Caesr AI

Caesr AI works from screenshots alone. The agent captures what's on display, a model decides the next action, and it clicks, types, or navigates like a person would. There are no hooks into the application code, which is why it handles apps that expose no API at all. That's the whole point: if a human can operate it, the agent can too. No API required.

Tasks are written as Markdown or CSV, not code. Anyone who knows the application can write one, and they live in your Git repository alongside everything else. When the UI changes, you edit a sentence rather than debugging a recorder. That's a big shift. Traditional test tooling breaks on a small layout tweak; here, a tweak costs you one line.

AgentOS makes an operating system available to the agent, with keyboard, mouse, and screen control in one layer. It runs on the machine doing the work, so the agent operates the device the way a person does. The same runtime covers Windows, macOS, and Linux, plus Android, browsers, and bench hardware, so a team doesn't maintain a different stack for each target.

AskUI Desktop is where work gets written, watched, and replayed. You open a task, run it against a connected device, and read back every step the agent took, with a screenshot per step and a transcript per run. For teams that need an audit trail or a handover artifact, that record is the reason to use it. No more guesswork. Troubleshooting a failed run stops being a hunch.

The CLI is the same engine without the window. Run askui run in a pipeline, on a schedule, or on a machine in the corner, and get the report as a build artifact. It needs no display. Each run returns an exit code plus a report, so it slots into existing CI just like any other check.

You can bring Anthropic, an OpenAI-compatible endpoint, or a self-hosted model on every plan. Inference never touches AskUI's infrastructure, which matters when screenshots contain sensitive data. On Enterprise, you can deploy on-premise or in an air-gapped setup and even skip inference fees by using your own model.

According to AskUI, the vision agent scored 66.2 on the OSWorld benchmark and reached 94.8% task completion on AndroidWorld, placing it on both public leaderboards at publication. Benchmark numbers don't tell you how it'll handle your specific app, but they're a useful signal when comparing computer-use agents, and they're published rather than buried.