Apptest.ai
Fully automated mobile app QA at your fingertips.
| Date | Investors | Amount | Round |
|---|---|---|---|
| N/A | €0.0 | round | |
| investor investor | €0.0 | round | |
* | KRW5.0b | Early VC | |
| Total Funding | 000k | ||
Apptest.ai, founded in 2016 and headquartered in San Jose, CA, operates as a software-as-a-service (SaaS) provider specializing in AI-powered automated mobile and web application testing. The company was founded by a team with a background in mobile QA, machine learning, and cloud computing to address the inefficiencies and high costs of traditional app testing. The firm's client base includes software and mobile app developers, ranging from small teams to large enterprises, with notable customers like LG U+, Hyundai Motor Company, and NBC Universal.
The business model is centered on a subscription-based service with flexible pricing plans, including a free trial and enterprise-level solutions. Revenue is generated by providing access to its proprietary testing platform. This platform aims to reduce clients' time-to-market and testing costs by automating the quality assurance process. The company has secured funding from investors including Samsung NEXT, STIC Ventures, and NAVIATOR GLOBAL, with a recent bridge investment of $3.7 million in mid-2024 to fuel global expansion and technology enhancement.
Apptest.ai's core offering is a suite of AI-driven tools designed for codeless test automation. The platform features two main products: Ptero, a test automation cloud, and Stego, a no-code test scenario authoring tool with a drag-and-drop interface. It performs UI-based black-box testing on a diverse range of real physical devices, not simulators, covering Android and iOS native apps, hybrid apps, and web applications. The service leverages computer vision and natural language processing to autonomously explore applications, identify bugs, and detect performance issues like crashes or slow screen loading. After a test, the platform delivers comprehensive reports that include step-by-step screenshots, device logs detailing CPU and memory usage, and an activity map, all accessible via a web client.
Keywords: mobile app testing, AI test automation, no-code testing, software quality assurance, SaaS, Ptero, Stego, real device testing, automated bug detection, application performance monitoring, UI testing, codeless automation, CI/CD integration, mobile device farm, Android testing, iOS testing, web application testing, black-box testing, test scenario authoring, software development applications