LIVEAI Development · Retail, industrial and education operators
AI Video Analytics CCTV Intelligence Development
AI video analytics built on existing CCTV, so theft, safety breaches and bottlenecks raise an alert in seconds.
- Industry
- Retail, industry, logistics and education
- Services
- AI video analytics development
- Platform
- Web dashboard, mobile apps and edge nodes
- Deployment
- On-premise, cloud or hybrid
- Hardware
- CPU or NVIDIA GPU
CH 02Overview
About AI video analytics
Every business already owns the sensor network it needs. CCTV records everything but tells you nothing until someone reviews the footage, usually days after the loss.
We build AI video analytics platforms on top of the cameras a business already has, so theft, safety violations, bottlenecks and process failures raise an alert in seconds instead of surfacing in next quarter's shrink report.
The platform covers 60+ detection types and 500+ theft patterns across 30+ industries, and runs on CPU or GPU hardware. Four systems built this way are already running on live footage.
CH 03The challenge
Recording is not monitoring
Recording is not monitoring. A typical site runs 16 to 64 cameras, but a person can meaningfully watch about four. The rest is storage: evidence gathered after the money is gone. The same footage could answer questions businesses pay consultants to estimate, such as why the queue backed up at 6pm or which shelf sat empty for three hours.
16 cameras · 4 watched. Twelve feeds go straight to storage.
Retail shrink
US retailers lost $90B to inventory shrink in 2025, with roughly $66B of it considered preventable (Appriss Retail, 2026 benchmark).
Rising theft
Average shoplifting incidents per retailer rose 18% year on year, alongside a 52% jump in organized in-store theft (NRF, Retail Theft and Violence 2025).
Cost of safety failures
A single workplace fatality costs an employer $1.3M on average, and a medically consulted injury about $44,000 (National Safety Council).
Proven payback
Roughly 85% of enterprises deploying AI video analytics report payback in under 12 months (industry ROI benchmarks, 2026).
The hard part is everything around the model
Running a detector on a video file is easy. Ingesting dozens of streams reliably, calibrating each camera, suppressing false alarms until operators trust the system, storing proof clips and getting them to a manager who has thirty seconds to act is the real work.
CH 04The platform
How a frame becomes an alert
Ingest
Connect existing RTSP, ONVIF, NVR, DVR, HTTP and cloud camera streams with no rip-and-replace and no proprietary hardware.
Calibrate
Tune each camera to its premises: angle, height, lens distortion, real-world scale, lighting and the zones that carry business meaning.
Infer
Run detection, multi-object tracking, pose, behavior classification and cross-camera re-identification.
Decide
Confirm events over time, score confidence, correlate with POS or HRMS data and clip the evidence. Without transaction data a camera can see someone leave with an item but cannot know whether they paid.
Act
Send push, SMS, email or webhook alerts in seconds, typically within two seconds of the frame, plus dashboards, trends and AI-written incident summaries. Operator corrections feed scheduled retraining.
CH 05What the cameras learn to see
Six vision primitives
Detection, line crossing, zone and dwell, pose estimation, tracking with re-identification, and density heatmaps. Every use case is a combination of these with business rules on top.
Detection
What is in frame
Line crossing
Who crossed a virtual tripwire
Zone and dwell
How long someone stayed
Pose estimation
How a body is moving
Tracking and re-ID
The same person across frames and cameras
Density heatmap
Where people gather
CH 06Alert anatomy
Actionable alerts
Each alert shows what happened, where, the proof clip, confidence over consecutive frames, a POS check, estimated financial impact and a recommended action, with options to assign or mark a false positive.
Alert routing
Theft goes to the store manager by push and SMS, fire and smoke to the site and fire panel by SMS and webhook, PPE breaches to the shift supervisor, queue overruns after 60 seconds to the duty manager, and a daily shift and loss summary to regional managers.
CH 07Capability catalog
Built from the primitives, up
Configurable dashboards
Tiles track metrics such as theft incidents, average queue wait, PPE compliance and open safety events.
Loss prevention
Shoplifting and concealment across 500+ patterns, employee theft and sweethearting, unpaid goods, till anomalies, refund fraud, repeat-offender re-identification, fuel drive-offs and self-checkout scan avoidance.
Safety and compliance
PPE, fire and smoke at ignition, slips and falls, blocked exits, restricted zones, man-down and lone-worker monitoring, forklift proximity, guarding bypass, spills, harness use and occupancy limits.
Workforce and productivity
Clock-in verification, lateness, absence from workstations, idle time, phone use, uniform compliance, task and cycle times, productivity scoring and visitor movement.
