Simulate computer-use models executing full desktop tasks. Trace real mouse trajectories, OCR vision recognition, keystroke streams, and latency checkpoints.
Models like GPT-6 Astra, Anthropic Computer Use, and OSWorld systems do not merely output text; they operate full graphical user interfaces through cyclic vision-action loops:
Delegating full desktop control introduces risk for sensitive operations like wire transfers, production database drops, or sending confidential emails. This studio demonstrates:
Legacy enterprise software (SAP, Bloomberg Terminals, legacy ERPs, desktop spreadsheet suites) lacks modern REST or GraphQL endpoints. A computer-use model operates legacy desktop software with zero custom engineering by utilizing universal pixels, mouse events, and native OS accessibility trees.
Yes. The "Export Executable JSON" button outputs structured actions (click coordinates, typed keystrokes, wait bounds, and validation checks) fully compatible with standard PyAutoGUI, Playwright, or OSWorld runtime environments.
The five finance preset latencies are four hundred twenty, six hundred fifty, two hundred eighty, four hundred eighty, and three hundred ten milliseconds. Their sum is twenty one hundred forty. The corresponding token constants sum to forty two hundred eighty. Adding one custom click appends three hundred fifty milliseconds and six hundred fifty tokens, producing twenty four hundred ninety and forty nine hundred thirty. At point one pixels per summed latency millisecond the bars span two hundred fourteen and two hundred forty nine. These totals are written constants. The canvas paints a fictional desktop; it does not open an ERP, read invoices, type notes, wire funds, or measure actual model inference. Running the finance plan at speed two point five or instant compile nine hundred ninety nine changes animation waiting, but the displayed completion time still sums the same preset latencies, two point one four seconds. The equal two hundred fourteen pixel bars show that dependency boundary. Frame captures are random integers two or three per step, and confidence is a random number from ninety eight point eight to below ninety nine point nine. Neither measures actual captures or model confidence. Strict safety mode writes a confirmation approved log and waits briefly without collecting a real human token. A safety label in the plan is not proof that external permission or sensitive-action approval occurred. The finance preset has five steps while CRM has four, represented by two hundred fifty and two hundred pixel bars. Export writes their action types, application labels, instructions, target rectangles, and a safety flag for safety-type steps. The fixed Linux and nineteen twenty by ten eighty environment is descriptive metadata, not a detected operating system or validated coordinate mapping. A native canvas click can reposition the selected target and export those coordinates. The generated custom step target caption uses a different formula from its actual rectangle until repositioned. Use the exported rectangle as local plan data, while actual execution, OCR, tests, PR creation, uploads, and public playback remain unproved.