J.P. Morgan Visa Mastercard American Express Capital One Wells Fargo Barclays SAP Oracle Salesforce Adobe Dell Technologies IBM Deloitte PwC EY Accenture Walmart Boeing Toyota Nissan Delta Caterpillar Philips BASF Maersk Roche Ford Intuit Cisco Fidelity T-Mobile IKEA Trivago Expedia Guidewire GM Financial Illumina Cytel ING DBS Lowe's Comcast
Govern your AI-built software, end to end.

Generation got cheap. Knowing what’s safe to ship didn’t. Trusted by 76 of the Fortune 500.

One engine for API and UI testing, accelerated by the AI you host.

Write 60% less test code. Any CI. Any LLM you host. Open core, 9.0k ★ on GitHub.

Our reference API, graded on every commit

Governance report
Open the report
NOT READY governance index 39% level Ungoverned

1 error-severity finding stands unwaived. 1 more gate is open. 34 rules ran.

design w .20
96%
security w .20
20%
documentation w .10
75%
proven-ness w .35
34%
contract w .15
75%

2 gates open

  • unwaived-errors1 error-severity finding stands unwaived
  • capped-dimensionsecurity-scheme-declared caps security at 20%. Uncapped it would read 62%.
ruleset sha256:b52324a1… · 34 bundled rules Deterministic. No model produced this.

Verdict

Computed, not guessed

Proven-ness

34% has evidence

Blocker

Named, with the fix

Reproducible

Your CI, your walls

Schedule a Demo

The Problem

Testing is fragmented, slow, and painful

Different tools for API tests, UI tests, mocks, and performance

Verbose code that takes longer to write than the feature itself

Tests that break every time you refactor, slowing your team down

The Karate Way

One tool. Plain syntax. Zero boilerplate.

Unified framework for API, UI, mocks, and performance tests

Readable, concise syntax that anyone on the team can understand

Built-in parallel execution, reporting, and CI/CD integration

The problem, in your language

“All green” is not the same as “proven.”

A passing dashboard reports activity. Your board, your auditors, and your regulators ask for assurance. Those are not the same question.

What the dashboard counts

  • •Endpoints hit, tests passed, percent green
  • •“100% of operations exercised”
  • •A build that went green last night

Activity. It tells you something ran.

What an auditor asks

  • •Which business rule did we actually prove?
  • •Was the senior-driver, high-risk-claim, boundary case exercised, or only claimed?
  • •Where is the evidence, and is it safe to ship?

Assurance. It tells you you’re safe to ship.

When the same AI writes the code and its tests, passing becomes the goal instead of finding the flaw. “100% hit” can still be not ready to ship.

For product owners · author of intent

One rulebook. Two readers. One verdict.

You define “correct” in plain business terms. That one definition becomes the test, the mock, and the evidence an auditor accepts.

Product Owner defines & approves →

Review a decision table, not code

The agent drafts the rule as a decision table, gaps and boundaries surfaced. You approve; it goes to version control.

The business rule

if driverAge > 70:

seniorFactor + 25%

→ RATE-001

Read as an acceptance criterion by you.
Executed as an oracle by engineering.

→ Developer consumes as-is

One source of truth, two readers

Your engineers run the same rule as an executable oracle and a mock. No second spec, no drift.

The same rule, run by engineering

The oracle

It computes the expected result, so no one hand-codes assertions that drift from what you meant.

The mock

It stands in for a backend that isn’t built yet, so verification doesn’t wait on another team.

Traceability

Every rule carries a requirement ID, so coverage traces to the requirement you signed off.

AI proposes. Deterministic verification decides. The agent explores the system, finds scenarios no one covered, and drafts candidate rules in plain language. Then a deterministic check grades every claim against the rule you approved, with no model in the path and nothing to second-guess.

The bottom line for a product owner

READY CONDITIONAL NOT-READY

Is it safe to ship?
Computed, not guessed.

Every release gets a verdict against your business rules, blockers named, evidence attached. No model in the path.

Proof, not a promise

We publish our own failing grade.

Our reference API, graded by our own tooling, in public, on every commit. No login, no demo request.

Deterministic. No model produced any of it, so anyone can re-derive it. How it is computed.

Open core · the engine

Every kind of test, one framework.

Under all three pillars is the open-source engine teams already trust: API, UI, mocks, and performance in one syntax.

API Testing

+ AI authoring

REST, GraphQL and SOAP with JSON/XML assertions, schema validation and data-driven scenarios. Karate Agent authors tests from natural language, MCP or your IDE.

Write REST, GraphQL & SOAP in one syntax

API Mocks & Contract Testing

Mocks in the same syntax as your tests. Stateful, thread-safe, 100% local. Run one suite against mock and provider; see where they disagree.

