Screencap is an innovative open-source tool designed for macOS that transforms your team's real, everyday workflows into structured datasets suitable for AI training and automation. By capturing comprehensive workflow contexts—including screen recordings, clicks, keystrokes, and window context—Screencap bridges the gap between human execution and machine learning data requirements.

Addressing critical data privacy and security concerns, Screencap enforces strict consent and privacy measures during the recording process. Sensitive applications can be automatically blocked before any data is written, and every single trace is thoroughly scrubbed and reviewed locally before it ever leaves a user's machine. Whether you are looking to try it solo with a free trial or coordinate a team pilot, Screencap provides a secure, transparent pipeline for building robust AI training datasets.

Pros of Screencap

Captures comprehensive workflow data including screen, clicks, keystrokes, and window context
Open-source transparency with strict local data scrubbing and review features before export
Built-in privacy controls that block sensitive applications before recording writes anything
Flexible trial and pilot options available for individual users and teams

Cons of Screencap

Currently restricted to macOS
Requires manual review steps before data leaves the machine
Focused primarily on AI training and automation data collection rather than general screen recording

Frequently Asked Questions

What does Screencap record?

Screencap records real workflows including your screen, mouse clicks, keystrokes, and window context to build structured datasets for AI training and automation.

How does Screencap handle privacy and sensitive data?

Privacy is enforced by blocking most sensitive applications before any data is written. Additionally, every trace is scrubbed and reviewed locally on your machine before it can leave.