Text2Test is an AI-native software testing platform that generates structured test cases from plain text, design, code, and tickets, then runs them as web tests. It is aimed at teams that want to create and execute coverage from product sources without selector-heavy authoring.
Text2Test is an AI-native software testing platform that turns product intent into executable web tests. It accepts plain text, design, code, and ticket sources through MCP, then generates structured test cases that can be run as plans and inspected step by step when they fail.
The product is built around a five-part workflow: connect sources, generate prioritized tests, mix different step types inside a single test case, run plans on demand or from CI/CD, and drill into failures with inline errors and replay. The site positions this as a way to reduce manual test authoring and keep coverage aligned with changing product sources.
Generate structured, prioritized test cases from plain text requirements without writing selectors or DOM-based steps. The product positions this as stable because the test is tied to product behavior rather than page structure.
Hand a test instruction to an LLM that reads the screen, reasons through the flow, and adapts when the UI changes. This is aimed at flows where fixed scripts are brittle or where the next step depends on what is on screen.
Combine plain-text steps, autopilot, script injection, visual verification, and HTTP requests inside one test case. This lets a single sequence cover UI actions, API state setup, and visual checks.
Bundle tests into plans and run them on demand, on a schedule, in parallel, or from CI/CD. The homepage also shows browser matrix support per plan and the ability to rerun failed tests only.
Inspect failed runs with inline error snippets, screenshots, and video, then drill into the exact step that broke. The site also mentions opening a Jira ticket from a failed step.
Use reusable data sources and HTTP requests across plans and test cases, including uploaded CSV, XLS, JSON, or XML files. The product also lists element tags as a coming-soon capability for stable references.
Use Text2Test Native when a requirement is written in plain language and you want it turned into structured coverage without creating selectors or templates first. This fits teams that keep product intent in tickets or written specs and want a test suite quickly.
Use Autopilot for flows where the next step depends on what is visible on screen, such as branching checkout paths, password resets, or multi-step wizards. The LLM-based flow can reason through changing UI states instead of following a rigid script.
Use mixed sequences when one test needs to combine UI actions, API setup, visual verification, and a scripted step in a single sequence. The source pages show examples of starting with plain text, setting state with an HTTP request, and finishing with another execution mode.
Use plans and directories to organize suites for scheduled runs, parallel execution, or CI/CD triggers. This is suited to teams that want repeatable checks on every push and a single place to review failures.
Use drillable results after a failing run to see the exact step, error snippet, screenshot, and video, then rerun only the failed tests. This supports debugging and handoff to issue tracking, including Jira from the failed step.
Text2Test is an AI-native software testing platform that generates structured test cases from plain text, design, code, and tickets, then runs them as automated web tests.
The source pages show plain-text test creation, but do not specify a required programming language or scripting knowledge for the main workflow. The positioning emphasizes no selectors and no DOM knowledge for Text2Test Native, and plain-text input for Autopilot.
It connects through MCP to sources such as Figma, Jira, GitHub, and OpenAPI, with Claude Design also shown on the homepage; some sources are noted as coming soon.
Text2Test groups test cases into plans and can run them on demand, on a schedule, in parallel, or from CI/CD. Failed runs surface per-test and per-step details, including inline error snippets and drill-down to the broken step.
The pricing page shows paid plans for Starter, Grow, Pro, and Custom. The listed plans include different monthly test-case limits, parallel runs, support response times, and added integrations or onboarding on higher tiers.
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