Calculate your automation ROI.

It uses straight arithmetic on the numbers you enter: hours × employees × hourly cost × 52 weeks, with the build fee and ongoing AI costs subtracted. Industry benchmarks put automation's recovery at 60–80% of repetitive-task time — if you want a conservative estimate, enter about 70% of the hours your team really spends.

Break-even depends entirely on your inputs — how many hours the process takes today and what those hours cost. At the calculator's default inputs — 5 people, 10 hours a week, $35 an hour — the arithmetic lands at week 5; change the inputs and the answer changes. Simple automations like data entry, email routing, and report generation tend to pay back fastest; complex integrations take longer.

Repetitive, rule-based work: data entry, invoice processing, customer email routing, report generation, scheduling, CRM updates, lead qualification, and document extraction. Tasks requiring judgment or creativity stay human-led — automation gives those hours back.

A typical AutomateNexus build starts at a one-time $7,500. After launch, the only recurring cost is the AI model provider — usually $30–$150 a month, paid directly to them. No retainer, no subscription, no per-seat fees. The calculator lets you adjust both numbers to match any quote.

No — small and mid-sized businesses often see the highest ROI, because manual processes are a larger share of their costs. A 10-person team spending 20 hours a week on manual tasks recovers the equivalent of a part-time hire, every week, without adding headcount.

Multiply how often the task runs by how long it takes, then by the loaded hourly cost of the person doing it, over a year. That is the annual cost of the manual version. Compare it to the build price plus model usage plus maintenance. Divide the build by the annual saving to get payback in years. The calculator above does this on your own inputs.

Using the salary figure instead of the loaded cost, which understates the saving. Estimating task time from memory rather than timing it. Ranking by how annoying a task is rather than how often it runs. And never deciding where the returned hours go — unassigned time quietly refills with more of the same work and then nobody can find the benefit.

Hours returned per week, per workflow, and where they were redirected. Runs completed versus runs that needed a human. Time from trigger to completion. Errors caught before they reached a system of record. Dashboards full of tasks processed and uptime percentages look impressive and answer none of those questions.