Sova AI: AI Agent for Android without PC

Sova AI: An Autonomous AI Agent for Task Automation on Android

Sova AI is a mobile app for Android that implements an AI agent capable of controlling apps and performing user tasks directly on the device. It requires no ADB, USB connection, root access, or PC. It operates via the Accessibility API, analyzing the screen element tree and screenshots. It supports voice commands as the default assistant.

Differences from Existing Solutions

Most AI assistants for mobile devices (computer-use, browser-use) are tied to a PC, limiting mobility. Sova AI functions exclusively on the phone, simulating clicks, scrolls, app launches, and other user actions. It combines UI tree parsing with computer vision for accuracy, minimizing LLM token usage.

Supported AI Models

The app uses BYOK (Bring Your Own Key) — the user provides an API key from a provider. Integration with:

• OpenAI
• Anthropic
• Google
• Grok
• Alibaba (Qwen)
• Deepseek

Keys are stored locally, without transmission to servers. Support for local models (Ollama, LM Studio) is planned for operation without cloud APIs.

Practical Use Cases

Sova AI has been tested in real-world tasks:

• Ordering taxis (Uber) and food
• Booking restaurant tables
• Automating Tinder
• Working with camera and astronomy apps
• Writing messages in Telegram, X (Twitter)
• Searching and creating playlists on Spotify, YouTube

Limits are defined by LLM speed — not suitable for real-time games, but works in turn-based ones (e.g., preference).

Installation and Availability

The app is unavailable on Google Play due to Accessibility API restrictions. Distributed via APK from the website, Samsung Galaxy Store, and Xiaomi GetApps. Installation is simple, suitable for all user levels. Currently free.

Key points:

• Full autonomy: no PC, root, or special hardware required.
• Flexible LLM integration via BYOK.
• Token savings through UI tree and screenshot combination.
• Voice control as the system assistant.
• Limitations: not for high-frequency real-time tasks.

Technical Implementation

Under the hood — Android Accessibility API for accessing screen element hierarchy. Supplemented with screenshot analysis for tasks where text structure is insufficient. LLM generates action sequences (clicks, swipes, text input). Token optimization reduces costs: the model focuses on key UI fragments.

For developers: openness to new LLM providers — integration requests are accepted. Local models will bypass cloud expenses.

— Editorial Team