New Coding agents can now ask Testomatica what a change will break before they make it. See how

Agentic QA for teams that ship with AI

Your AI writes the code.
Testomatica proves it works.

Every deploy gets tested on its own. Agents explore it like a real user, each bug is proven by replay, and every proven bug turns into a permanent test. You get a go/no-go answer in under an hour, and nobody writes a test script.

  • No test scripts to write
  • No production access
  • Only reproduced bugs reach Jira
Run #1284 · deploy a1f93c · staging LIVE
  1. Preflightsite, access, budgetWAIT
  2. Gate suite0 / 184 checksWAIT
  3. Change analysisreading the diffWAIT
  4. Agents exploring3 personasWAIT
  5. Referee replayclean session, no AIWAIT
  6. Test writtenregression suiteWAIT
Fits the stack you already ship with
  • GitHub
  • Jenkins
  • Jira
  • Playwright
  • SonarQube
  • Grafana
  • Microsoft Teams
  • Claude Code
  • AWS Bedrock
0 minfrom deploy to a go/no-go verdict
0 tokensspent on regression. AI money only goes to finding new things
0×replayed in a clean session before a bug is filed
0things worth testing, mapped and tracked on one coverage map
Two developers working at their desks, code on screen

The verification gap

Writing code got ten times faster.
Checking it didn't.

With Claude Code, Cursor and friends, one person ships what a whole team used to. But every merge can quietly break a price, a checkout or a permission. Nobody has the hours to click through the whole app again, so things slip.

  • Tests never get written. A solid end-to-end test takes hours. The backlog just keeps growing.
  • Red builds get ignored. Flaky tests and noisy AI tools train everyone to stop looking.
  • Fixed bugs come back. Nothing was standing guard the second time.
  • Release day is a gut call. "Did anyone test checkout?" shouldn't be a Slack thread.

See it work

Watch a bug become a test

This is a real finding from our pilot on a live B2B marketplace, step by step.

An agent shops like a real customer

The persona is a rushed shopper on a slow mobile connection. The agent goes for the category page this deploy touched and keeps scrolling. Rules run quietly behind every step.

  • Device, network and account are set in the browser. The agent doesn't play-act them.
  • It's told to report anything odd, not to finish the task.
agent-session · explorer · persona: rushed-shopper / mobile / slow-3g
12:04:11 open  /category/baby-care
12:04:14 read  listing: 27 cards rendered
12:04:19 scroll  batch 2 loaded (+24)
12:04:23 scroll  batch 3 loaded (+24)
12:04:31 scroll  batch 5 loaded, 147 cards
12:04:31 rule  no-duplicates-on-page  VIOLATED
          147 cards, 144 unique products
12:04:33 note  3 items repeat at the page boundary.
         first render shows 27, ajax asks for page 2
         with pageSize=24, so offset 24 overlaps.

What changes on Monday

Everything you can stop doing

Testomatica takes the repetitive, hard-to-staff part of QA off your plate. Your team keeps the decisions.

The job Without Testomatica With Testomatica
Regression testing a releaseSomeone clicks through the app for a day or twoRuns on every deploy by itself, verdict in under an hour
Writing end-to-end testsHours per test, so the backlog never shrinksWritten for you from bugs that were actually proven
Triaging test failuresMornings spent on "is this red build real?"Only reproduced bugs reach Jira, with a repro attached
Knowing what's coveredA feeling, or a line-coverage numberA map of 240 items with the gaps listed by name
Old bugs coming backFound again by a customerBlocked by the test that was written the first time
The release decisionA gut call in a Slack threadA go/no-go recommendation, with the evidence behind it
Keeping AI costs saneEvery run pays for the model againRegression costs zero tokens, and spend drops every release

How it fits your day

You merge. It does the rest.

There's no pipeline to babysit and no new tool to open. You'll see Testomatica in the places you already work.

  1. 09:12
    You merge a PR

    A change to how category pages load more products.

  2. 09:14
    Deploy detected

    A new build on staging. Preflight checks pass and the run starts.

  3. 09:21
    Gate passes, agents go

    184 checks are green. The diff points the agents at the listing pages.

  4. 09:43
    Bug proven and filed

    Duplicate products on scroll, reproduced 3/3. The Jira ticket is linked to your PR.

  5. 10:20
    You push the fix

    The new test fails before your fix and passes after it. The ticket closes itself.

  6. 10:31
    Go for release

    The verdict lands in Teams. The new test guards that bug from now on.

Two engineers reviewing code together on a monitor
QA-2291 closed · test promoted

Savings calculator

How much time would you get back?

Move the sliders to match your team. The numbers update as you go.

Hours back every month 0
Value per month$0
Releases with a verdict0
Engineer-weeks per year0

This is an estimate. It assumes Testomatica takes over about 80% of repeat manual checks and 70% of test writing and upkeep. Your numbers will differ.

Get these hours back

The platform

Everything a senior QA team does, on every deploy

01

Change-aware testing

It reads the diff and your tickets, finds which pages, APIs and rules the change touches, and tests those first and hardest.

02

Agents with personas

A rushed shopper, a slow 3G phone, a search crawler. Agents explore the way real people use your product, not the happy path.

03

Evidence on every run

Screenshots, Playwright traces, console and network logs, passed or failed. You can replay any run step by step later.

