Markov

Train computer-use AI models with synchronized screen recordings and interaction datasets

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You can use Markov to train computer-use AI agents with real-world workflow datasets. The service captures how people interact with computers, recording screens along with synchronized mouse movements, keystrokes, and narrations. It provides specialized data environments across software like AutoCAD, SolidWorks, Revit, Salesforce, Blender, and standard web browsers. You can access benchmark rubrics, problem statements, and reference files to build supervised fine-tuning pipelines. These rich datasets help machine learning researchers teach autonomous agents to navigate complex desktop software and browser tasks reliably.

What Markov does

Download computer-use interaction datasets from Hugging FaceTrain vision-based agents to operate desktop applicationsInspect synchronized mouse click and keyboard input sequencesEvaluate agent output files against gold-standard rubricsFine-tune multimodal models on specific enterprise workflowsSimulate multi-step user actions in CAD software environmentsSynchronized screen recordings with keystroke and mouse telemetryDomain-specific CAD environment datasets including AutoCAD and SolidWorksOpen-source datasets hosted on Hugging Face with thousands of hoursAudio narrations explaining user actions during workflow executionVerifiable outcomes paired with gold standard output files and rubricsBrowser, spreadsheet, and coding workflow recordings for supervised fine-tuning