WhatA developer tool that records rich, structured workflow traces (UI interactions, app state, intent annotations) from knowledge workers and converts them into high-quality training datasets for computer-use AI agents.
SignalRaw keystrokes and mouse movements are low-signal data — what's actually needed to train useful AI agents is structured understanding of intent, context, and application state, which requires purpose-built recording infrastructure.
Why NowComputer-use AI agents (like Anthropic's, OpenAI's Operator) are shipping now but starved for high-quality training data that maps human intent to screen actions — the demand side just appeared.
MarketAI labs and enterprises building computer-use agents; $2B+ near-term market; gaps in existing screen recording tools (Loom, RPA vendors) which don't produce ML-ready datasets.
MoatProprietary data annotation schema and tooling that becomes the standard format for computer-use agent training — network effects as more models train on your format.
Meta to start capturing employee mouse movements, keystrokes for AI trainingView discussion ↗ · Article ↗ · 671 pts · April 21, 2026
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