04

Confidence-based routing

High-confidence bugs go straight to Jira. Borderline ones wait in an approval queue, and noise stays on the dashboard.

05

A release gate

Your production deploy asks Testomatica first: go, stop, or a human decides. If it can't answer, it never lets a release slip through by default.

06

Code, agents and people together

Code blocks the release. Agents explore. People sign off. Anything a person or agent finds becomes code whenever it can.

Built for vibe coding

Your coding agent asks before it breaks things

Testomatica comes with an MCP server. Before Claude Code or Cursor edits a file, it can ask what that change will affect, which business rules apply and which tests to run. You prevent mistakes instead of catching them later.

  • An impact graph built from your code: files to services to pages to rules
  • Business rules written down once, in a form agents can check
  • The same answer goes on the PR as a comment
claude-code · mcp: testomatica
> I'm about to change ProductService.cs. What could break?

testomatica.impact("src/Services/ProductService.cs")

path  ProductLoadAllPaged.sql → ProductService
      → CatalogModelFactory → CatalogController

affected pages   Category · Search · Product page
business rules   price sort holds · no duplicates
                 card price = product page price
run first        12 gate tests  (~3 min)
open risk        QA-2291 duplicates on scroll (open)

> Got it. I'll keep the page size consistent and run those 12 tests.

Coverage you can point at

Know what you tested. And what you didn't.

Every test lands on a map of your app's surfaces and quality dimensions. The gaps are listed by name, so you decide what's next instead of finding out in production.

From the pilot

Real bugs from our first runs on a live marketplace

We ran these against the staging environment of a multi-vendor B2B marketplace. Every one was reproduced by the referee before it was reported.

Major

Products repeat on scroll

147 cards on screen, only 144 unique products. Three items showed up twice at the page boundary.

Proven 3/3 · caught by a rule
Major

In-stock items priced at 0.00

Ten products showed as in stock at zero price. They also jumped to the top of the "lowest price" sort.

Proven 3/3 · caught by a rule
Major

"Lowest price" sort out of order

The sort used the undiscounted price, so what buyers saw was out of order in at least four places.

Proven 3/3 · caught by a rule
Major

Cards silently redirecting home

Some product links sent people back to the homepage with a 302 instead of a 404. Nobody noticed.

Caught by a universal check
Minor

Homepage script errors

A banner initialized twice and threw a JavaScript error. That broke two smoke tests, though users couldn't see it.

Caught by the gate suite
Minor

Broken images

Two images used by the listing pages returned errors on every load.

Proven 3/3 · caught by a rule
$2.60for a full 34-step exploratory session by the agent
5 / 5earlier findings re-proven later with no AI and no cost
78% → 1.5%deploys falsely blocked by flaky tests, with one smart retry
100%of 240 items on the coverage map assigned to code, an agent or a person
A small product team working together on laptops around a table

Who it's for

For people who ship faster than they can test

Startups without a QA team

Get the safety of a dedicated QA function on day one, plus a release verdict on every deploy.

AI-first engineering teams

When agents write half the code, let agents help check it, with proof instead of guesswork.

Solo builders and indie hackers

Ship side projects on a Friday knowing something tireless is watching every change.

Engineering leaders

One honest picture of quality: coverage, open risks, flaky tests and cost, trending release over release.

Safe by design

Powerful, but never reckless

No production access

It works on your test and staging environments. Staging is strictly read-only.

Write endpoints blocked

On staging, every request that could change data is blocked before it leaves the browser.

Personal data stays out

By default only public pages reach the model. Signed-in flows need data masking first.

Hard budget limits

When the AI budget runs out, agents stop and the deterministic tests keep going.

Encrypted secrets

Integration tokens are stored with AES-256-GCM and are never shown again in the UI.

Full audit trail

Every approval, override and setting change is logged with who, when and why.

FAQ

Questions, answered

Something else on your mind? Get in touch and we'll walk you through it on your own app.

Do I need to write or maintain any tests?

No. Testomatica writes regression tests from bugs it has actually found and proven, and it keeps them stable. They're standard Playwright tests in your repo, so you can edit them or run them without us.

Won't an AI tester flood me with false alarms?

That's exactly what the design prevents. The model only suggests. Rules in code decide, and a referee replays every finding in a clean, AI-free session before anything is filed. If it can't be reproduced, you never hear about it.

Does it need access to production?

No. It runs against your test and staging environments, and staging is read-only. Optionally, your production deploy can ask it for a go/no-go before it runs.

How long until it's useful?

The gate suite and universal checks run on the first deploy it sees. Agents and the coverage map get sharper with each release, because what they learn is kept.

What does it cost to run?

Deterministic tests and regression cost no AI tokens. Only exploration uses the model. In our pilot, a full 34-step exploratory session cost about $2.60, and spend per deploy goes down as more turns into code.

What does it integrate with?

GitHub, Jenkins and CodeBuild, Jira, SonarQube, Grafana, Microsoft Teams, Entra ID sign-in, and coding agents over MCP. Results show up on a dashboard and in your tracker.

Early access

Ship on Friday.
Sleep on Friday.

We're onboarding a small group of AI-first teams. Leave your email and we'll set Testomatica up on your app with you.

  • Guided setup on your staging
  • First run on your next deploy
  • No credit card