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QA.tech

Accelerate your development cycle with AI agents that perform end-to-end testing like real users. Catch bugs early and automate QA workflows without scripting.

Paidsoftware testingHiring
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Price not published

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About QA.tech

QA.tech is an AI-powered autonomous testing platform designed to modernize the quality assurance process for software development teams. Unlike traditional scripted testing tools, it uses intelligent agents that navigate applications like actual human users, exploring various paths to identify functional and non-functional issues. The tool aims to solve the bottleneck created when high-speed development teams are held back by manual testing or brittle, time-consuming scripts. By automating end-to-end journeys, it allows teams to maintain high code velocity while ensuring product stability across web and mobile platforms. The core of the platform lies in its agentic approach to testing. Instead of writing rigid code for every interaction, users can describe test scenarios in plain English or let the AI autonomously explore the application. These agents can handle complex workflows, including third-party integrations, email verification, and cross-platform transitions between mobile apps and web interfaces. The system integrates directly into existing development pipelines, providing instant feedback via pull request reviews and detailed logs. It also features exploratory testing capabilities where the AI proactively searches for edge cases and UX inconsistencies that might be missed by standard regression tests. This tool is primarily built for fast-moving engineering teams, CTOs, and product managers who need to scale their testing without linearly increasing their QA headcount. It is particularly effective for SaaS companies, fintechs, and developers using modern web frameworks who require rapid feedback loops in their CI/CD environments. Organizations looking to replace hundreds of manual testing hours or those struggling with flaky traditional E2E tests will find value in this approach. It even supports specialized use cases like video game testing, where the model can learn to perform in-game actions like WASD movement. What distinguishes QA.tech from traditional frameworks like Cypress or Playwright is its significant reduction in maintenance and creation time. Tests can be created in minutes rather than hours, and because the AI reasons about the UI, tests do not break with every minor CSS or HTML change. The platform provides actionable feedback beyond simple pass/fail statuses, identifying UX bugs and non-functional regressions. Furthermore, its SOC 2 compliance and integrations with tools like Slack, GitHub, and Linear ensure it fits into enterprise-grade workflows, offering a level of autonomy that bridges the gap between manual human intuition and automated efficiency.

QA.tech pros & cons

Pros

  • Replaces hundreds of manual testing hours with autonomous AI agents.
  • Cuts test creation and suite run time from hours to approximately five minutes.
  • Maintains a high 95% bug detection rate during automated runs.
  • Eliminates flaky tests by reasoning about the UI instead of relying on fixed selectors.
  • Provides SOC 2 compliance for enterprise-grade security and data handling.

Cons

  • Starter plan is restricted to a single user account.
  • Pull request (PR) testing is not available on the entry-level Starter plan.
  • Pricing is not transparent and requires contacting the sales team for quotes.
  • Data retention for test executions is limited to 30 days on the lowest tier.

QA.tech use cases

  • Engineering leads can automate full regression runs within CI/CD pipelines to ensure new code doesn't break existing features across different markets.
  • CTOs at fast-growing startups can scale testing capacity without hiring additional manual QA staff, saving hundreds of hours per month.
  • Product managers can describe new feature scenarios in plain English to verify user journeys before a major release.
  • Game developers can use specialized AI agents to test in-game mechanics like WASD movement and complex interactive actions.
  • QA engineers can use exploratory testing agents to proactively find UX inconsistencies and bugs outside of standard scripted paths.

QA.tech features

  • ci/cd pipeline integration
  • automated test maintenance
  • detailed console logs
  • cross-platform mobile testing
  • exploratory testing
  • pr review integration
  • end-to-end user journey testing
  • ai testing agents

QA.tech pricing

Is QA.tech free? No, QA.tech doesn't offer a free plan.

Starter

Price varies

  • 1 user
  • Limited parallel test runs
  • Standard model access
  • Unlimited environments
  • Multi-application test flows
  • Exploratory testing
  • 30-day test data retention
  • SOC 2 compliance

Growth

Price varies

  • Up to 5 users
  • Custom parallel test runs
  • PR testing
  • Quicker test runs
  • Coverage reports
  • Test execution performance reports
  • 90-day test data retention
  • Slack, Teams, and email support

Enterprise

Price varies

  • Custom user count
  • Unlimited parallel test runs
  • Fine-tuned model option
  • Custom data retention
  • SLA-backed dedicated support
  • Custom security review
  • Priority reliability engineering
  • Custom contract terms

QA.tech FAQs

How does QA.tech differ from traditional E2E testing tools?

Unlike scripted tools like Cypress, QA.tech uses AI agents that reason about the UI like a human would. This reduces test creation time from hours to minutes and eliminates the flakiness caused by minor code changes.

What platforms and frameworks can be tested?

The tool is compatible with any web framework and supports cross-platform testing including mobile apps, web interfaces, and API calls. It can even handle complex scenarios like WASD movement in video games.

What are test executions in the pricing model?

Test executions are not 1:1 with unit tests; a single execution covers an elaborate test case spanning multiple systems. You can create as many scenarios as needed and pay based on the volume of these full runs.

How does it integrate with developer workflows?

QA.tech integrates directly with GitHub for PR feedback, Slack for notifications, and Linear for bug reporting. It can also be triggered via CI/CD pipelines or monitored with tools like Prometheus.

Does the tool support exploratory testing?

Yes, the AI agents can explore your product beyond specific instructions to identify new test cases. This helps uncover UX bugs and non-functional issues that standard scripts often miss.

Open roles

All AI jobs
QA.tech

Senior Fullstack Engineer

engineeringhybrid Stockholm, SE full-time

Benefits:

  • Competitive salary

  • Comprehensive benefits package

  • Creative and inclusive work environment

  • Flexible working hours

  • Remote work possibility

Experience Requirements:

  • Highly skilled and experienced senior developer

  • Strong background in leading engineering teams

  • Experienced in delivering top-tier software solutions

  • Dived into AI since the early days of ChatGPT

Other Requirements:

  • Ability to work independently and efficiently

  • Passion for exploring and adopting new technologies and APIs

  • Ready to push the boundaries of AI

Responsibilities:

  • Apply AI and ML algorithms to develop innovative solutions

  • Build AI agents that interact with customer platforms

  • Revolutionize the quality assurance process

  • Shape the future of software testing

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QA.tech

Senior AI Engineer

engineeringhybrid Stockholm, SE full-time

Benefits:

  • Competitive salary and benefits

  • Dynamic, inclusive work environment

  • Flexible hours and remote work options

  • Opportunities for growth and impact

Experience Requirements:

  • Experience with NLP, Computer Vision, and Reinforcement Learning

  • Experience working with Large Language Models (LLMs)

Other Requirements:

  • Passion for cutting-edge technologies

  • Ability to drive projects independently

  • Curiosity about AI advancements

Responsibilities:

  • Develop AI systems using NLP, Computer Vision, and Reinforcement Learning

  • Fine-tune Large Language Models to improve precision

  • Apply cutting-edge AI research to revolutionize QA

  • Collaborative problem solving

Show more details

Ratings & reviews

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