its biggest onboarding hurdle has been getting Excel native finance teams to believe their 20 tab model can survive the move. An LLM based importer turns migration from a services project into productized onboarding.

• In practice, importing is hard because legacy finance models are full of brittle cell references, manual tabs, odd naming, and custom logic. Causal built its product around replacing cells with variables and categories, so an importer has to read the old model, infer intent, and remap each line into that structure.
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• This is becoming a category wide AI use case. Equals is using AI to guide users through unfamiliar schemas and generate usable query structures during onboarding. Runway embeds AI into model explanations and workflow assistance. The pattern is AI as glue that removes setup friction, not just a chat box for formulas.
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• The strategic payoff is lower sales friction against both Excel native incumbents and other modern FP&A tools. Vena wins by keeping teams in Excel, while Causal, Equals, and Runway win by promising a better planning workflow. If import gets easy, fewer prospects need to choose between familiar legacy files and a modern product.
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The next phase of the category is likely to be won less by who has the smartest formula copilot, and more by who makes migration feel nearly automatic. Once old spreadsheets can be ingested, cleaned up, and connected to live data with minimal manual rebuilding, modern FP&A tools can move from replacement threat to obvious upgrade.