V-Count Nano AI delivers 99% accuracy at clinic entrances, waiting rooms, registration desks, and public areas, independently benchmarked against manual counts across thousands of live deployments. Nano Prime reaches 98% accuracy. Accuracy holds up under direct sunlight, shadows, reflective surfaces, group flow, strollers and wheelchairs, and peak surges. Customers in healthcare typically validate accuracy during a 2 to 4 week pilot before full rollout.

Pricing is per sensor plus a BoostBI analytics subscription. There is no per report or per dashboard upcharge. A single door healthcare location typically starts around a few hundred euros in hardware plus a monthly BoostBI seat. Multi site chains get volume pricing and BoostBI Enterprise. Get a precise quote by booking a discovery call at https://v-count.com/demo-request/.

V-Count uses 3D stereo vision, not cameras in the traditional sense. No facial images, no personally identifiable information, no biometric identifiers are captured. The sensor only outputs counts, directions, dwell times, and anonymous shapes. V-Count is GDPR, CCPA, KVKK, LGPD, and PDPA compliant out of the box, with a Data Processing Agreement available on request. Many healthcare operators deploy V-Count in jurisdictions where traditional CCTV analytics would be prohibited.

The core metric set for healthcare includes waiting area occupancy, patient flow, and dwell at registration. Beyond that, BoostBI computes derived KPIs like conversion rate (when POS or ticketing is connected), capture rate (visitors who entered vs those who walked past), dwell time by zone, peak hour loading, and year over year comparisons. Everything is available via the dashboard, scheduled email report, or REST API.

Installation takes about 20 minutes per sensor. Most healthcare locations use ceiling mount at 2.5 to 6 meters. Sensors need only power (PoE or 12V DC) and an ethernet or wifi connection. Calibration is automatic via BoostBI. V-Count certifies installation partners in more than 60 countries and offers remote commissioning for self install teams.

Yes. V-Count is deployed at clinic entrances, waiting rooms, registration desks, and public areas across hospital administrators and clinic operators in more than 130 countries. The sensor range, field of view, and mounting options cover typical healthcare geometries. For unusually high ceilings, wide entrances, or outdoor areas, ask about Nano AI wide angle, sensor arrays, or the Nano Outdoor model.

BoostBI exposes a REST API with OAuth authentication, and supports webhooks, CSV export, and scheduled email reports. Common integrations for healthcare include POS systems (Lightspeed, Square, Shopify, NCR, Oracle Simphony), ticketing platforms, CRM (Salesforce, HubSpot), BI (Power BI, Tableau, Looker), building management (BMS/BACnet, MQTT for IoT), and workforce tools (Kronos, UKG, Quinyx, 7shifts). Custom connectors can be built in days.

V-Count differentiates on five things. First, 99% accuracy with on sensor AI that handles occlusion, groups, and bad lighting. Second, privacy first by design: no facial recognition, no PII, compliant out of the box. Third, a true cloud analytics layer in BoostBI with APIs, heatmaps, and benchmarking, not just raw counts. Fourth, a global install base of 600+ companies across 130+ countries with local installation partners. Fifth, transparent pricing and contracts. Most healthcare operators who switch from legacy systems report more accurate counts, faster time to insight, and lower total cost of ownership.

Typical ROI in healthcare comes from three levers. Staffing: match labor to peak hour flow and cut over staffing cost 5 to 15%. Merchandising: increase conversion 2 to 8% by acting on capture rate and dwell data. Capacity and compliance: avoid fines and legal risk from over capacity events. Most customers recover the investment in under 12 months; chain operators often see payback in one quarter.

Yes. BoostBI Enterprise is built for chains and portfolios. You can benchmark locations by waiting area occupancy, patient flow, and dwell at registration, rank them, flag outliers, and send location specific reports to managers. Each site gets its own dashboard while HQ sees the full estate. Hospital administrators and clinic operators can also run A/B tests across sites.

A single site goes live in under a day, from sensor mounting to dashboard. A multi site rollout of 10 to 50 healthcare locations typically completes in 4 to 8 weeks, including network readiness, installer scheduling, BoostBI setup, and training. 500+ site programs run as phased rollouts with certified partners.

Yes. Data is retained indefinitely by default and is exportable at any time. Year over year and season over season comparisons are native to BoostBI. For cross customer benchmarking, ask about the BoostBI Industry Index, which anonymizes healthcare data across the V-Count customer base to show how your sites trend against the industry average.

The default is the Nano AI 3D stereo vision sensor, which runs deep learning inference on the device. For outdoor healthcare environments, Nano Outdoor is IP65 rated and handles minus 30 to plus 60 Celsius. For entry level single door locations, Nano Prime offers 98% accuracy at a lower price point. All hardware is PoE or 12V DC powered, with a 5 year warranty.

Yes. V-Count does not capture, process, or store personal data. Counts, directions, and dwell metrics are anonymized by design. The company signs Data Processing Agreements, supports EU data residency via AWS Frankfurt, and has completed ISO 27001 certification. Hospital administrators and clinic operators in regulated sectors (healthcare, financial services, government) have deployed V-Count without a Data Protection Impact Assessment red flag.

Yes. BoostBI supports real time alerts via email, SMS, or webhook when thresholds are crossed. Typical alerts for healthcare include capacity breach, queue length over target, unusually low traffic, and sensor offline. Alerts can route to individuals, Slack channels, or ticketing systems.