Kriba provides a portable high‑resolution ultrasound platform that uses deep‑learning algorithms to detect infections in serous body fluids such as cerebrospinal, peritoneal, and ocular fluid without invasive sampling. The system captures real‑time ultrasound images, automatically classifies infection presence and severity, and delivers instant results through a secure clinician dashboard for point‑of‑care use in hospitals, clinics, and home settings.
Funding
Funding not disclosed
Founders
Product
Problem
Diagnosing infections in serous body fluids such as cerebrospinal fluid, peritoneal fluid, or ocular fluid typically requires invasive sampling procedures that are painful, carry risk of complications, and may delay treatment, especially in vulnerable populations like newborns and home dialysis patients.
Solution
Kriba offers a high‑resolution ultrasound platform combined with deep‑learning algorithms to detect cellular and biochemical signatures of infection directly through the skin. The device captures detailed ultrasound images of the target fluid space (e.g., transfontanellar window for meningitis, peritoneal cavity for peritonitis, anterior chamber for uveitis) and an AI model automatically classifies infection presence and severity. Results are delivered instantly to clinicians via a secure software interface, enabling rapid, non‑invasive screening and longitudinal monitoring without the need for lumbar puncture, paracentesis, or invasive ocular sampling. The approach is designed for point‑of‑care use in hospitals, clinics, and home‑based settings, supporting early detection and timely therapeutic decisions.
Target Audience
Primary customers are neonatologists and pediatric clinicians, nephrologists managing home peritoneal dialysis patients, and ophthalmologists seeking non‑invasive infection screening tools, as well as hospitals and specialty clinics adopting point‑of‑care diagnostics.
Features
- High‑frequency transfontanellar and abdominal ultrasound probes optimized for imaging serous fluid compartments
- Proprietary deep‑learning models trained on annotated ultrasound datasets for meningitis, peritonitis, and anterior uveitis detection
- Real‑time AI inference with automated infection scoring and visual heat‑maps displayed on a clinician dashboard
- Cloud‑enabled data storage and analytics for longitudinal patient monitoring and trend analysis
- Portable, battery‑operated hardware suitable for bedside, neonatal intensive care, and home peritoneal dialysis environments
- Integration with electronic health record systems via standard APIs for seamless workflow adoption