QA as a service · Manual · AI agents · Automation · Load
Senior QA engineers, AI agents and automation — on every release.
Zenius tests every merge with a proven 316-case library, works your product the way a real user would, rehearses your peak weeks before the date, and signs the go/no-go before you ship. A name attached, not a percentage.
Send us a URL — within five business days you get a map of your critical flows, what we would test, and a first verdict. No slides. Prefer to talk? 20 minutes with the engineer who would sign your releases →
Illustrative release verdict: AI agents generate tests from the pull request, automation runs the 316-case suite, a senior engineer explores the product by hand, a load rehearsal finds the breaking point, and a named engineer signs the go/no-go.
Verdict pending · every failure classified, every fix re-run
Illustrative run. Real verdicts come with logs, traces, video and a named signature.
- 316proven test cases, mapped to your flows
- 7 yrslive on a ticketing platform, incl. World Cup on-sales
- 50%faster PR → validated at SI Tickets
The enterprise problem
You bought a test tool. It generates tests. It doesn't tell you whether to ship.
Developers now ship at AI speed. Test tools generate more tests than ever. What nobody added is the judgment to read the results — and there is no headcount left to apply it. That is the gap Zenius fills: humans, agents and automation in one quality function, with a name on the verdict.
The bottleneck was never writing tests. It's judgment — and there's no headcount left to apply it.
of QA engineers say bug volume has risen since their developers adopted AI
say their own testing workload has grown — none report a single QA hire in response
gave AI-generated code a full trust rating on a five-point scale
organisations still deploy untested code; one in five loses more than $1M a year to poor quality
Sources: DeviQA, State of AI-Generated Code 2026 (300 QA practitioners) · Tricentis, 2026 Quality Transformation Report (2,501 respondents).
What we do
Four disciplines. One quality function.
Automation and AI agents run on every merge. Senior engineers do the work machines structurally cannot. Load rehearsals find the failures only a peak reveals. One named engineer reads all of it and signs.
Does every flow still work, on every release?
Functional, regression, integration and mobile tests run in your pipeline on every merge — not in a phase at the end. A proven case library is mapped to your flows: checkout, inventory, promo codes, payments, refunds, mobile web. Your existing tests stay exactly as they are.
- Coverage from day one — 316 proven cases mapped to your critical flows
- Trends, not last runs — pass rate across every run over time; one green build is not evidence, a stable line is
- Triage, not noise — every failure classified as flaky, environment or genuine defect
- An audit trail — each failure logged to the commit that fixed it and the re-run that verified it
Who writes the tests when developers ship ten to one?
The Zenius agent pulls each pull request, reads the acceptance criteria, generates tests against them from the proven library and runs them for pre-validation — before a human ever looks. Ten developers per QA engineer stops being a crisis and becomes the ratio.
- Tests generated from acceptance criteria, not from guesswork
- AI failure triage — flaky, environment or defect — so a red run tells you whether to call infra or dev
- Every generated test reviewed by a senior engineer before it joins the suite
- Proven at SI Tickets: 50% faster from PR raised to validated
What happens when a human tries to break it on purpose?
Senior engineers work your product the way a confused, impatient or malicious user would — not scripted paths, but the paths real people actually take. This is the layer automation and agents structurally cannot cover, and it only shows up when someone tries to break something deliberately.
- Engineers who have shipped the same system in your sector — nobody learns your problem on your budget
- Every bug verified by a human, with video, traces and logs
- A false positive gets investigated and fixed within 24 hours
- Runs alongside automated coverage as part of Managed QA
Does it hold when everyone arrives at once?
A peak is not a normal day with more people on it. We rehearse it at event scale two to three weeks out — early enough that what it finds can still be fixed before the date your revenue depends on. Proven through World Cup on-sales on a live ticketing platform.
- The failures only load reveals: seat-hold contention, payment-gateway throttling, queue behaviour, cache stampede at the moment the sale opens
- Your breaking point found and documented before every major release — not after your users do
- Standby included: an engineer through the window while the peak runs, not a report delivered and abandoned
Who is accountable for the verdict?
We run the platform for you. A named senior engineer signs the go/no-go before every release goes out — accountable for the verdict, not just the coverage number. Before the release, and before the date your revenue depends on.
- One screen: green, or not green — and why
- The verdict is checkable, not asserted — every failure tied to a fix and a verified re-run
- 24-hour failure triage, ongoing suite maintenance, documented decisions
How it works
Coverage in three weeks. A signature on every release after that.
Every engagement opens with system design and governance, because brittle automation fails quietly and expensively. Scope is fixed, deliverables are named, and a number is attached.
Map the critical flows
We work your product with you, map the flows your revenue depends on, and agree the coverage scope in writing.
- Critical-flow map
- Coverage scope, signed off
- Peak dates on the calendar
Build the suite
The library is mapped to your flows and the agent fills the gaps. A senior engineer reviews every test before it goes live.
