reversa-pricing-estimate

Feature pricing for legacy software is estimated by generating parallel ranges for effort, value, and market scenarios. This approach uses documented deterministic formulas alongside customer billing profiles to produce explainable pricing ranges instead of guessing.

Value-based pricing is calculated by running a mini-interview to gather specific value inputs from the client. This data is then combined with feature sizing to generate a pricing range that reflects the perceived value.

Market benchmarks derive pricing ranges by referencing a country and seniority benchmark table. If specific benchmark inputs are missing, the calculation applies explicit fallback behavior to ensure a usable market pricing estimate.

Yes, you must run the pricing profile and feature size prerequisites beforehand. Estimating an active feature requires reading an existing customer billing profile and feature sizing state to produce valid calculations.

Yes, pricing estimates are persisted to both estimate.md and estimate.json files. The output strictly follows a provided JSON schema to ensure deterministic calculation results are machine-readable and structurally validated.

Effort estimation requires deterministic formulas to satisfy determinism and provide strong guardrails during proposal generation. This ensures the calculated pricing scenarios are explainable, repeatable, and based on documented offline logic.