Understand how engaged your staff are, in real time.
Safari AI turns your existing cameras into a live workforce analytics system. Monitor activity levels, track peak interaction periods, and optimize staffing decisions across every department and shift.
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Without engagement data, workforce decisions rely on observation and instinct.
Most businesses have no reliable way to measure staff engagement levels in real time across departments. Managers rely on walkthroughs and anecdotal feedback, leading to missed service gaps, poor schedule decisions, and no basis for data-driven workforce optimization.
- —No visibility into when customer-facing staff are disengaged until a complaint surfaces
- —Schedules are built on historical patterns rather than actual peak engagement periods
- —Managers spend time on observational rounds rather than acting on real-time data
- —Labor costs remain high in periods where engagement data would justify leaner staffing
Validated against ground-truth manual observation at deployment. If a camera view underperforms, we retune before you go live at no cost.
Leverage your existing cameras. No construction. Live in under two weeks.
Camera Review
We assess your existing CCTV or IP camera feeds remotely. Compatible views proceed; incompatible ones are flagged before any commitment.
On-Prem Deployment
A compact server is installed on-site and connected to your camera streams. All video is processed locally. Nothing leaves your network.
Calibrate & Go Live
Models are validated against manual observation. Once accuracy is approved, you're live with real-time dashboards and API access from day one.
How leading operators use Safari AI staff engagement data to drive decisions.
Charlotte Hornets
The Charlotte Hornets leverage existing cameras to measure real-time KPIs including guest entrance throughput, concessions queue analytics, and arena heatmapping to drive higher revenue without adding staff.
Read Hornets Case Study Stadiums, Arenas & Venues
Reconext
Reconext's Mexicali facility optimizes manufacturing operations across multiple third-party production lines by measuring critical operational KPIs including staff engagement analytics and dynamic staff operations.
Read Reconext Case Study IT & Electronic Services
StorageMart
StorageMart improves speed of service by measuring staff engagement analytics, front desk dwell time analysis, and parking occupancy monitoring through existing camera infrastructure.
Read StorageMart Case Study Commercial Real EstateEverything staff engagement analytics should do, and actually does.
Monitor staff activity levels and engagement patterns across all areas.
Correlate employee activity with productivity and identify improvements.
Optimize schedules based on peak interaction periods and demand patterns.
Position staff strategically based on real-time engagement and demand data.
Activity Monitoring
Monitors staff activity levels and engagement patterns to help businesses understand when and where employees are most active, enabling managers to act on data rather than walkthroughs and intuition.
Performance Analytics
Real-time engagement analytics enable managers to correlate employee activity with productivity and identify opportunities for performance improvement before issues compound across shifts.
Schedule Optimization
Comprehensive tracking helps businesses optimize staffing schedules by identifying peak interaction periods and reducing labor costs during low-engagement windows without sacrificing service quality.
Resource Allocation
Staff engagement data supports better allocation decisions, enabling businesses to position employees strategically across departments and improve operational efficiency based on where demand actually is.
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Safari AI delivers 99%+ accuracy on pedestrian and footfall counts across indoor and outdoor environments. Accuracy is validated against manual ground-truth counts during deployment, and our computer vision models are trained on enterprise-scale datasets from theme parks, stadiums, retail destinations, and QSRs. If a camera view underperforms, we tune the model to your specific environment before you go live.
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No. Safari AI works with the CCTV and IP cameras you already have — no camera rip-and-replace, no construction, no re-wiring. Deployment requires an on-premise server to process the video feeds locally at your site, which we spec and configure as part of onboarding. Your existing camera infrastructure stays exactly as it is.
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Most customers are live within days to a few weeks, depending on server provisioning and site access. After an initial camera review to confirm compatibility, we install the on-prem server, connect your existing camera feeds, calibrate the models, and validate accuracy against your baselines.
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Safari AI is built for high-density venues — we measure crowd counts and pedestrian flow at theme parks, NHL and NBA arenas, outlet centers, and stadium concourses. Our models handle occlusion, overlapping visitors, and non-linear movement patterns that break traditional sensor-based or beam-break counting systems. Reference clients include LEGOLAND, the Charlotte Hornets, and the Calgary Flames.
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Yes. Counts and analytics are available through live dashboards, scheduled exports, and REST APIs, which means you can pipe footfall data into Tableau, Power BI, Snowflake, your POS, or any internal system. Most enterprise customers run Safari AI alongside existing BI and RevOps workflows rather than as a standalone dashboard.
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Pricing is per-camera and scales based on the number of cameras, sites, and measurements you need — pedestrian counts, occupancy, dwell time, queue wait, and more can be layered on the same feeds. We offer a free 90-day pilot using your existing cameras with no credit card required, so you can validate accuracy and ROI before committing. Contact us for a tailored quote.
Frequently Asked Questions
See exactly what your cameras can do.
Evaluate Safari AI on your existing camera infrastructure for 30 days. No credit card, no commitment.
30-day free pilot · No credit card required · Uses your existing cameras · Video processed on-premise
Frequently Asked Questions
How accurate is Safari AI's footfall counting?
Safari AI delivers 99%+ accuracy on pedestrian and footfall counts across indoor and outdoor environments. Accuracy is validated against manual ground-truth counts during deployment. If a camera view underperforms, we retune the model to your specific environment before you go live, at no additional cost.
Do I need to replace my cameras to use Safari AI?
No. Safari AI works with the CCTV and IP cameras you already have. No rip-and-replace, no construction, no re-wiring. An on-premise server is installed to process video locally; your existing camera infrastructure stays exactly as it is.
How long does Safari AI deployment take?
Most customers are live within days to a few weeks. After a camera compatibility review, we install the on-prem server, connect camera feeds, calibrate the models, and validate accuracy against your baselines before going live.
Can Safari AI handle high-density crowds?
Yes. Safari AI is built for high-density venues — theme parks, NBA and NHL arenas, outlet centers, and stadium concourses. Models handle occlusion, overlapping visitors, and non-linear movement that defeats traditional beam-break sensors. Clients include LEGOLAND, Charlotte Hornets, and Calgary Flames.
Can Safari AI integrate with Tableau, Power BI, Snowflake, or our POS?
Yes. Footfall counts and analytics are available via live dashboards, scheduled exports, and a REST API. You can pipe data into Tableau, Power BI, Snowflake, your POS, or any internal system. Most customers run Safari AI alongside existing BI and RevOps workflows.
How does Safari AI pricing work?
Pricing is per-camera and scales with the number of cameras, sites, and measurement types. Pedestrian counts, occupancy, dwell time, queue wait time, and more can be layered on the same feeds. A free 30-day pilot with no credit card required is available so you can validate accuracy and ROI before committing.