- Suite running on every merge
- First coverage number
- Tests in open standards — yours
Run, triage, sign
Suite maintenance, 24-hour failure triage, exploratory sessions, load rehearsals before every peak, and a documented go/no-go every release.
- Trend dashboard, not last-run luck
- Flaky / env / defect on every red
- Named engineer signs the release
No lock-in: the automation, the suite, the pipeline and the evidence stay with your team, exportable at any time — whether or not you keep running it with us.
Two ways to get a Zenius
Find a Zenius. Or hire one.
A Zenius is a senior QA engineer with an AI agent and a proven 316-case library behind them. Run the platform yourself and the agent does the generating and running. Hire a Zenius and a named engineer runs the whole function — and signs every release.
Find a Zenius
Run the platform yourself. The Zenius agent generates and runs your tests on every merge.
- Connect your repository — the agent maps your critical flows
- Tests generated from the 316-case library and your acceptance criteria
- Runs on every merge, scheduled runs, flaky and release reports
- Pass-rate trends, failure drill-down and AI triage — flaky, environment or defect
- Your existing tests stay exactly as they are; everything stays in open standards
First run free. Enterprise tier unlocks the full suite and scheduled coverage.
Start with a free runHire a Zenius
We own your testing. You own shipping. A named senior engineer runs the platform for you and signs the go/no-go.
- Everything in the platform, run and maintained for you
- Exploratory testing by engineers who have shipped your kind of system
- Load rehearsal at event scale two to three weeks out, with an engineer on standby through the peak
- Every bug verified with video, traces and logs; false positives fixed within 24 hours
- A documented go/no-go, signed by name, before every release
Priced per test under management — creation, infrastructure, maintenance, triage and reporting included. Performance validation is a separate line item.
Get a free coverage mapBoth run on the same platform. Start with Find a Zenius, and move to Hire a Zenius the day you want a name on the release — the suite, the trends and the evidence come with you.
Where this runs
Seven shapes of the same peak.
Different products, the same failure modes under load and speed. Pick your shape to see what we cover.
Ticketing & Events · 7 years live
The hardest peak there is.
On-sales open at a known minute and everyone arrives at once. Seat and inventory holds, queue fairness, promo codes, payment retries, refunds. Proven through World Cup on-sales on a live platform.
What we cover
- Seat and inventory holds under concurrent demand
- Queue fairness at the moment the sale opens
- Promo code redemption at volume
- Payment retries and gateway throttling
- Refund and cancellation flows post-sale
How each discipline runs
- Automation keeps checkout, promo codes and refunds verified on every release
- Engineers work the on-sale like a frustrated fan — double-booking a seat, abandoning at payment, retrying a promo
- Full on-sale rehearsal at expected concurrency, two to three weeks out
- A named engineer signs the go/no-go before every on-sale
Travel & Booking · near-adjacent
Fare rules, currencies and the season-launch spike.
OTAs, tour operators, hotel and villa booking. Fare rules, multi-currency, date pickers, cancellation windows — and the campaign spikes that hit third-party inventory and rate lookups hardest.
What we cover
- Fare combinations and cancellation policies across currencies
- Date-picker logic and cancellation windows
- Third-party inventory and rate lookups under a campaign spike
How each discipline runs
- Fare and cancellation rules verified on every merge, so pricing errors never reach a customer
- Engineers probe fare-rule edge cases the way a confused traveller actually would
- Campaign and season-launch spikes rehearsed before the date
- A named engineer reviews fare-rule and spike results before the seasonal push
Flash Sales & Reservations
Prove the stock count survives a stampede.
Flash-sale commerce, restaurant and appointment booking. Stock accuracy, slot contention, checkout under a stampede — not just whether the page stays up.
What we cover
- Stock accuracy and overselling under concurrent buyers
- Slot contention — the same slot from many tabs the instant a drop opens
- Checkout integrity under a stampede
How each discipline runs
- Stock and slot logic validated continuously, so overselling is caught in development
- Engineers hammer the same slot from multiple tabs the way real buyers do
- A concurrency run that proves the stock count survives, not just that the page stays up
- A named engineer signs off on stock-and-slot integrity before a drop
E-commerce Checkout
Cart to payment on a platform that never fully closes.
Inventory sync, discount stacking, gateway failover, tax validation — and the ad-spike and campaign-day traffic that lands on checkout and the payment gateway.
What we cover
- Inventory synchronisation and discount stacking
- Payment gateway failover and tax validation
- Checkout and gateway behaviour on campaign day
How each discipline runs
- Inventory sync, discount stacking and gateway failover verified on every merge
- Engineers work carts like real shoppers — stacking discounts, switching payment methods mid-checkout, abandoning and returning
- Ad-spike and campaign-day traffic rehearsed against checkout and the gateways before the sale goes live
- A named engineer reviews checkout and gateway results before every campaign
Fintech & Payments · high stakes
Nothing silently miscounted.
