Tailor this page to you
In most teams, 80% of testing effort is execution, not design — and that’s exactly the 80% we cut. Karate lets even non-technical domain experts automate the complex, customized apps — Guidewire, SAP, Salesforce, legacy desktop — that brittle tools never could.
DOM-first, not screenshot-based. A hybrid model where scripted flows run at native speed with zero LLM calls and the model only fires on recovery — fast, deterministic, BYO-LLM, and no maintainer required every sprint.
What changes when you adopt it
Regression replays at ~$0
Learn a flow once; the LLM leaves the loop
Two weeks → two nights
Releases stop waiting on QA
Domain experts automate
Plain English — no coding required
The hard apps become testable
Guidewire, SAP, Salesforce, legacy desktop
Cut the 80% · on your model · inside your network
The business case
Test design is roughly 20% of the effort; execution is the other 80% — where the cost, the delay, and the manual grind live. Even a modest dent is a number the CFO notices.
Once a flow is learned it replays deterministically at ~$0 — no per-run token bill, and no growing roster of contractors maintaining brittle scripts.
Collapse the execution effort that gates every release. Regression that took two weeks compresses toward two nights — so shipping stops waiting on QA.
Your domain experts automate in plain English — no coding. Engineers stop babysitting selectors and move to reviewing evidence.
80% of our effort is execution — and the apps that matter most, like our customized Guidewire rating screens, are the ones we can’t automate.
— What enterprise QA leaders tell us
You feel this when…
80%
of QA effort is execution — the part we automate
~$0
token cost to replay a learned flow in CI
10–50×
fewer tokens than screenshot-based AI agents
Under the hood
Two architectures dominate AI testing, and the choice decides cost, speed, and which models you can run.
Vision-based (screenshot)
DOM-first · Karate Agent
await page.fill('#email-input-v2', 'admin@test.io');
await page.click('button[data-testid="submit-v2"]');
await page.waitForSelector('.dashboard-welcome');
// Ship a UI redesign — this test fails.Scenario: Admin sees the welcome message
* agent { url: 'https://app.example.com/login' }
* agent.do('sign in as admin@test.io / pw')
* agent.verify('dashboard shows "Welcome, admin"')
// Ship the same redesign — this still passes.How we win back the 80%
Describe intent in plain language; the agent writes the flow and recovers when the UI drifts. The maintenance tax that kills automation programs goes away.
Meet Karate AgentValidated flows become deterministic scripts that run nightly in CI at ~$0. Exploration is the exception; cheap replay is the steady state — cost per case falls every week.
AI regression testingPurpose-built for complex, customized enterprise UIs — Guidewire, SAP, Salesforce, legacy desktop — where selector-based tools fail. The hard screens become automatable.
UI automationUse cases
Start narrow and high-value — one painful flow — then expand.
Critical journeys that break every sprint from UI churn — the single highest-ROI place to start.
AcceptanceBusiness stakeholders describe what to verify; product owners read the report, not test code.
Agent-shipped codeWhen Cursor, Claude Code, or Copilot ship a feature, the agent verifies it in the same loop.
Bring your most painful manual suite or your hardest screen. We’ll automate it on your model, inside your environment, and show you the execution effort you get back.