Know your crowd. Maximize every revenue opportunity.
Safari AI counts crowds and groups in real time using your existing cameras at 99%+ accuracy. Know your live occupancy, prevent overcrowding, and keep guests safe. Trusted by Taco Bell, Charlotte Hornets, LEGOLAND, 7-Eleven, and the Calgary Flames.
Manual counts and IR beams fail in crowds.
Most venues use manual clickers or beam sensors that fail the moment crowds form. People move in groups, block sensors, and change direction. The result is no reliable occupancy data when you need it most.
- Beam-break sensors undercount by 15 to 40% in crowd conditions1
- Manual counts take labor hours and arrive days after the fact
- No breakdown by entrance, zone, or time-of-day
- No alerting when thresholds are crossed. You find out too late
Validated against manual ground-truth counts at deployment. If a camera view underperforms, we retune the model to your environment before you go live, at no additional cost.
Real-time crowd counts from your existing cameras. 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 counts. Once accuracy is approved, you're live with real-time dashboards and API access from day one.
How leading operators use Safari AI party and crowd count data to drive decisions.
Calgary Flames
The Calgary Flames measure and optimize real-time KPIs including guest entrance throughput, concessions queue analytics, and pedestrian footfall heatmapping throughout the arena.
Read Calgary Flames Case Study →
Summit One Vanderbilt
Summit One Vanderbilt optimizes guest experiences and operational efficiency by measuring critical operational KPIs including guest journey tracing and real-time occupancy management.
Read Summit One Vanderbilt Case Study →
Merlin Entertainments
Merlin leverages Safari AI on 3 continents to monitor real-time operational metrics across their attractions, optimizing guest experiences and improving operational efficiency.
Read Merlin Entertainments Case Study →Party and crowd count analytics that actually works.
Pinpoint bottlenecks at entrances and redeploy resources before lines form.
Identify high and low-traffic zones in real time to redistribute crowds and improve guest experience.
Test operational changes with real crowd data to optimize layouts and increase revenue.
Manage capacity limits and ensure safe guest distribution during peak periods.
Real-Time Crowd Counting
Count groups and individuals simultaneously across every zone. Know your live occupancy to the minute, not the hour.
Capacity Alerts and Thresholds
Set crowd limits per zone or venue-wide. Get instant alerts when counts approach capacity so staff can act before safety issues arise.
BI and Operations Integration
Push live crowd data into Tableau, Power BI, Snowflake, or your ops platform via REST API. Safari AI fits into your existing stack.
Multi-Zone Benchmarking
Compare crowd density across zones and events. Identify patterns across time periods and replicate what works for crowd flow management.
Frequently Asked Questions
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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.
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.
IR beam-break sensors are documented to miscount in high-traffic or wide-entrance conditions due to simultaneous crossings and non-human obstructions. Accuracy in crowd conditions can fall to 60 to 85%, representing a 15 to 40% undercount error. Sources: People Counting Systems — Infrared Sensors; V-Count — People Counting Technologies Guide; Milesight VS360 IR Sensor (up to 80% accuracy noted).
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