## Deterministic execution, rendered across your entire browser matrix

Orchestrate suites across your pipeline, let self-healing locators absorb the small changes, and run at scale without standing up your own infrastructure.

## No flaky runs

Tests render from a captured DOM snapshot instead of holding open a live connection, so results don't depend on network timing or race conditions.

## No local grids

Run cross-browser and cross-device coverage from the cloud instead of standing up and maintaining your own device farm.

## No manual locator fixes

When an element's underlying code changes, Applitools finds it using visual and semantic clues, so a UI update doesn't mean a broken test.

## Every result traces back to the same deterministic core

AI coding assistants can refactor a UI in minutes and push changes faster than any release calendar used to allow. Whatever gets orchestrated, healed, or rendered, execution runs on the same Deterministic Language Model and Visual AI, so a red build stays meaningful no matter how fast the code underneath it is moving.

DETERMINISTIC EXECUTION

## Get the same result for every run

**Coded logic, not a black box** Execution runs on a Deterministic Language Model that computes each step from rules, not statistical guesses, so a failure is a real bug and not a different roll of the dice.

**No thinking cycles at runtime** Because the model isn't reasoning through each step live, execution runs faster and the cost stays predictable as your suite grows.

**A signal you can act on** A red build means the UI broke. A green build means it didn't. Nothing in between.

TEST ORCHESTRATION

## Combine, schedule, and run tests your way

**Suites built around how you release** Group tests into suites that match your release process, whether that's a nightly run, a pre-release gate, or a check on every pull request.

**Scheduled runs for standing coverage** Set tests to run on a recurring schedule so regressions surface between releases, not just during them.

**Triggered from your pipeline** Call test suites through the API from your CI/CD process, so orchestration keeps pace as AI-assisted commits push more changes through the pipeline than a person-paced release ever did.

SELF-HEALING TESTS

## Keep tests running when the code underneath changes

**Finds elements without exact locators** When a class, ID, or attribute changes, Applitools uses visual and semantic clues to find the same element instead of failing outright.

**Holds up against AI-driven refactors** When an AI coding assistant renames a class or restructures a component, Applitools finds the same element instead of failing on an identifier that no longer matches.

**Less time on locator upkeep** Spend engineering time writing new tests, not rewriting old ones every time the DOM shifts.

Visual AI

## Validate what a user actually sees

**One checkpoint replaces pages of assertions** Add the Eyes SDK and a single visual checkpoint validates the full page or component in place of hundreds of lines of DOM assertions.

**Built to ignore rendering noise** Visual AI is trained to catch real regressions while ignoring anti-aliasing and other rendering noise that a user would never notice.

**Catches what functional tests miss** Functional checks confirm the code ran. Visual AI confirms the interface still looks right, catching layout and rendering issues before a user does.

cross-browser/device testing

## Render every browser and device without the wait

**Run once, render everywhere** The Ultrafast Grid takes a single local test run and renders it across every browser, device, and viewport you need, instead of re-running your suite on each one.

**No live connection required** Rendering runs from a DOM snapshot instead of an open connection to a remote browser, removing a common source of flaky runs.

**No separate infrastructure to manage** Skip the reverse proxy, VPN, or self-hosted grid that traditional cross-browser tools depend on.

## Why the signal holds up at scale

# 1

## Reproducible by design

Every run computes results with a Deterministic Language Model, not a general-purpose LLM. The same input produces the same steps and the same result, no matter how many times it runs.

# 2

## Coverage that scales with your pipeline

Orchestrated suites, self-healing locators, and parallel rendering all run on the same core, so execution keeps pace as your pipeline and your AI-generated code both grow.

# 3

## Built to see like you do

Visual AI ignores anti-aliasing and minor rendering shifts and flags a change only when it would actually look different to a user.

# 4

## Your app data stays yours

Applitools compares screenshots locally within your environment. App data and anything personal on screen is never used for training.

## Run your next suite on infrastructure built to hold up