Build cost
Design, data, integration, evaluation, security, and launch.
Free Tools / Cost & Savings
Find the conversion or retention lift an AI feature needs to repay build, inference, and maintenance cost.
Gross-margin-adjusted payback
Enter current economics, implementation cost, and expected lift before seeing the result.
Design, data, integration, evaluation, security, and launch.
Inference, observability, support, maintenance, and model changes.
Conversion, retention, expansion, or operational saving with attribution.
Gross contribution must recover investment inside an acceptable horizon.
Score candidate AI features by ROI, effort, and risk before you build.
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It adds expected conversion-driven revenue and churn-reduction revenue, then applies gross margin before comparing benefit with build, inference, and maintenance costs.
Revenue is not fully available to repay an investment. Gross margin provides a more defensible approximation of contribution before operating overhead.
It converts the required monthly revenue lift into users at current average revenue per user. It is an equivalent target, not a claim that retention is the only route to value.
No. It assumes the stated lift applies throughout the horizon, which is optimistic for many launches. Model staged adoption separately before approval.
No. The calculator runs in your browser. Framz records only that the verified profile used the tool, not the business metrics.
Framz prototypes AI features against real workflows, quality gates, costs, and measurable adoption outcomes.
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