Apptest.ai provides an AI‑driven, no‑code platform for automated mobile testing on real Android and iOS devices. Users create test scenarios with a drag‑and‑drop visual editor, and the cloud service runs them in parallel, delivering logs, video, and analytics that integrate with CI/CD pipelines, accelerating release cycles while ensuring compliance and traceability.
Funding
$3.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
NGFounders
Product
Problem
Mobile application quality assurance often relies on manual scripting and fragmented device farms, leading to slow test cycles, high labor costs, and inconsistent test coverage across Android and iOS platforms.
Solution
Apptest.ai delivers an autonomous, AI‑driven testing platform that runs complete test suites on real devices without any code. The Stego editor uses computer‑vision models to recognize UI components and lets users compose test scenarios through a drag‑and‑drop interface. Once defined, scenarios are executed in the Ptero cloud, which schedules parallel runs on a managed device farm, captures high‑fidelity logs, screenshots, and video evidence, and aggregates results in a centralized dashboard. The service provides instant, auditable reports that can be consumed by CI/CD pipelines or exported via API, enabling DevOps and QA teams to accelerate release cycles while maintaining compliance and traceability.
Target Audience
The primary customers are QA engineers, DevOps teams, and mobile product groups in enterprises and SaaS companies that require continuous, high‑volume testing of Android and iOS applications.
Features
- AI‑powered visual element detection that automatically maps screen objects for script‑free scenario creation
- No‑code, drag‑and‑drop scenario authoring in Stego, supporting conditional flows and data‑driven inputs
- Real‑device execution on a managed Android/iOS farm, ensuring native performance and OS‑level fidelity
- Fully autonomous cloud orchestration (Ptero) with parallel scheduling, auto‑retry, and resource scaling
- Comprehensive test artifacts: step‑by‑step video, annotated screenshots, device logs, and network traces
- Centralized analytics dashboard with trend visualizations, failure clustering, and exportable JSON/CSV reports
- RESTful API and CI/CD integrations (Jenkins, GitHub Actions, Azure DevOps) for seamless pipeline automation