Money movement, ledgers, reconciliation, KYC flows. Idempotency, double-entry integrity, settlement timeouts — proved under concurrent writes, not just under a timer.
What we cover
- Idempotency and ledger integrity on every money-movement change
- KYC and settlement flows — partial failures, retried requests, ambiguous states
- Reconciliation evidence before release
How each discipline runs
- Idempotency and ledger-integrity checks run on every change before it reaches production
- Engineers probe KYC and settlement edge cases a script won't think to try
- Concurrent-write load against the ledger to prove nothing is silently miscounted
- A named engineer signs off on ledger and reconciliation evidence
Marketplaces · two-sided
Both sides of the transaction, tested together.
Buyer and seller flows that depend on each other. Listing sync, bidding windows, payout timing, dispute logic — so a failure under load doesn't surface as a trust problem days later.
What we cover
- Listing sync and bidding windows
- Payout timing and dispute logic
- Cross-side breakage when one side changes
How each discipline runs
- Buyer and seller workflows tested together on every merge
- Engineers work both sides at once, the way a dispute actually unfolds
- Both sides load-tested together so payout or listing-sync failures show up here, not in support tickets
- A named engineer reviews evidence from both sides of the transaction
SaaS Platforms · general shape
Every release touches surface area nobody remembers exists.
Multi-tenant workflows, permission boundaries, integrations, background jobs. The whole quality function, run at your release cadence.
What we cover
- Multi-tenant isolation and permission boundaries
- Integrations and background-job behaviour
- Backlog and retry behaviour on job queues
How each discipline runs
- Tenant isolation and permission boundaries validated at every shipping cadence
- Engineers push permission boundaries the way a curious admin or a malicious tenant would
- Load scoped to the releases and integrations that matter, rehearsing queue backlog and retries
- A named engineer runs the whole function at your release cadence
Don't see your shape? The pattern still applies — tell us what breaks under load and we'll map it
Proof
Production evidence, not pitch decks.
Every claim points at something running — logs, users, a reference who relied on it. Hours returned, errors removed, revenue protected. If we can't name the number, we haven't finished.
Case study · SI Tickets · Ticketing
QA absorbed AI-speed development without adding a single person.
A ticketing marketplace running ten developers to every QA engineer, with on-sales — including World Cup matches — where everyone arrives at once.
Median time from pull request opened to QA-verified, measured eight weeks before versus after. Same release cadence. Escaped defects flat.
Years of engineering experience
Test cases in the proven library
Industries served
Regions — US, Europe, India, UAE
Why Zenius
We've already shipped what you're about to build.
Built on India's largest practitioner-led enterprise AI study — 100+ AI practitioners and 40 enterprise leaders interviewed — and seven years of running QA for products that live and die on a peak.
Senior people, not a bench
The engineers on your build have shipped the same systems in production, in your sector. Nobody learns your problem on your budget.
Architecture first
Every engagement opens with system design and governance, because brittle automation fails quietly and expensively.
Outcome-based scoping
Fixed scope with named deliverables and a number attached — not open-ended hourly billing.
Cost-efficient delivery
An India-based model with real overlap on US hours — enterprise rigour at a lower blended rate, across the US, Europe, India and the UAE.
Built to pass your internal approval
Everyone who has to say yes, answered.
Outsourcing quality goes through engineering, finance, procurement, security, legal and the CEO before anyone signs. Each of them gets their own page — forward the one they need.
"Why can't we just buy a tool?"
The judgment gap, how we run inside your pipeline, what we never touch, and the FAQ your tech lead will ask.
For engineering Finance & CFO"What does this actually save?"
An ROI calculator with editable assumptions: in-house cost, regression hours, escaped defects and peak-day risk versus a $60K–$250K engagement.
Open the calculator Procurement"How do they compare?"
Zenius next to QA Wolf, Rainforest QA and Testlio on model, scope, pricing and lock-in — plus entity, terms and documents.
See the comparison Security & legal"Where does our data go?"
How we handle code, environments and evidence; the standards we benchmark against; DPA, sub-processors and the questionnaire turnaround.
Security & trust CEO & founders"Is our brand safe with them?"
Who we work with, what a failed peak costs, and why a named engineer signing every release is the accountability you are buying.
For leadership RFP & vendor onboarding"Send us the vendor pack."
Legal entity, offices, capabilities, SLAs, security summary and contract documents on one printable page.
RFP & vendor packGet started
Start with a paid 3-week pilot on one product area.
You get a coverage number and a performance report whether or not you continue. If we miss the agreed coverage date, that month is credited.
- A critical-flow map and a coverage number for one product area
- A suite running on every merge — yours, in open standards
- A performance report with your breaking point documented
- A named engineer's go/no-go on your next release
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