Run the simulation

Pick a scenario. We generate a year of synthetic but realistic bank + bookkeeping data (with planted issues — missing entries, duplicates, miscategorization), then run the full AI pipeline against it to show what it detects and categorizes. The figures below are illustrative results from synthetic-data testing — they show how the model works on planted ground truth, not a guarantee or promise of results on your books.