Home/For finance & CFOs
One fixed line replaces three you can't budget.
Quality today is paid for in three places that never appear on the same spreadsheet: QA headcount you can't hire fast enough, engineering hours lost to manual regression, and the incidents that land on your biggest revenue days. Zenius turns that into one contract between $60K and $250K a year — and takes care of it. Run the numbers below with your own assumptions.
Your situation
Team & cadence
Cost to build the function in-house
Teams that ship at AI speed typically run 1 QA engineer per 6–10 developers. SI Tickets runs 1:10 with Zenius.
US default: Glassdoor 2026 median total pay for a QA automation engineer is $119,000; add ~30% for employer costs, tooling seats and management.
Test-automation SaaS, device cloud, CI minutes, load-testing licences.
What quality costs you today
Hotfix engineering time, support load, customer credits. Use your own incident data if you have it.
Peak-day risk
On-sales, season launches, campaign days, drops.
Revenue that moves to a competitor, is refunded, or is lost to a queue that fails. ITIC 2024: 91% of mid-size and large enterprises put an hour of downtime above $300,000.
Uptime Institute 2026: one in five organisations said their most recent impactful outage cost more than $1M.
Zenius
Managed engagements typically run $60K–$250K a year, priced per test under management. See the bands below.
SI Tickets measured 50% faster from PR opened to QA-verified, same cadence, escaped defects flat.
Assumption — set from your own escaped-defect history after the pilot.
Assumption — a rehearsal two to three weeks out finds the failures only concurrency reveals while they can still be fixed.
Build it in-house vs Zenius
Annual exposure today, and what Zenius removes
Print this page to attach the model to your approval.
Method, formulas and sources
In-house cost = QA engineers needed × fully loaded cost + tooling. Regression time = hours per release × releases per month × 12 × loaded hourly cost. Defect cost = defects per quarter × 4 × cost per defect. Expected peak loss = peaks per year × revenue at risk × probability of an incident. Removed = each exposure line × the reduction you set. Net annual benefit = (in-house cost − Zenius) + removed exposure. ROI = net ÷ Zenius. Payback = Zenius ÷ monthly (in-house cost + removed exposure).
Sources for defaults: Glassdoor, QA Automation Engineer pay, US, 2026 (median total pay $119,000); ITIC 2024 hourly downtime cost survey (91% of mid-size and large enterprises above $300,000/hour); Uptime Institute 2026 (one in five impactful outages above $1M); SI Tickets case (50% faster PR → validated, measured eight weeks before vs after). Everything else is an editable assumption, deliberately conservative.
What the money buys
$60K to $250K a year. We take care of it.
Priced per test under management — creation, infrastructure, maintenance, triage and reporting included. Performance validation is a separate line item. Three typical bands:
One product area, managed
The platform plus a senior engineer owning one critical area — checkout, booking, or the on-sale flow — with automated coverage on every merge and a signed verdict per release.
- Coverage number agreed in week 1
- 24-hour failure triage
- One load rehearsal per year
One product line, every peak
Managed QA across a product line with exploratory sessions each release, a load rehearsal before every peak and an engineer on standby through it.
- Exploratory testing every release
- Rehearsal 2–3 weeks before each peak
- Standby during the window
Multiple product lines
The whole quality function for several products or brands: dedicated named engineers, multiple peaks a year, executive-level reporting and a seat in your release process.
- Dedicated senior engineers
- Quarterly trend review with leadership
- Right-to-audit and custom SLAs
Why the in-house number is usually wrong
Headcount is the visible cost. The invisible ones are larger.
A QA engineer at $155K fully loaded looks cheaper than a $120K contract until you add the three months to hire, the tooling, the manager's time, the developer hours still spent on manual regression because one person can't cover ten, and the one on-sale a year that goes wrong. Zenius prices the outcome, not the seat.