In healthcare, an "almost right" AI is worse than no AI. AiSPRY ships clinically validated, regulator-aligned models - embryo grading, medical imaging, drug forecasting, pharma compliance - explainable on every prediction, deployable at the edge, and trusted by ART clinics, hospitals, and regulated pharma manufacturing alike.
The frontier isn't AI replacing doctors - it's AI removing the variability that shouldn't have been there in the first place. Embryo grading, radiology second-reads, drug demand forecasting, packaging-line counts - every one of these benefits from a model that always sees the same image the same way.
Each capability below is shipped - not pitched. Clinically validated, regulator-aligned, and deployable inside hospital networks.
Multi-stage CNN models for embryo grading aligned to Gardner / Istanbul scales, sperm quality assessment, and embryo implantation window prediction - explainable via Grad-CAM / LRP, deployable on incubator-side hardware.
Vital-Essential-Desirable segmentation, ensemble forecasting per segment (data-driven + model-driven + DL + transformer-based), and a FastAPI + React reorder UI with risk-attitude controls. Built for multi-specialty reality.
Cancer detection from histopathology, solar / lesion classification, segmentation pipelines using MONAI. Always shipped with explanation overlays - clinician sees what the model saw.
Computer-vision systems for automated real-time inventory counting on packaging lines, with GMP / FDA-grade audit trail generation. Replaces error-prone manual counts.
Retrieval-grounded clinical assistants - answers cite hospital SOPs, ART Act provisions, ICMR circulars. No hallucinated treatment recommendations; explicit refusal when source is missing.
GenAI bots that extract patient details and clinical history from HMS, lab systems, and image archives via prompt - surfacing what the clinician needs without paper-shuffling.
Real clinics, real regulators, real audit cycles.
Clinical AI, vision-based compliance, and hospital-grade forecasting - built for regulators, embryologists, and pharmacy councils, not for demos.
R&R-tested labels from senior clinicians - not crowd-sourced annotations. Garbha.ai's models were trained on 10,000+ embryologist-graded images.
Grad-CAM / LRP / SHAP layered into outputs - clinicians see what the model saw, not just the score.
Patient images and EHR data never leave the hospital network. Cloud is opt-in, not default.
ISO 13485:2016, CDSCO Manufacturing License, ART Act, ISO/IEC 42001, DPDP - addressed in design, not patched in audit.
Plugs into embryologist workflow, HMS, packaging-line PLCs - clinicians and operators don't change what they do, the AI fits the work.
Talk to AiSPRY about an embryo-grading rollout, a hospital VED forecasting deployment, or a packaging-line vision pilot. We bring the clinical-grade rigour, you bring the workflow.