Human factor
Violations are noticed after the fact, and service quality depends on the attention of the manager and shift lead.
AI video analytics for restaurants, cafes and HoReCa chains
AI Hospitality Management Platform
STATANLY turns existing IP cameras into an operational video analytics system with AI scenarios, events, alerts, KPIs and integrations for service, kitchen, staff, cash desk and guest experience management.
5-15%reduction of hidden losses and missed revenue
10-20%growth in service speed and table turnover
24/7control of service, kitchen, cash desk and staff
IP camerasworks with existing video surveillance
iiko / r_keeperintegrations with POS, CRM, BI and reporting
Cloud / On-Premquick launch and network scaling
HoReCa video analytics
Video analytics for restaurants and cafes: camera-based control of key operations
The STATANLY AI platform analyzes video streams from existing IP cameras and turns video surveillance into restaurant operations analytics. It helps automate control of staff, kitchen, cash desk, queues, guest flow, food pickup and service standards — from a single venue to a HoReCa chain.
- Staff monitoring
- Kitchen video analytics
- Cash desk control
- Visitor counting
- Queues and service speed
- Speech analytics
Background
Most restaurant processes are still controlled manually
Cameras are already installed, but are usually used only to review incidents. The manager does not see the full picture across the hall, kitchen, cash desk and staff, while service standards depend on the shift and individual employees.
Hidden losses
Guest walkouts, slow pickup, returns, write-offs and cash desk exceptions are not combined into one operational picture.
No objective KPIs
It is difficult to compare restaurants, shifts and teams by speed, standards and reasons for deviations.
Late decisions
By the time the video archive is reviewed, the issue has already affected the guest, the check or the reputation.
Where efficiency is lost
Where does a restaurant lose revenue and service quality?
Losses occur every day because of inefficient processes, staff mistakes and lack of control in key zones. AI turns video surveillance from a passive archive into an operational management loop: events, reasons, KPIs, notifications and evidence base.
Dining hall and service
Long guest waiting time, empty or dirty tables, low turnover and missed upsell.
Kitchen and pickup
Delayed food pickup, order assembly mistakes, overholding, returns and product losses.
Staff and discipline
Idle time, phone use, uneven workload, violations of uniform and service standards.
Guests and service
Leaving without ordering, low repeat visits, negative experience and no managed customer journey.
5-15%missed revenue
10-20%turnover losses
15-25%excess staff costs
24/7automatic event capture
Before
Cameras only record video
- The manager checks video selectively.
- Reports are prepared manually.
- Service speed and loss reasons remain approximate.
- Network standards are difficult to control consistently across all locations.
After
AI records events and calculates KPIs
- Queues, tables, pickup, kitchen, cash desk and staff are monitored in real time.
- Events go into a journal with frames and video clips.
- The network manager sees comparisons across restaurants, shifts and teams.
- Scenarios can be expanded without replacing cameras.
Platform capabilities
Video analytics modules for restaurants and HoReCa chains
Functionality can be enabled step by step: from one zone to a network of locations with a unified analytics center.
Staff and discipline
Presence, phone use, routes, appearance, idle time, service time and shift KPIs.
Kitchen and preparation area
Pickup speed, order contents, sanitary rules, smoke, fire, cleanliness and procedures.
Service hall
Hall load, free and dirty tables, first waiter approach, cleaning and queues.
Guests and service
Visitors, repeat visits, average dwell time, peak hours and heatmaps.
Cash desk and pickup control
Queues, order assembly speed, cash drawer opening, receipt, suspicious actions and pickup.
Speech analytics
Greeting, upsell, loyalty card, stop phrases, consultations and script compliance.
Staff
Restaurant staff video analytics: employees and shifts
The system shows presence, routes, activity, service time, idle time, zone compliance and discipline. The manager sees not only a single violation, but also repeated problems by employees, shifts and restaurants.
- presence during the shift and being in the work zone
- movement routes, idle time and service time
- phone in hand, missing badge or uniform violation
- appearance, hair, headwear and behavior in the hall
- employee, shift, zone and restaurant KPIs
Guest experience
Guest video analytics: traffic, guest journey and table turnover
The platform shows the guest journey from entry to exit: flow, waiting, seating, first contact, order, pickup, repeat visit and leaving without service.
- total flow, entry, exit and unique visitors
- hall load, occupied, free and dirty tables
- first waiter approach, waiting time and average dwell time
- repeat visits, heatmaps, peak hours and customer journey
- queues at entry, cash desk, pickup and pickup zone
Kitchen and SOP
Kitchen video analytics: cleanliness, hygiene and SOP control
AI helps control sanitary and operating standards without manual camera review: PPE, hygiene, workplace cleanliness, foreign objects, labeling, smoke and fire.
- gloves, uniform, headwear and sanitary rules
- work zone cleanliness, trash and contamination
- phone use, foreign objects and procedure violations
- labeling of prepped items, storage and order at the station
- audit of kitchen standard compliance by shifts and locations
Cash desk zone
Cash desk video analytics and suspicious activity control
The cash desk module links POS-zone events to video: cash drawer opening, receipt handling, returns, discounts, actions without purchase and procedure deviations.
- the cash drawer is open longer than allowed or opens too often
- operations without receipt, cancellations, returns, discounts and manual corrections
- phone, calculator or unrelated actions while the cash drawer is open
- linking an event to a frame, video clip, shift and employee
- notifications to the manager and statistics by cashiers and locations
Audio analytics
Speech analytics for restaurants: service standard control
The audio module checks not cash operations, but the dialog with the guest itself: greeting, consultation, upsell offer, correct wording, absence of stop phrases and service completion.
