Minitap raises $4.1M to fix slow AI mobile development

Mobile development is notoriously slow, lagging far behind the rapid iteration cycles seen in web development, even with the rise of powerful AI coding assistants. A new startup, Minitap, claims it has solved this bottleneck, promising to make mobile feature shipping 10 times faster by enabling AI agents to test and iterate autonomously on real devices.

The San Francisco-based company announced today it has raised $4.1 million in seed funding, co-led by Moxxie Ventures and Mercuri. The round follows a dramatic technical achievement: Minitap’s 23-year-old founders, Nico Dehandschoewercker and Luc Mahoux-Nakamura, claimed the global #1 position on the AndroidWorld industry benchmark—a measure of AI control over mobile devices—surpassing research teams from Google DeepMind, Microsoft, and ByteDance within 40 days of starting the project.

While large language models (LLMs) like Claude and Cursor have dramatically accelerated web workflows, they remain largely ineffective for mobile. The core issue is complexity: AI agents cannot easily test code across thousands of device configurations, verify features work on real hardware, or iterate when bugs inevitably appear. This forces companies like Duolingo and Hinge to run five times more experiments on the web than on their mobile apps.

“Mobile is 60% of internet usage but moves at 10% of web speed,” said CEO Nicolas Dehandschoewercker. “We built Minitap to close that gap. The companies that run 10x more experiments will win their markets.”

The Infrastructure for Autonomous Mobile Agents

Minitap’s solution centers on two key innovations designed to bring agentic AI to mobile use. The first is `mobile-use`, an open-source framework that allows AI agents to control phones like human users. The second is `minitap cloud`, infrastructure that instantly spins up any iOS or Android configuration across thousands of devices in parallel.

These tools create a fully autonomous loop: an AI coding environment writes mobile code, tests it on real devices, identifies bugs, fixes itself, and ships working features without human intervention. This process aims to cut the timeline for shipping a new mobile feature from the industry standard of six weeks down to days.

The funding round attracted significant attention from the AI infrastructure community, including unicorn founders like Thomas Wolf (Hugging Face), Petter Made (SumUp), and operators from OpenAI and DeepMind.

Minitap’s immediate goal is to allow product managers to describe a feature, provide a Figma design, and have the AI generate, test, and ship an A/B test in a single afternoon. Longer term, the team plans to build mobile apps that optimize themselves autonomously, running experiments and iterating based on user behavior without any human intervention, fundamentally changing the landscape of AI mobile development.