Kaarigar

KALPis a multi-agent synthetic dataset generator that solves the domain gap the failure of AI models trained on clean, pretty synthetic images when deployed on real, dirty factory cameras. You upload 5 seed images, KALP transcribes them into rich language for Nano Banana 2 Lite, then five parallel agents generate intentionally degraded variations noisy, blurry, dark, occluded in controlled ratios, all auto-labeled in YOLO format with zero human input. The result: a fully annotated, deployment-ready dataset in 90 seconds, validated with a 4.8% mAP improvement on YOLOv8 over real data alone.