Independent JayAI project · Not affiliated with Anthropic

04 / Test public value

Make a pilot case you can challenge.

Start with a real workflow, compare the full staff effort before and after assistance, and test whether the capacity returned justifies the operating and implementation costs. The numbers below are illustrative until your team measures them.

Workflow under review

Choose a use case

Select a workflow from the explorer or pick one here.

View use case and pilot questions ↗

Editable assumptions

Describe one repeatable unit of work

Use the same unit for baseline and assisted time. Assisted time must include drafting, checking, corrections, escalation, and sign-off.

Start here: replace the example volume, staff time, and costs with estimates for your workflow. The starting values are identical for every use case.

Work and staff time
Cost to operate and launch

This field starts at zero. Add API cost only if the workflow uses the API; include other route charges above.

Estimate direct API token cost ↗

Illustrative planning estimate — verify every assumption before use

Three-year modeled net capacity value

$2,600

Capacity value proxy after modeled costs, not cash savings

Annual realized capacity150 hours
Annual capacity value proxy$9,000
Annual recurring cost$4,800
One-time implementation$10,000
Three-year capacity ROI11%
Modeled payback29 months
How it is calculated

Time difference × monthly volume × 12 × realization factor = annual capacity hours. Hours × loaded hourly cost = annual capacity value proxy. Three-year net = three years of that value minus three years of recurring cost and one-time implementation.

Pilot evidence

Measure quality alongside time

The use case’s suggested measure and validation questions travel here. Set a baseline, define an acceptable quality threshold, and record what staff had to correct before treating any modeled value as evidence.

Suggested pilot

Choose a representative, bounded workflow with cleared material and a human reviewer.

Measure

Staff time including review; completeness; corrections; service outcome.

Validate before deployment

Data permissions, source quality, accessibility, human approval, and agency policy.

Record what the pilot finds

Use aggregate measures and a human reviewer’s conclusion. These notes do not change the value calculation.

This browser saves the scenario locally. Do not enter protected case details.

Planning interpretation

Time returned is capacity for higher-value work, better service, or backlog reduction. It is not a payroll reduction or an appropriated-dollar saving. “Capacity ROI” divides modeled three-year net capacity value by modeled three-year cost. A positive ratio does not establish that service quality, equity, safety, or eligibility controls are acceptable. The example inputs are invented; replace them with observed baseline and pilot data. Calculations run in your browser; the API cost handoff places the estimate in the URL. Before scaling, record the agency owner, approved use-case inventory entry if applicable, data classification, impact assessment, reviewer sign-off, and monitoring plan under the rules that apply to that agency.

Measurement approach informed by GAO’s AI accountability framework ↗ and NIST’s AI RMF Measure guidance ↗. Neither endorses this estimate.