UI Automation

+ AI recovery

Browsers and desktop apps in readable commands. Karate Agent recovers when locators drift, so tests survive UI refactors.

Automate UI without CSS selectors

Performance Testing

Re-use your API tests as performance tests: thousands of concurrent requests, Gatling built in.

Re-use API tests as load tests

See the Difference

Write 60% less test code

Traditional (RestAssured): 25 lines
import io.restassured.RestAssured;
import static io.restassured.RestAssured.*;
import static org.hamcrest.Matchers.*;

public class UserTest {
  @Test
  public void testCreateUser() {
    RestAssured.baseURI = "https://api.example.com";

    String body = "{" +
      "\"name\": \"John\"," +
      "\"email\": \"john@test.com\"" +
    "}";

    given()
      .contentType("application/json")
      .body(body)
    .when()
      .post("/users")
    .then()
      .statusCode(201)
      .body("name", equalTo("John"))
      .body("id", notNullValue());
  }
}
With Karate: 8 lines
Feature: User API

Scenario: Create a new user
  Given url 'https://api.example.com/users'
  And request { name: 'John', email: 'john@test.com' }
  When method post
  Then status 201
  And match response.name == 'John'
  And match response.id == '#notnull'

New · AI Test Automation

Karate Agent, the AI-native test workspace, built into the platform.

An LLM-powered agent that drives the browser, recovers when UIs drift, and authors tests in plain English. Display-text locators, BYO LLM (Claude, GPT, Gemini, Llama, Ollama), 100% self-hosted, and MCP-native for Claude Code and VS Code Copilot.

~30s

Scripted flow runtime

72×

Fewer page scans

0

Tokens on scripted paths

80%

Faster test authoring

60%

Less code vs alternatives

10x

Faster with parallel execution

Recognized by analysts, reviewers & developers

Enterprise Ready

Built for scale. Designed for teams.

Enterprise-grade security and support for test automation at scale.

Single-tenant by design

One isolated instance per team, behind your firewall. No shared identity store, no multi-tenant attack surface.

Role-Based Access

Fine-grained permissions for teams, projects, and environments.

Audit Logs

Complete visibility into who did what, when. Export-ready for compliance.

Local-First by Design

Self-hosted end-to-end. No SaaS dependency, no telemetry, no outbound calls. Your data never leaves your network.

Dedicated Support

Named account manager, SLA-backed response times, and onboarding assistance.

Self-Hosted Option

Deploy in your own cloud or on-premise. Your data never leaves your infrastructure.

What Teams Are Saying

Loved by developers. Trusted by enterprises.

“Ease of setup, ease of writing tests even for juniors, and the fact that it uses Gherkin allows everyone to understand the tests.”

LK

Lina K.

Head of QA · Capterra verified

“Well documented and well supported. The DSL is so simple to learn. Offers a full range of automation capabilities: client-side assertions, server-side mocks and simulators, even performance testing.”

AS

Anthony S.

Team Lead / Principal Engineer · Capterra verified

“An excellent tool in all sense. Used it for both API and UI automation. Found it amazing with parallel execution, negligible flakiness, and code-less automation.”

KJ

Kanishka J.

QA Automation Lead · Capterra verified

Questions

The things people ask first

Is Karate a cloud service?

No. Everything runs on your machines and your CI. No hosted tier, no telemetry. Karate runs air-gapped in banks, insurers and healthcare.

What does Karate test?

APIs (REST, GraphQL, SOAP, gRPC, Kafka, WebSocket), browser and desktop UI, performance and mocking. One file drives functional, load and contract tests.

How is this different from a passing test suite?

A passing suite reports activity, not which rule was proved or whether only your mock answered. Karate joins evidence to requirements and computes a verdict, blockers named.

Is any of the scoring done by an AI model?

No. Verdicts are deterministic: no model, no network, no guess. Same inputs, same result. AI helps author tests, never decides whether one passed.

Can we use our own LLM?

Yes. Bring your own model, including self-hosted via Ollama, so nothing leaves your perimeter. Model choice is config, not a different product.

Do we have to replace the tests we already have?

No. Teams adopt incrementally: new tests in Karate, existing suites carry on. The platform layers governance and coverage on top of what you have.

Get Started

Start where it suits you.

Open source. Community driven.

Join thousands of developers who contribute to and rely on Karate every day. Star us on GitHub, submit a PR, or just say hello.

8,800+

GitHub Stars

350+

Contributors

2M+

Downloads

See Karate in action.

Unified API, UI, and AI test automation: open source, self-hosted, enterprise-ready. Get a guided walkthrough from our team.

76 Fortune 500 650+ companies
Schedule a Demo

Enterprise Platform

Audit logs, offline licensing, and dedicated support. 100% local. Your data never leaves your infrastructure.

Air-gap ready Self-hosted
Contact Us Schedule a Demo