Monitor service speed, attempted ingredient theft, kitchen operations, service standards and compliance with process sheets using AI and existing cameras.
The system analyzes the dining area, kitchen and pickup zone. It identifies queues, delays, procedural violations and suspicious operations. It notifies responsible staff and produces reports for each location.
Without having to constantly review camera recordings manually.
Suitable for individual locations, restaurant chains and franchises. Integration with an internal server and ERP systems is possible.
Costs rise for reasons beyond production costs. Some losses occur every day in full view of the cameras.
Guests wait too long for orders, and some leave without buying.
A manager cannot simultaneously monitor tills, kitchen, dining area and pickup.
The result is lost revenue, reduced capacity and negative reviews.
Solution: AI measures queues and waiting time and warns when standards are exceeded.
Service is fast on one shift, while another has constant delays and standards violations.
Mystery shoppers and spot checks do not show what happens every day.
The result is unpredictable service, recurring errors and extra monitoring costs.
Solution: the system records measurable events and deviations from defined procedures by shift and location.
A vacant table remains uncleared, and a guest waits for a server's attention.
There is no objective data on cleaning time or first contact with guests.
The result is lower table turnover and lost potential orders.
Solution: AI tracks table occupancy, cleaning delays and first service, notifying the floor manager in real time.
Orders accumulate, dishes wait at pickup and are sometimes given to the wrong guests.
The POS shows the order, but does not always explain which physical stage caused the delay.
The result is waste, rework, returns and late deliveries.
Solution: cameras combined with the order system help find bottlenecks and check order completeness.
Food, consumables and finished products go missing.
Inventory checks reveal discrepancies only afterward, and manually finding the event in camera footage takes time.
The result is increased food cost, shortages and unexplained losses.
Solution: the system flags suspicious movements in defined zones, matches events with records and sends them for review.
Staff forget protective equipment, skip visible cleaning steps or depart from the operation sequence.
Continuous visual monitoring requires a manager's presence.
Solution: AI detects visually identifiable violations and saves supporting footage.
Choose tasks that affect your venue's economics. Each can have its own monitoring rules, notifications and reporting.
The system counts people in a queue, measures waiting time and sends a notification when the queue exceeds a set threshold.
For: fast food, cafés and venues with till areas.
Analytics for seating, table vacancy and cleaning time, and delays before first contact with guests.
For: restaurants, table-service cafés and family restaurants.
Identifying kitchen-stage delays, finished dishes accumulating at pickup and overloaded work zones.
For: restaurants and dark kitchens.
Comparing recognized items at pickup with POS or KDS order contents where the camera angle is suitable.
For: delivery services, quick-service restaurants and takeaway cafés.
Checking head coverings and other required protective equipment, along with visually identifiable procedures.
For: all food-service venues.
Detecting unstaffed tills, staff arriving late for shifts, unattended pickup zones and deviations from the required operation sequence.
For: coffee shops, cafés, fast food and franchise chains.
Detecting suspicious events in storage, refrigerated and staff areas. Matching them with operational records through integration.
For: restaurants, chains and central kitchens.
Detecting uncleared tables, abandoned trays, visibly overflowing bins and cleaning delays.
For: fast food, food courts, cafés and restaurants.
Courier waiting time, accumulated orders, handoff delays and pickup-zone load.
For: delivery, dark kitchens and QSR.
Comparing locations by service speed, workload, standards deviations and shift performance.
For: restaurant chains, franchises and management companies.
Cameras already record what happens. AI catches violators in the act.
The system continuously analyzes video, recognizes events and reports situations requiring management attention.
Instead of watching hours of archives, managers receive a specific event: where the problem arose and what needs checking. A recording clip accompanies the notification.
We measure impact through changes in business metrics.
The system connects to the venue's video feeds, analyzes events and brings the results together in the manager's interface.
Monitoring zones: entrance and tills, dining area and tables, kitchen, pickup zone, warehouse and staff areas.
What the business receives: immediate notifications of discipline and process violations, event history, shift analytics and comparisons across locations.
Scenario: seven people form a queue in a café. The system detects that the defined limit has been exceeded and notifies the manager.
What the manager sees: queue start time, waiting duration, till-area load and supporting footage.
Result: an opportunity to respond to overload earlier and allocate staff across shifts.
Scenario: finished orders accumulate at pickup. The system detects the delay and links it to order data where POS/KDS is connected.
What management receives: stage durations, delay notifications and a report on the busiest periods.
Result: identifying bottlenecks in preparation, assembly and order handoff.
Scenario A: a cook is in the work zone without the required head covering. The system records the visible violation and notifies the responsible person.
Scenario B: food is moved from storage outside the prescribed procedure. The system flags the event for review, while inventory integration helps match it with records.
Result: fewer missed violations and faster incident review.
One screen can show metrics for a selected period:
Data is grouped by venue, shift and period. Managers can move from a metric to a specific event.
We connect to compatible cameras and recorders, configure video processing and integrate data with POS, KDS and BI systems where needed.
The system can run on the client's servers inside a private environment, or we can organize and maintain separate infrastructure.
We select a venue and 2–3 priority tasks, check video quality, configure analytics and record baseline metrics.
The pilot measures event recognition accuracy. We then decide whether to expand the system.
You do not need to work out equipment, servers and video processing yourself. We will select architecture for your existing system and security requirements.
Deployment within the company's private environment where the infrastructure meets technical requirements.
For large chains with their own IT teams and increased data requirements.
We select and rent the necessary compute resources, configure the system and maintain its operation.
For companies without their own server equipment or a dedicated IT team.
Additional benefits:
We identify loss-causing processes: queues, service, kitchen operations, hygiene procedures or shortages.
We study camera positions and specifications, video quality, zone layouts and required integrations.
We select scenarios, site, budget, accuracy criteria and business KPIs.
We configure models, event rules, notifications, the interface and access.
We compare before-and-after metrics, assess notification usefulness and calculate the economics.
Once effectiveness is confirmed, we deploy to the remaining venues.
Technical support. We monitor uninterrupted, reliable system operation.
Tell us what you want to monitor. We will discuss technical feasibility, suggest suitable scenarios and define the pilot scope.
How many venues do you have?
Which task do you want to address first?
Yes, if their specifications, positioning and stream quality support recognition of the required events. This is checked before deployment.
Not always. Camera repositioning, another angle or computing resources may be needed for video processing.
Integration is possible where suitable APIs, access rights and technical compatibility exist. We define its scope during assessment.
Yes. Centralized reporting and comparisons between venues can be organized.
The system can flag defined suspicious events, but must not automatically conclude that a person is guilty. A responsible person reviews the incident.
We configure video processing, storage and access with applicable law in mind. Core people-counting and queue-monitoring scenarios do not require facial recognition.
Cost depends on locations, cameras, selected scenarios, integrations and deployment model. After assessment, we can estimate the pilot and subsequent rollout.