Excel-native AI assistant for building and updating public-equity financial models from plain-language prompts using Daloopa data.
Daloopa Scout is an Excel-native AI assistant for public-equity financial modeling. It can build a model from a blank workbook or template, roll a newly reported quarter into an existing model, populate historicals and KPIs, compare companies and answer questions over Daloopa data. Reported values can carry links back to the underlying filing or disclosure. 1 2
AiToolMap did not build or update a live investment model with Scout, compare cells against filings, reproduce Daloopa's benchmark or measure formula/period-placement errors. The fixed 50-source panel found no eligible exact-product independent rating or benchmark. The 8.0 score is therefore a LOW-confidence desk rating and is not rank eligible. 6
Financial-model errors can propagate directly into valuation and investment decisions. Scout's source links, approval step, worksheet guards and Revert function are meaningful controls, but they do not remove the need for analyst review. Teams should verify reported figures against source disclosures, check period alignment and formulas, independently review forecasts and assumptions, and avoid treating vendor claims such as '99% accuracy' as a substitute for their own validation. 3 4
Scout is narrower than a general spreadsheet agent, and that focus is valuable. It combines an LLM workflow with Daloopa's structured financial dataset rather than asking the model to discover every number on the open web. For substantial requests it generates a plan before writing, locks the active sheet while working, and provides a Revert action. Current documentation also clearly states that forecast assumptions remain the user's responsibility and that users should review totals, periods and outputs. 2 3
The trust surface is unusually specific. Daloopa documents that Scout runs inside the existing Office.js add-in sandbox, sends only the workbook context needed for the request to its backend/model provider, currently uses Anthropic Claude, does not train on customer workbook content, retains prompts/responses/referenced workbook context for 14 days, and cannot access local disk or run macros. 4
Scout is constrained to Excel and Daloopa data, does not browse the web or use external connectors, requires Excel to stay open, and does not run on a schedule. Daloopa's own documentation says a full three-statement model can take roughly 70 minutes to a little over two hours, and recommends splitting large jobs because long prompts are more likely to stall. Access depends on a Daloopa subscription and there is no standalone public list price. 5 2
The larger issue is independent validation. Daloopa advertises very high data accuracy and a benchmark lead over other Excel agents, but AiToolMap found no independent reproduction of those Scout-specific claims. G2 currently lists Daloopa with zero reviews. 1 6
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