Real-Time Intelligence for Every Pump, Every Door, Every Shift.
Safari AI connects to your existing cameras to deliver live vehicle traffic, store door conversion rates, occupancy levels, and dwell time analytics. No construction, live in under two weeks.
Turn every camera feed into a decision your team can act on.
Pedestrian Traffic Analysis
Foot traffic at locations to validate site selection.
- Verify pedestrian volume before committing capital
- Benchmark locations to find volume growth opportunities
Store Door Counts
Entries vs. pass-by traffic to surface conversion gaps.
- Spot when high foot traffic is not converting same shift
- Optimize entrance strategies on actual conversion data
Vehicle Traffic Monitoring
Forecourt vehicle volume to staff ahead of demand peaks.
- Staff cashiers before surges, not after queues form
- Forecast fuel demand by time of day and day of week
Capture Rate Optimization
Pass-by to store visit conversion, measured and actionable.
- Measure signage and promotion impact on walk-in rate
- Staff the entrance during high-traffic windows
Occupancy Management
Live in-store occupancy to manage checkout and crowd flow.
- Open additional registers before queues form
- Trigger restocking crews at defined occupancy thresholds
Dwell Time Analysis
Time spent per zone to guide product placement decisions.
- Place high-margin products where customers linger most
- Identify low-engagement zones and improve layout
Every view your operations team needs, live.
From vehicle counts at the forecourt to store door conversion rates, Safari AI surfaces the right data at the right moment and tells your team exactly what to do.
Staff your forecourt before the pump queue builds, not after.
Track vehicle volume at your pumps in real time. When inbound rate spikes, your team gets a specific staffing recommendation with enough lead time to act before customer experience is impacted.
- Live vehicle counts per pump lane updated every shift
- Surge alerts with staffing recommendations sent ahead of peaks
- Hourly trend to forecast high-volume windows 20 to 30 minutes out
- Day-over-day comparison to validate pricing and promotional changes
Find out how many fueling customers enter the store and how many don't.
Track forecourt counts alongside store door entries. When conversion falls below target, your team gets a specific recommendation to capture more of the traffic already on your lot.
- Conversion rate by hour to spot underperforming dayparts same shift
- Alerts when conversion drops during high foot-traffic windows
- Cross-location comparison to find untapped walk-in potential
- Multi-week trend to measure impact of promotions and signage
Know when your store is getting crowded and open a register before the queue forms.
Track live in-store occupancy every shift. When the store approaches your comfort threshold, your team gets a specific action so customers never wait in an unmanaged queue.
- Real-time occupancy count against your store capacity threshold
- Checkout queue alerts with staffing recommendations for managers
- Peak occupancy forecast by time of day from live vehicle data
- Restocking and cleaning crew triggers at defined occupancy levels
Find out which store areas customers engage with and which they walk straight past.
Track time spent in each zone. When high-margin areas have low dwell times, your team gets a specific recommendation on product placement or layout to improve engagement.
- Per-zone dwell time benchmarked against store targets
- Low-engagement alerts for zones customers spend less time than expected
- Product placement recommendations based on where customers naturally pause
- Before and after comparison to measure layout and merchandising changes
Guessing is costing you conversion, revenue, and customers you never knew you were losing.
Most gas stations and c-stores rely on POS data alone or gut feel. By the time a problem shows up in end-of-day sales, the opportunity to recover it has already passed.
- Forecourt vehicles leaving without entering the store with no live conversion visibility
- Checkout queues forming during peak windows because staffing is based on schedule, not live demand
- High-margin product placement guessed, not informed by where customers actually dwell
- Site decisions made on estimates, not verified pedestrian and vehicle counts
Validated against manual ground-truth counts at your deployment. If any camera view underperforms, we retune at no cost before you go live.
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; any 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 and Go Live
Models are validated against manual counts at your location. Once accuracy is confirmed, you are live with real-time dashboards and API access from day one.
How leading operators use Safari AI to drive decisions.
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.