Customer experience
Footfall, queue length and wait time, abandonment, dwell by aisle, heatmaps and paths, conversion, staffing gaps, anonymous demographic bands and service-desk timing.
Operations and process
Empty shelves and planogram deviation, kitchen and drive-thru timing, order handover checks, food holding time, dock turnaround, loading verification, assembly sequence and cleaning checks.
Security and access
Perimeter breach, tailgating, ANPR/LPR, loitering and abandoned objects, fights, weapon presence, crowd surge, camera tamper and forced or held doors.
Quality and assets
Visual defect inspection, packaging and seal checks, fill levels and counts, grading, asset and tool tracking, pallet condition and corrosion or leak inspection.
Intelligence layer
Plain-language incident summaries, estimated impact and recommended actions, periodic rollups, multi-site benchmarking, anomaly detection, natural-language search across footage and exportable evidence packs.
CH 07BIndustries
Wherever cameras are already watching, there is value being missed
The underlying primitives are shared across every sector. The value is entirely specific to yours.
Retail & consumer
Shrink, footfall, merchandising
- Convenience & forecourtHigh-frequency, low-value theft against margins that shrink erases fast.concealment · drive-off · till anomaly
- Supermarkets & groceryShrink control and merchandising intelligence from the same cameras.self-checkout · empty shelf · queue
- Apparel & departmentHigh-value concealment plus fitting-room and floor conversion data.tag tamper · dwell · conversion
- Pharmacy & healthcare retailControlled-stock accountability and counter security.restricted stock · queue · access
- Smoke shops & cannabisHigh-theft categories under strict regulatory audit requirements.concealment · age check · vault access
- Malls & duty-freeTenant footfall reporting and shared-space crowd safety.footfall · heatmaps · crowd density
Food service
Speed, accuracy, hygiene
- QSR & fast foodSpeed of service is the product, and every second is measurable.prep time · handover · queue
- Drive-thruLane and window timing that POS timestamps alone cannot explain.lane time · window · ANPR
- Casual & fine diningTable turn, server coverage and front-of-house responsiveness.table turn · wait time · coverage
- Cloud kitchensMulti-brand throughput and courier handover accuracy.ticket time · courier pickup · mix-ups
- Food processingHygiene discipline and line compliance under audit pressure.hairnet / glove · zone · foreign object
- Catering & canteensPeak-load staffing and food-holding-time control.hold time · footfall · hygiene
Industrial & energy
Safety-critical environments
- ManufacturingSafety compliance and cycle-time visibility without instrumenting the line.PPE · guarding · cycle time · defects
- Oil, gas & petrochemicalConsequences are catastrophic, so leading indicators beat logbooks.PPE · restricted zone · flare / smoke
- Mining & quarryingVehicle and pedestrian interaction is the dominant fatality mechanism.proximity · fatigue · haul route
- Chemicals & pharmaGowning and procedural compliance where audits are mandatory.gowning · zone discipline · batch step
- Power & utilitiesRemote unmanned assets with high intrusion and failure cost.perimeter · thermal · lone worker
- Shipyards & heavy fabricationLarge open sites where fixed sensors cannot practically cover the work.height work · hot work · exclusion
Movement & storage
Throughput and dwell
- Warehouse & distributionDock congestion and forklift risk are the two costliest blind spots.dock turnaround · forklift · load verify
- 3PL & fulfillmentClient-level SLA evidence and pick-accuracy verification.pick verify · SLA proof · damage
- Cold chainDoor-open duration and handling compliance on temperature-critical stock.door dwell · handling · zone time
- Ports & terminalsContainer movement, yard congestion and restricted quay access.container ID · yard flow · access
- Rail & transit hubsPlatform-edge safety and passenger crowd management.platform edge · crowd · loitering
- Airports & cargoApron safety, queue prediction and restricted-zone integrity.apron PPE · queue · perimeter
- Fleet depotsYard movement, fuel accountability and pre-trip check verification.ANPR · fuel · pre-trip check
Public & institutional
Duty of care and throughput
- Hospitals & clinicsPatient safety events and ward flow, with anonymous tracking by default.patient fall · wandering · hand hygiene
- Aged & residential careFall detection and night-time wellbeing checks without intrusive wearables.fall · bed exit · wandering
- Education & trainingObjective attendance and engagement data, session by session.attendance · attentiveness · access
- Banking & branchesBranch security and queue economics in a single deployment.ATM tamper · queue · tailgating
- Government & civicPublic-building access control and service-counter throughput.access · queue · abandoned object
- Stadiums & venuesCrowd density, gate throughput and incident response time.crowd surge · gate flow · fights
Property & leisure
Experience, access, standards
- Hotels & hospitalityGuest experience metrics that no satisfaction survey captures accurately.lobby queue · back of house · access
- Casinos & gamingTable integrity, exclusion-list enforcement and floor flow.table watch · exclusion · crowd
- Gyms & fitnessOccupancy, equipment utilization and unattended-member safety.occupancy · equipment use · fall
- Construction sitesSites change daily; fixed sensors cannot keep up, but cameras can be re-zoned.PPE · fall risk · exclusion · headcount
- Residential & commercial towersLobby access integrity and common-area incident detection.tailgating · loitering · parcel theft
- Data centersCritical infrastructure where unescorted access is the primary risk.tailgating · rack access · thermal
- Agriculture & livestockCounting, condition and intrusion across areas too large to staff.livestock count · intrusion · grading
- Franchise networksOne dashboard proving brand standards are actually followed at every location.multi-site scoring · audits · benchmarks
CH 08Deployment
Where it runs, and on what
Deployment patterns
Single high-density sites with local inference, multi-site estates with an edge node per site, franchise and multi-tenant networks with full tenant isolation, and remote assets that run offline and sync when connected.
