80%
Test Coverage from 35%
How a 30-person fintech startup used AI QA agents to more than double test coverage and ship weekly with confidence.
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Stop writing brittle test scripts. AI QA agents run end-to-end browser tests from plain English and self-heal when your app updates.
Automation workflow
from $197/month
A productised n8n workflow for the QA testing job you keep doing by hand — set up, hosted and maintained for you.
Custom AI agent
from $2,000
Built for your systems and rules on Claude and n8n. Live in 2–4 weeks with documentation and a walkthrough; maintenance optional from $99/month.
Real outcomes from real builds — not marketing copy.
Provide the URL to your staging or production environment.
Describe the user flow in text, or record yourself clicking through the application once.
The agent executes the tests on every code push, alerting the dev team in Slack if any flow breaks.
E2E test suites break constantly as the UI evolves. Maintaining selectors and fixing flaky tests consumes QA engineering time.
Describe user journeys in plain English. The AI agent navigates your app in a real browser, validates outcomes, and automatically adapts when selectors or layouts change.
Tools: Reflect, Mabl, QA Wolf
Developers skip writing unit tests due to time pressure. Code ships without coverage, and bugs reach production.
The AI agent analyzes your code, generates meaningful unit tests (not just boilerplate), and covers edge cases like null inputs, boundary values, and error paths.
Tools: CodiumAI, Copilot, Codegen
Functional tests pass but the UI looks broken. CSS changes cascade unpredictably. Manual visual QA doesn't scale across browsers, devices, and screen sizes.
The AI agent captures screenshots across key pages, viewports, and browsers before and after each deployment. It compares images intelligently—ignoring dynamic content like timestamps while flagging genuine visual regressions.
Tools: Percy, Chromatic, Applitools
Developers change code but don't always write regression tests. Existing test suites miss edge cases introduced by new changes, and bugs reach production.
The AI agent analyzes the diff in each PR, identifies affected code paths and dependencies, and generates regression tests targeting the specific areas at risk. Tests run in CI before merge.
Tools: CodiumAI, Mabl, QA Wolf
Testing with production data creates privacy and compliance risks. Manually creating test data is tedious and often unrealistic, leading to bugs that only appear with real-world data patterns.
The AI agent analyzes your production data schema and patterns (without accessing PII), then generates synthetic datasets that mirror real-world distributions, edge cases, and relationships. Data refreshes on demand or on schedule.
Tools: Tonic.ai, Synthetics AI, Faker.js
APIs evolve constantly, and changes often break downstream consumers. Manual API testing focuses on happy paths and misses edge cases—schema changes, removed fields, type changes, and pagination differences slip through. Contract testing is valuable but tedious to set up and maintain, especially across dozens of microservices.
The AI agent reads your API specifications (OpenAPI, GraphQL schema), generates comprehensive contract tests covering all endpoints, parameter combinations, and edge cases, and runs them in CI. When specs change, it automatically updates tests and flags backward-incompatible changes. It also generates consumer-driven contract tests by analyzing actual API usage patterns from logs.
Tools: Pact, Postman, Schemathesis
Tell us your workflow — we'll send a free scope and timeline within 48 hours.
Not quite? Take a look at ai coding agent — the closest neighbour.
Ship software faster with zero regressions. AI Quality Assurance agents autonomously navigate your web app, generate comprehensive end-to-end tests based on plain language, and catch broken links and visual layout bugs before deployment.
Writing Playwright or Cypress tests is slow and brittle. AI QA agents allow you to write tests in plain English ('Log in, add shoes to cart, checkout'). The agent spins up a cloud browser, attempts to follow the instructions, visually verifies the outcome, and even heals the test automatically if your developers change a button's CSS selector.
Unlike a generic chatbot or manual process, an AI QA testing agent runs autonomously and integrates with your existing tools. Gartner projects that by 2026, over 80% of enterprises will have used GenAI APIs or applications.
Pick the path that fits your team and timeline. Most companies start with one and grow into the others.
Wire up a ready platform yourself. Best for hands-on teams comfortable configuring software.
See QA testing toolsWe scope, build, and deploy your agent — integrated with your CRM and tools. Best for teams that want it live in days, not months.
See the ROI and cost before you commit — useful for justifying the decision internally.
Code Review Time Savings CalculatorIf you’d rather DIY, these are the tools we’d reach for. Each lets QA engineers and developers run an AI QA testing agent without writing code.
We may earn a commission when you sign up via our links. How we recommend tools
Calculate how much time and money your engineering team spends on code reviews and how AI can cut it by 60%.
Calculate how much manual testing costs per release and how AI QA agents cut testing time by 75%.
Generate 35+ test cases for your AI agent — happy-path, edge, adversarial, boundary. Download JSON or CSV. Works with Promptfoo, DeepEval, Braintrust.
This is the primary benefit of AI QA. Because it relies on visual understanding and large language models rather than hard-coded XPath selectors, it 'heals' the test and finds the new button automatically.
Tell us your workflow and we'll send a free AI build plan for QA engineers and developers — scope, recommended agents, and a go-live timeline — within 48 hours. No obligation.
Or just email [email protected]