revenue-modeler

SaaS revenue projections with bear, base, and bull scenarios are generated by extracting tier ACVs, fiscal year, and currency from pricing-model.md, product-overview.md, and company-profile.md to calculate bottom-up ARR using new-logo rates, expansion, and churn.

Building a bottom-up ARR model for an early-stage SaaS startup requires parsing pricing tiers and product context to calculate monthly and quarterly recurring revenue from new logos, ACV, expansion, and churn, outputting a markdown model with CSV blocks and source citations.

Creating SaaS financial projections with scenario analysis requires pricing-model.md, product-overview.md, and company-profile.md as inputs to extract tier ACVs, fiscal year, and currency for transparent assumption-backed revenue modeling.

Validating SaaS revenue forecasts involves running sanity checks that flag logo ramps against hiring plans, assess tier mix realism, and verify expansion mechanisms to prevent unrealistic forecasts and reduce investor friction.

Scenario analysis in SaaS revenue modeling tags every input with its source, citing pricing-model.md, founder inputs, or illustrative assumptions directly within the markdown output tables to ensure transparent, assumption-backed financial projections.

Automated SaaS revenue modeling should not be used when you lack the required pricing-model.md, product-overview.md, and company-profile.md context files, as the scenario analysis cannot extract tier ACVs or perform sanity checks without them.