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§ Private Profile · San Francisco, CA, USA
Executable specifications in English for test automation
testRigor has raised $4.8M across 2 funding rounds.
Key people at testRigor.
testRigor was founded in 2015 by Artem Golubev (Founder) and Enzo Biancato (Founder).
testRigor has raised $4.8M in total across 2 funding rounds.
testRigor is an executable specifications engine to help companies to empower their manual QA to be able to build automation 15X than QA engineers and spend 200X less time maintaining the code.
Key people at testRigor.
testRigor has raised $4.8M across 2 funding rounds. Most recently, it raised $4.1M Seed in August 2021.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Aug 24, 2021 | $4.1M Seed | — | Flashpoint, Phystech Ventures, PTV, Y Combinator | Announced |
| Apr 1, 2020 | $720K Seed | — | AIX Ventures, Shigeru Handa, Egypt Ventures, Flybridge Capital Partners, Founder Collective, NTT Venture Capital, Sunset Ventures, Mark Cuban, Matt Brezina, Nicolas Pinto, Ravi Grover | Announced |
testRigor was founded in 2015 by Artem Golubev (Founder) and Enzo Biancato (Founder).
testRigor has raised $4.8M in total across 2 funding rounds.
testRigor's investors include Flashpoint, Phystech Ventures, PTV, Y Combinator, AIX Ventures, Shigeru Handa, Egypt Ventures, Flybridge Capital Partners, Founder Collective, NTT Venture Capital, Sunset Ventures, Mark Cuban.
testRigor is an AI-driven test automation platform that enables software teams to create executable specifications and end-to-end tests using plain English, eliminating the need for coding skills. It serves agile development teams by automating functional UI, exploratory, regression, and API testing across web, mobile (native and hybrid), and desktop applications. The platform significantly accelerates test creation—up to 50 times faster than Selenium—and reduces test maintenance effort by up to 200 times, especially for rapidly evolving products. This allows teams to increase test coverage efficiently while spending less time on upkeep, ultimately improving software quality and delivery speed[1][2][3].
testRigor was founded to address the complexity and high maintenance costs of traditional test automation tools that require coding expertise. While specific founding details are not publicly detailed, the company evolved to focus on making test automation accessible to non-technical users by leveraging generative AI and natural language processing. This approach emerged from the need to reduce the manual overhead in QA teams and to create ultra-stable tests that adapt easily to UI changes and new functionalities. Early traction came from agile teams seeking faster test creation and maintenance reduction, validating the platform’s ability to scale automated testing without the typical fragility of locator-based scripts[1][3][5].
testRigor rides the growing trend of AI-powered automation and low-code/no-code tools that democratize software development and testing. As software delivery accelerates with agile and DevOps practices, the demand for scalable, maintainable, and fast test automation grows. testRigor’s timing is critical as teams struggle with the complexity and fragility of traditional automation frameworks. By enabling non-developers to contribute to test automation and reducing maintenance overhead, testRigor helps organizations increase test coverage and quality assurance velocity. This influence extends to the broader ecosystem by pushing the industry toward more user-friendly, AI-enhanced testing solutions that align with continuous delivery and digital transformation initiatives[1][2][3][7].
Looking ahead, testRigor is well-positioned to expand its AI capabilities, further automating test generation and maintenance while enhancing integrations with popular development and CI/CD tools. Trends such as increased adoption of AI in software engineering, growing complexity of applications, and the need for faster release cycles will continue to drive demand for platforms like testRigor. Its influence may grow beyond QA teams to include product managers and business analysts who can directly author executable specifications in plain English, bridging the gap between requirements and automated testing. This evolution could redefine how organizations approach quality assurance, making it more collaborative, efficient, and aligned with user behavior insights[1][3][8].