Launch of TreeGress's No-Code QA Platform, Set for August MVP Reveal
Treegress, a deep tech startup based in Sacramento, California, has announced the launch of its Minimum Viable Product (MVP) for no-code QA automation, scheduled for August 2025. This innovative platform is set to transform the way software teams approach quality assurance (QA) by providing an intuitive and AI-driven solution that requires no coding skills.
Co-founded by Anna Karnaukh and Oleg Lola, Treegress is focused on autonomous QA for software teams. The platform is designed to eliminate the friction associated with traditional QA tools that heavily rely on user input, such as recorded flows, manual element tagging, or baseline images. Instead, Treegress generates test cases automatically, streamlining the QA process and allowing teams to test faster with less friction and more confidence.
How Treegress MVP Works
The Treegress MVP platform requires only a URL to get started and generates intelligent test cases automatically. It interprets each DOM (Document Object Model) element based on its role in the app, not just the tag or style, making its tests more resilient. Treegress tracks DOM mutations and listens for user-triggered events in real time, allowing it to continually adapt test cases and maintain coverage automatically.
One of the key features of Treegress MVP is its ability to recognize intent and build test cases based on system behavior, not just the appearance of elements. It uses progressive degradation, assigning each UI element a hierarchy of fallback strategies, allowing test cases to remain functional and valid even as the frontend evolves.
At the core of the platform is a custom-built DOM serialization engine that deeply understands structure, usability, and interaction context. Treegress employs a multi-agent architecture, including agents for test case generation, test case verification, and a self-healing engine, all working under an integrated test management system.
Benefits of Treegress MVP
Treegress MVP offers several benefits for software teams, including:
- No-code Test Creation: Users can build automated tests through an intuitive interface without writing code, lowering barriers for QA teams and product managers to validate software functionality quickly.
- AI-assisted Automation: By integrating AI technologies, Treegress MVP automates complex parts of testing such as scenario generation, test maintenance, and result analysis, thereby reducing time and effort traditionally needed for QA.
- Faster Iteration and Validation: As a minimal viable product (MVP), it focuses on essential test automation features that validate core functionalities early, enabling agile feedback loops and faster product iteration.
- Reduced Technical Overhead: It allows non-technical users to drive QA automation, minimizing the reliance on engineers for test script development and maintenance, which traditionally slows down the QA process.
In essence, Treegress MVP embodies the principles of a minimal viable product combined with generative AI and automation frameworks, offering an accessible, efficient route to implement robust QA without coding—thereby accelerating validation cycles, reducing manual testing effort, and improving software quality early in the development process.
Contact Information
For more information about Treegress MVP, please visit their website at www.treegress.com. You can also reach out to them via email at [email protected] or by mail at their Sacramento, CA address.
[1] This article is based on information from the Treegress press release.
- Treegress MVP, an innovative platform for no-code QA automation, will be launched by tech startup Treegress in August 2025.
- The platform, co-founded by Anna Karnaukh and Oleg Lola, is designed to streamline QA processes by generating test cases automatically using AI.
- One of Treegress MVP's key features is its ability to recognize intent and build test cases based on system behavior, making it more resilient to frontend evolution.
- This technology offers benefits such as no-code test creation, AI-assisted automation, faster iteration and validation, and reduced technical overhead, making it easier to implement robust QA without coding.
