Customers routinely see...
10-15%
Customer Satisfaction
100%
Realtime Visibilty
30-35%
Asset Utilisation
50-60%
Billing Cycle
30-35%
Manual Labor
15-20%
CO2 Emissions
15-30%
Driven Miles
Last Mile TMS For Healthcare - Lab Logistics
Enterprise Based Full Network Visibility
Full Network-Wide Logistics Visibility ensures real-time tracking and monitoring across the entire supply chain. For lab logistics, this includes monitoring specimen movement across hubs, hospitals, and processing labs while maintaining chain of custody compliance and integrity of pickup and drop-off of samples. AI-driven insights help predict delays, optimize routes, and enhance operational efficiency across geographic locations. This level of visibility is crucial for managing STAT orders, multi-leg and/or multi-facility transfers, and time- and temperature-sensitive samples.

Order Planning With AI & ML Based Route Optimization
Order Planning & Route Building in lab logistics involves dynamically determining the most efficient pickup, transfer, and delivery paths while considering urgency, specimen type (ambient, refrigerated, frozen), and regulatory constraints. AI-powered routing optimizes multi-leg and multi-facility transfers, ensuring STAT orders reach the right processing labs within stipulated timeframes. Real-time adjustments account for lab eligibility, travel distances, traffic conditions, and sudden order changes. This precision-driven approach enhances efficiency, reduces delays, and ensures fast, compliant, and cost-effective specimen transportation.

Dispatch Execution
Impact on Dispatch Execution in lab logistics is streamlined by nuVizz’s Last Mile TMS, which automates complex decision-making for real-time order handling. The system dynamically processes call-in requests, STAT orders, and multi-leg transfers, instantly determining optimal pickup, transfer, and drop-off locations. It evaluates lab processing eligibility, route efficiency, driver availability, and time constraints to ensure seamless execution. AI-powered automation minimizes manual intervention, enabling faster response times, and improved service reliability across the entire logistics network.

Driver Execution
Impact on delivery representative flow is significantly enhanced by nuVizz’s intuitive and adaptive mobile app, which streamlines the entire workflow. The app dynamically adjusts to varied workflows, ensuring efficient sample bag tagging while maintaining chain of custody. Drivers can record and handle exceptions in real-time, preventing disruptions in specimen transportation. The system also enables on-the-fly creation of new stops, locations or make transfers, allowing seamless sample collection, rerouting, and multi-leg transfers. This level of automation improves accuracy, efficiency, and compliance, reducing manual errors and ensuring smooth operations.

Analytics, Dashboards & Reporting
Lab logistics teams may obtain comprehensive insights into delivery performance, compliance, and operational efficiency with the aid of nuVizz’s sophisticated analytics, real-time dashboards, and automated reporting. Advanced analytics offer visibility into order volumes, route efficiencies, STAT order fulfillment rates, and chain of custody adherence. Customizable dashboards help identify bottlenecks, optimize resource allocation, and enhance decision-making by leveraging AI-driven trends and predictive analytics. Dispatchers, drivers, and lab managers gain actionable intelligence to improve turnaround times, reduce costs, and maintain regulatory compliance, ensuring a data-driven approach to operational excellence.

Customers
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000
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Highlighted customer review
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Press releases
nuVizz Recognized in the...
ATLANTA, March 04, 2025 (GLOBE NEWSWIRE) — nuVizz, a provider of transportation management solutions and last-mile...
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ATLANTA, Feb. 04, 2025 (GLOBE NEWSWIRE) — nuVizz, a leading innovator in Last-Mile Transportation Management Solutions...
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nuVizz Recognized in the...
ATLANTA, July 10, 2024 (GLOBE NEWSWIRE) — nuVizz, a leading provider of transportation management solutions and...
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