15M Workflow Dataset Raises Switching Costs
Scribe
This dataset turns Scribe from a screen capture tool into a workflow system of record for enterprise AI decisions. Optimize is valuable because it does not just show one employee how to do a task, it aggregates thousands of recorded clicks and page transitions into process maps, bottlenecks, and ranked automation opportunities. Once a large company has documented work across teams, replacing Scribe means losing both the library of guides and the behavioral history that makes those recommendations useful.
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The closest budget analog is process mining and task mining. Celonis and UiPath sell software that reconstructs how work flows across systems and employee desktops, then point teams to high ROI automation targets. Scribe is approaching that same budget from the front end, starting with user generated how to guides instead of ERP logs or desktop surveillance.
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The switching cost is highest in large accounts because the data gets better as more teams use it. A single captured guide is documentation. Millions of guides across 40,000 apps become a map of which tools people actually open, which steps repeat, where handoffs break, and which workflows are stable enough to automate.
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This also changes the buyer. Capture can spread bottom up with an individual employee. Optimize sells top down to CIOs and operations leaders because it helps answer a harder question, where AI agents or automation should be deployed first, and what savings are realistic before a company spends on implementation.
The next step is for workflow data to become infrastructure for other AI tools, not just a reporting layer inside Scribe. As Optimize, enterprise search, and MCP connectors mature, the company can sit between employees and downstream copilots, feeding agents the exact steps, systems, and exceptions that make automation work in real companies.