- greeting, polite tone, closing phrase and script compliance
- offer of seasonal menu, bakery, drinks, toppings and additional ingredients
- loyalty card, help with choice and product composition consultation
- control of stop words, prohibited wording and incorrect promises
- standard compliance metrics by employees, shifts, locations and network
Food pickup
Pickup-zone video analytics and prepared-meal control
Typical losses occur at pickup: the dish is not prepared to the standard, an ingredient is missing, the order waits too long or a hot dish cools down.
dish typeorder class recognition
standardcomparison with the visual standard
temperaturenormal / below normal / overheating
SLAtime at pickup and unserved orders
Standard compliance
Checking presentation, ingredients, garnish, decoration and visual deviations.
Order not picked up
An event is created if a dish stays at pickup longer than allowed.
Completeness error
Checking order contents and key elements before handoff to the guest.
Cold dish
Control of temperature deviations and delays between preparation and pickup.
Interfaces
Violation journal, event cards, dashboards and analytics
The interface separates operational work and management analytics: the operator processes events and evidence, while the manager reviews dynamics, SLA, statistics and location comparisons.
Violation journal
A unified event feed with filters by restaurant, zone, status, violation type, employee and time.
Event card
Evidence frame, video clip, event ID, time, camera, responsible person and processing history.
Operational dashboards
Queues, cash desk, kitchen, pickup, tables, staff and SLA in one manager view.
Reports and statistics
Comparison of locations, shifts and teams, violation trends, service dynamics and management reports.
Implementation
From one restaurant to a unified digital network loop
The project can start with one location and a limited detector set, then expand scenarios, zones and integrations.
Pilot
Start with a small pilot and clear algorithms
For the first stage, we select 3-5 scenarios where results can be easily checked by video, events and KPIs. After the pilot, we add new detectors and scale the solution to the network.
guest and unique visitor counting
queue, waiting and service speed
kitchen order, PPE and sanitary rules
pickup zone, unserved orders and cash desk
dirty tables, first approach and table turnover
new detectors after effect validation
01
Camera and zone audit
We define the hall, kitchen, cash desk, pickup and service control points.
02
Quick start
We connect core scenarios to existing IP cameras without purchasing new equipment.
03
Events and KPIs
We configure the journal, notifications, roles, dashboards and management reports.
04
Scaling
We connect new restaurants, AI scenarios, integrations and a unified Control Tower.
Cloud / SaaS
Fast connection, cloud reports, events, notifications and centralized analytics.
On-Prem
Deployment on the customer's internal infrastructure: server, roles, archive, reports and integrations.
Hybrid
A combination of local processing, cloud analytics and a gradually expandable model library.
AI Factory
Adding new scenarios without a long development project
The platform supports a module library and tools for adding new models: new dish classes, violations, service events, zones, rules and reports can be expanded as the network develops.
labelingfine-tuningVLM/LLMsynthetic datarollout
Integrations
Connection with corporate systems
Events and KPIs can be sent to POS, CRM, BI, 1C, iiko, r_keeper, Telegram, Email, SMS and internal network management systems.
iikor_keeper1CCRMBIAPI
FAQ
Frequently asked questions about video analytics for restaurants and cafes
A concise overview of how STATANLY AI video analytics works in restaurants, cafes and HoReCa chains.
What is video analytics for a restaurant?
It is a system that automatically analyzes camera video and converts what happens into events, metrics and alerts. Instead of manually reviewing archives, managers get data about staff, guests, queues, kitchen operations, cash desk activity, pickup and service quality.
What tasks can video analytics solve in cafes and restaurants?
The system can count visitors, analyze queues and waiting time, monitor staff performance, kitchen cleanliness and procedures, cash desk events, order pickup, hall occupancy, first waiter approach and other operational KPIs.
Can we use our existing CCTV cameras?
Yes. Core STATANLY scenarios can work with existing IP cameras. Before a pilot, camera positions, viewing angles and zones are audited to determine which scenarios can be launched on the current infrastructure.
Do we need to replace the entire video surveillance system?
No. Existing video infrastructure can be used for most core scenarios. Additional equipment is only needed where the current angle, image quality or zone coverage is insufficient for reliable analytics.
Can the system monitor restaurant staff using cameras?
Yes. The platform can detect presence in work zones, routes, idle time, service duration, phone use, uniform violations and other configured events, then build statistics by employee, shift and location.
How does kitchen video analytics work?
AI scenarios monitor sanitary and operational standards including PPE and uniforms, workstation cleanliness, waste and foreign objects, phone use, labeling, station order, smoke and fire.
Can the system monitor the cash desk and POS operations?
Yes. The cash desk module links events around the POS zone with video and can detect drawer opening, returns, discounts, cancellations, no-receipt operations and other deviations, with evidence linked to a frame, video fragment, shift and employee.
Does the platform count visitors and analyze guest flow?
Yes. It can analyze entry and exit, total traffic, unique and repeat visitors, hall occupancy, waiting time, occupied and free tables, peak hours and other guest-journey indicators.
Are integrations with iiko, r_keeper and other systems available?
Yes. Events and KPIs can be passed to POS, CRM, BI, 1C, iiko, r_keeper, Telegram, Email, SMS and internal chain-management systems through available integrations and APIs.
Can the platform run in the cloud or on our own servers?
Yes. Cloud / SaaS, On-Prem and hybrid deployment models are available. A project can start with one venue and a few verifiable scenarios, then expand to new zones, restaurants and the entire chain.
Software registry
STATANLY HoReCa — software documentation
Documents covering software use, administration, installation and operation.
Pricing
All prices are in Russian rubles.
On-Prem — on-site deployment
Cloud version
Use the calculator to estimate your cloud subscription cost.
Want to test the platform at one location?
We will select 3-5 pilot scenarios: pickup, queue, cash desk, kitchen, staff or guest journey. After the pilot, we will scale to the network.