Leverage your existing cameras to drive profitability.
Safari AI delivers 99%+ accurate footfall analytics using your existing camera infrastructure. Trusted by Taco Bell, Charlotte Hornets, LEGOLAND, 7-Eleven, and the Calgary Flames.
Manual counts and IR beams are costing you decisions.
Most operators rely on infrared door sensors or periodic manual counts. These methods fail in crowds, can't handle multi-path entrances, and offer no real-time visibility.
- 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.
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 counts. Once accuracy is approved, you're live with real-time dashboards and API access from day one.
How leading operators use Safari AI footfall data to drive decisions.
Taco Bell
Taco Bell measures pedestrian traffic analytics at potential new locations to make data-driven decisions about store investments through footfall analysis.
Read Taco Bell Case Study →
7-Eleven
7-Eleven measures and optimizes real-time KPIs including pedestrian traffic analysis for property evaluation and door count conversion rates at over 10 NYC locations.
Read 7-Eleven Case Study →
#2 Outlet Operator in North America
The second-largest outlet operator in North America optimizes guest experiences across their retail destinations by measuring parking utilization, vehicle flow tracking, people counts, guest dwell times, and restroom usage analytics.
Read Outlet Operator Case Study →Everything footfall analytics should do, and actually does.
Precise counts from your existing cameras.
Evaluate property performance and reduce investment risk across sites.
Identify peak patterns and optimize staffing in real time.
Benchmark across locations to replicate what works.
Multi-Zone, Multi-Entrance Counting
Count independently across every entrance, exit, or zone. Understand where traffic concentrates and when, down to the minute.
Real-Time Alerts & Thresholds
Set capacity thresholds and receive instant alerts when visitor counts spike or drop. React before problems compound, not hours later.
BI & POS Integration
Push footfall data into Tableau, Power BI, Snowflake, or your POS via REST API. Safari AI fits into your existing analytics stack.
Cross-Location Benchmarking
Compare footfall across every site in your portfolio. Identify top-performing locations and replicate what's working organization-wide.
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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