Testifly is an autonomous QA platform that discovers web app flows, generates end-to-end tests, heals selectors, and reports root causes with video.
What the product does and how it is positioned
Testifly provides an autonomous quality assurance platform designed for web applications. By submitting an application URL, teams can initiate automatic site mapping, scenario discovery, and test suite creation without hand-authoring test scripts or selectors.
The system monitors deployments via CI/CD gates, scheduled runs, and production monitoring. It adapts tests to UI redesigns, provides root cause analysis accompanied by session replays upon failure, and integrates directly with Jira, Linear, Notion, Slack, and MCP servers.
Source-supported ways to use the product
Engineering teams connect their deployment pipelines to run autonomous test suites as a CI/CD gate, intercepting regressions before releases reach production.
Product and QA teams upload technical documents, spreadsheets, or PDF specifications to automatically produce corresponding functional test suites.
Teams configure scheduled runs across multiple environments to catch runtime bugs, UX violations, and workflow breakages in live web applications.
The documented workflow, where available
Users register an account with an email address and password without mandatory credit card verification.
The user inputs the target web application URL, prompting the platform to evaluate accessibility, bot protection, login mechanisms, and application structure.
Teams configure credentials for password-based, social, magic link, or custom login workflows, which are encrypted using AES-256-GCM and stored in Azure Key Vault.
Testifly traverses the target environment to map pages and navigation paths, automatically assembling executable regression and sanity suites.
The platform runs tests on deployment triggers or set schedules, self-heals modified selectors, and pushes root cause diagnostics, video replays, and issue logs to connected workspace tools.
Testifly automates test creation by directly inspecting and traversing target web applications. Rather than requiring developers or QA engineers to write test scripts, define assertions, or manually map selectors, the platform scans pages, features, and user journeys autonomously. It can also ingest contextual requirements by converting uploaded spreadsheets, documents, and PDF files into test suites.
When interface redesigns or underlying behavioral changes occur, the platform automatically adapts existing suites. Instead of failing due to brittle DOM selector modifications, Testifly identifies functional updates, realigns corresponding tests, and repairs broken selectors without human maintenance tickets.
During test execution in staging, production, or CI/CD pipelines, Testifly evaluates functional assertions, UX conventions, and bad practices. When a test run fails, the platform delivers root-cause analysis explaining the underlying failure alongside a synchronized session video replay to assist debugging.
The system interfaces with developer environments through integrations with Jira, Linear, Notion, Slack, and Model Context Protocol (MCP) servers. Security workflows encrypt test credentials twice using project-specific AES-256-GCM keys and Azure Key Vault storage, decrypting values only in memory during login flows.
Checks to run with your own material and workflow
What was checked and when
Answers based on the source-checked product record
Testifly supports deployment in the cloud, on-premises environments, and self-hosted setups behind corporate firewalls.
Testifly supports various login mechanisms, including standard passwords, social logins, magic links, and custom authentication configurations.
Credentials are encrypted twice with project-specific AES-256-GCM and Azure Key Vault, decrypted only in memory during login runs, and never logged.
When a test run fails, Testifly provides an automated root cause analysis detailing why the test failed alongside a recorded session video replay.
Testifly integrates with Jira, Linear, Notion, Slack, and any AI assistant compatible with the Model Context Protocol (MCP).
