Use Cases

One runtime, nine jobs.

Karate Agent is an AI-native test runtime. Whatever the job below, the output is the same: ordinary, deterministic Karate tests your CI runs without the agent.

Every job is one POST /api/jobs away, over REST or MCP, from your terminal, your pipeline, or your own AI assistant.

Author a Suite from a Spec

API
OpenAPI in PR out

Point the agent at an OpenAPI spec. It stands up a stateful mock, explores the API, and emits a reviewable Karate suite with coverage measured against the contract. A spec becomes governed tests in an afternoon.

API testing →

Modernize Manual Regression

UI
Evidence per run ~$0 replay

Turn the test cases a manual team executes into deterministic browser checks that run overnight. Every run leaves screenshots, video, and rule verdicts, and testers move up the stack to review evidence instead of clicking through screens.

AI regression testing →

Maintain the Suite You Have

Heal
Human-approved Never silent

Point the agent at the suite you already own. When a schema or the DOM shifts, it re-drives the drifted check and proposes the repair for a human to approve. The recurring cost of automation is maintenance; this is where the hours go.

How healing is governed →

Test Packaged Apps

Vendor
Guidewire Vendor cadence

Guidewire-class platforms are heavily customized and updated on the vendor’s schedule, which is where selector-based tests snap. Display-text locators survive the churn, and captured traffic gives API-level evidence even where customization blocks standard API testing.

Packaged app testing →

Verify Business Rules & Rating

Rules
Executable twin Engine-graded

The agent drafts the rate book as an executable rulebook from your documents; you review a decision table, not code. The engine grades it with no judge in the loop, and the live system is checked against it row by row. A wrong premium is a defect, tied to the rule.

Business rules testing →

Generate Test Data That Knows the Answer

Data
Boundary + pairwise Expected results

Boundary, pairwise, and covering-array decks generated from the rulebook, every row carrying the computed expected result and the requirement it proves. Export as JSON or CSV and run it from Playwright, Postman, or any framework.

Test data generation →

Grade Your AI-Written Tests

Mutation
Black-box No source needed

AI-generated suites reach high coverage and can still assert almost nothing. Mutation testing seeds defects into provider behavior and replays the suite: survivors name the bugs no test would notice, and echo assertions score zero.

API mutation testing →

Prove the Mock Tells the Truth

Contract
One suite, two targets No broker

Run the same functional suite against your mock and your real provider in one session, and get back a measured divergence set, including the finding no schema check can make: both legs green and the responses still differ.

Contract testing →

Embed It in Your Own AI Stack

MCP
karate_eval REST + MCP

Drive the whole runtime from Claude Code, VS Code Copilot, or Cursor over MCP, or wire it into your internal agent platform as the test-engineering engine. Agents generate locally; standard Karate runs deterministically in your CI.

MCP & API docs →

What will you prove?

Every job ends the same way: ordinary Karate tests in your git, deterministic runs in your CI, and evidence a reviewer can open.