Caremaze provides an AI-powered platform designed to streamline and optimize clinical trial patient recruitment. The system analyzes complex eligibility criteria against real-world patient data to accelerate identification and matching. This technology reduces enrollment timelines and improves the efficiency of clinical research operations.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare providers often contend with fragmented data sources and manual scheduling processes, leading to suboptimal resource allocation, bottlenecks in patient flow, and reduced clinical throughput. These inefficiencies increase operational costs and can compromise patient experience.
Solution
Caremaze delivers an AI-driven operations platform that consolidates clinical, administrative, and logistical data into a unified view. Its predictive analytics engine forecasts demand for beds, staff, and equipment, enabling proactive adjustments to scheduling and capacity planning. Real‑time dashboards surface bottlenecks and suggest corrective actions, while automated alerts keep care teams informed of emerging constraints. By aligning resources with anticipated patient volume, the platform boosts operational efficiency and supports higher throughput without additional staffing. The solution integrates with existing EHR, RIS, and ERP systems through secure APIs, ensuring seamless data flow and compliance with healthcare regulations.
Target Audience
The primary customers are hospital systems, large multi‑site clinics, and health networks that manage inpatient beds, operating rooms, and ancillary services and need data‑driven operational control.
Features
- Unified data ingestion layer that normalizes feeds from EHR, PACS, scheduling, and inventory systems
- Machine‑learning models that predict bed occupancy, staffing needs, and equipment utilization up to 48 hours ahead
- Interactive, role‑based dashboards displaying real‑time capacity metrics, patient flow heatmaps, and variance analysis
- Automated exception alerts and recommendation engine for dynamic reallocation of resources
- Scenario simulation tool for “what‑if” planning of surge events, seasonal trends, or policy changes
- HL7/FHIR‑compatible API suite for bidirectional integration with legacy and cloud‑based health IT platforms
- End‑to‑end encryption and audit logging to meet HIPAA and GDPR requirements