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Company profile:
Startup name: Autosana
Tagline: AI testing to ship faster
Elevator Pitch: Autosana is the end-to-end testing layer for your coding agents, across iOS, Android, and Web apps.
Coding tools have 10x’d dev speed, but so has the surface area for bugs, leaving teams stuck, relying on or manual QA to validate code changes.
Autosana solves this by closing the loop between dev and testing.
Autosana creates, updates, and runs E2E tests automatically from your code diffs. Locally, it loops with your coding agent until every test passes. In PRs, it loops with cloud agents and shows video proof of your new feature or bug fix working end-to-end.
We power the E2E testing behind the YC mobile app and dozens of popular apps, serving 50M+ DAU.
Target Market: Software development teams and businesses building iOS, Android, and web applications
How will you make money?:
How much capital have you raised?:
Website: https://autosana.ai/
City/Country:
AI-assisted summary:
Autosana is a San Francisco-based startup offering an AI-driven quality assurance (QA) platform designed to automate end-to-end testing for iOS, Android, and web applications. By leveraging artificial intelligence, Autosana aims to streamline the QA process, enabling development teams to identify and address issues more efficiently. (globenewswire.com)
The Problem and Target Users
In the rapidly evolving landscape of mobile and web development, maintaining robust QA processes is increasingly challenging. Traditional methods often rely on manual testing or brittle test scripts that require constant updates, leading to inefficiencies and potential oversights. This issue is particularly acute for development teams striving to keep pace with accelerated release cycles. (siliconangle.com)
Autosana targets both enterprises and startups seeking to enhance their QA processes. The platform is designed to serve technical engineers and non-technical manual testers by providing a user-friendly solution that integrates seamlessly into existing workflows. (siliconangle.com)
The Product and Key Features
Autosana’s platform introduces an “agentic” approach to QA, utilizing AI agents that simulate real user interactions to detect issues before they reach end-users. Key features include:
- Natural Language Test Creation: Users can describe test scenarios in plain English, eliminating the need for coding expertise. (globenewswire.com)
- Self-Healing Tests: The AI agents adapt to changes in the application’s user interface, reducing maintenance efforts associated with traditional test scripts. (caplight.com)
- Framework Agnostic: Supports applications built with various technologies, including React Native, Flutter, Swift, and Kotlin. (caplight.com)
- CI/CD Integration: Seamlessly integrates into continuous integration and continuous deployment pipelines, facilitating efficient testing workflows. (caplight.com)
Business Model, Pricing Signals, and Traction
Autosana operates on a business-to-business (B2B) model, offering its platform as a subscription-based software-as-a-service (SaaS) product. The company has demonstrated significant traction, powering QA for applications serving over 100 million daily active users and achieving over 100% month-over-month revenue growth since its launch in June 2025. (globenewswire.com)
In February 2026, Autosana secured $3.2 million in funding from investors including Y Combinator, Pioneer Fund, Phosphor Capital, DeVC, 468 Capital, and notable angel investors such as Paul Graham. The funds are intended to expand the engineering and growth teams and further develop the platform. (globenewswire.com)
Expert Take
Autosana’s innovative use of AI to automate QA processes addresses a critical pain point in software development, particularly for teams managing rapid release cycles. The platform’s natural language interface and self-healing capabilities offer a compelling value proposition by reducing the technical burden of test creation and maintenance. However, as with any AI-driven solution, the effectiveness of Autosana’s agents in handling complex or edge-case scenarios remains to be fully evaluated as the platform matures.
Note: Information based on publicly available sources at the time of writing, and summarized by AI.
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