Enter your team's numbers. See exactly what Appium maintenance
costs — and what switching to Drizz Vision AI saves.
Four inputs. Real-time math. See your numbers in productivity, hours and dollars — Year 1, no projections.
Authoring + maintenance + tokens
Authoring + execution tokens
Return on Drizz token investment
Share of team capacity reclaimed
Your team's exact productivity numbers + benchmarks from 3 teams like yours. Formatted for forwarding straight to your VP or engineering lead.
8,150 SDET-hours is roughly 4 full engineers worth of work. Here's what teams typically build with that capacity in Year 1 once Drizz removes the maintenance tax.
Get iOS and Android suites to feature-equivalence — the project everyone keeps deprioritizing.
WCAG 2.2 AA audits, screen-reader paths, contrast and motion verification — finally.
App launch time, scroll FPS, memory usage, cold-start benchmarks per release.
Numbers below reflect default inputs — adjust the calculator above for your team's exact figures.
Year 1 engineering productivity gain — share of team capacity reclaimed from Appium maintenance
Per SDET per release still spent on Appium fixes and flaky triage — even with Claude assisting
Total Year 1 dollar savings at default team settings
For the skeptics: every constant disclosed, formulas reproducible in a spreadsheet.
For a team with 1,000 scripts, 10 SDETs, and 8 releases/month using Claude to assist Appium, total testing-time consumed is approximately 8,650 SDET-hours per year — 1,750 on authoring (Claude cuts this in half), 3,840 on selector break-fixes (Claude cuts ~20%), and 3,060 on flaky triage (Claude cuts ~15%). That's about 7.2 hours per engineer per release on maintenance alone. Drizz reduces total testing-time to 500 hours, reclaiming ~41% of total team capacity.
Year 1 ROI is 1.4x at default settings — every $1 spent on Drizz replaces $1.40 of Claude + Appium cost. Year 1 dollar savings: ~$72,000 (Claude+Appium $260K vs Drizz $188K). The more meaningful number is engineering productivity: 8,150 SDET-hours reclaimed = 41% of total team capacity, or 4.1 full-time engineers freed up to work on coverage, new features, or backlog instead of selector break-fixes.
Authoring one Appium test averages 3–4 hours including debugging. The same test in Drizz takes 20–30 minutes, written in plain English. For 1,000 scripts: 3,500 hrs vs 500 hrs. Drizz tests can be authored by non-SDET QA analysts, cutting the hourly cost significantly.
Authoring one Appium test with Claude's assistance takes approximately 1.75 hours (down from 3.5 hrs raw). The same test in Drizz takes 30 minutes, written in plain English — still ~3.5x faster than Claude + Appium. For a 1,000-script suite, that's 1,750 SDET-hours versus 500 hours. Drizz tests can also be authored by non-SDET QA analysts since no selector or code knowledge is required.
Flakiness moves the ROI ratio the most — a team with 30% flakiness sees ~1.9x Year 1 ROI; one with 5% sees closer to 1.05x. Release frequency cuts the other way: teams running 1–3 releases/month see ROI above 2x; teams running 12+ releases/month see ROI closer to 1.3x. Script count and team size scale both sides proportionally — they change absolute hours, dollars, and productivity % gained but not the ratio.
Two options: (1) Email yourself the custom 1-page report using the form above — it's formatted for forwarding, with your inputs, output numbers, and a short narrative your VP can read in 90 seconds. (2) Book a 30-min walkthrough and we'll send a tailored deck after the call, including benchmarks against teams like yours (Porter, Tata 1mg, Dashverse). The report alone usually starts the conversation; the walkthrough closes it.
Critical-path suite of 100–200 scripts: typically 2–3 weeks. Full migration of 1,000+ scripts: 6–10 weeks. Because Drizz tests are plain English, a non-SDET QA analyst can lead the migration with SDET oversight on test-design decisions. Drizz provides onboarding support at no additional cost.