Data residency and biometric law
Inference stays local where footage may not leave a country or building, with retention, encryption and audit logging set per region. Face recognition is optional and scoped against local law, with anonymous tracking by default.
Hardware tiers
Basic analytics such as counting, zones, intrusion and dwell run on an 8-core i7 or Ryzen 7 class CPU with 16 to 32 GB RAM for about 4 to 8 cameras. Advanced analytics such as behavior, pose, PPE and re-ID need an NVIDIA RTX GPU with at least 8 GB VRAM for about 8 to 24 cameras per GPU.
Business data integration
POS, ERP, WMS, HRMS, access control and alarm panels connect via API, database connector or scheduled file exchange, making unpaid goods, register fraud and financial impact provable.
False alarm control
Per-camera zones, thresholds tuned on the client's footage, temporal confirmation across frames and an operator review loop keep precision first.
CH 09How we deliver
From feasibility audit to continuous tuning
A complete camera intelligence platform rather than a box of models, delivered in six stages in a deliberate order.
Stage 1: Feasibility audit
A free written assessment of the camera inventory, sample footage, network and use cases: which detections current angles support, which need a camera moved and what hardware is required.
Stage 2: Calibration and site survey
Each camera is calibrated per site and per use case for height, angle, distortion, scale, lighting and business zones such as tills, entrances, shelves and exclusion areas. This is the biggest factor in whether teams still trust alerts six months later.
Stage 3: Model selection and tuning
Proven detection and tracking backbones are fine-tuned on the client's own footage, lighting, uniforms and camera heights, with thresholds set against their tolerance for false positives.
Stage 4: Single-site pilot
One location, a defined detection set and real alerts reaching real people over typically four to eight weeks, with measured precision and recall before any rollout.
Stage 5: Platform build and rollout
Dashboards, mobile apps, role-based access, multi-site and multi-tenant structure, alert routing, clip storage, audit logs, integrations and billing, then site-by-site rollout with a repeatable calibration playbook.
Stage 6: Continuous tuning
Operators mark false positives and those corrections feed scheduled retraining, so the system keeps pace with changing seasons, layouts and uniforms.
CH 10Running on live footage
Four systems already in production
500+ patterns
Retail shoplifting and concealment detection
A per-person behavior classifier on live RTSP streams recognizes more than 500 distinct patterns, keeps a rolling confidence score per shopper and escalates concealment, bag-stuffing, tag tampering and group shielding to a red alert with the clip attached.
PPE compliance on a live process site
Each worker is checked for helmet and high-visibility vest with a confidence score per item. Breaches go straight to the supervisor and build a per-shift, per-zone compliance record, tuned for glare, backlight and distance on the client's own cameras.
~30 FPS / stream
Fire and smoke detection before conventional alarms
A visual smoke and flame detector on existing yard cameras flags plume formation at ignition with camera, zone and timestamp, covering open areas where point detectors cannot work.
72.67% engagement
Classroom engagement analytics
For a competitive-exam institute, each session yields attendance, minutes present, per-student attentiveness, a dominant state across nine emotion categories and an engagement status, rolled up to subject and course dashboards. The same engine powers workforce analytics.
- 60+
Breadth of detection
Detection types available across the platform.
- 30+
Industries covered
Sectors the platform has been scoped for.
CH 12Technology
The inference stack
Computer vision
ML and inference
Video and streaming
Backend
Frontend and mobile
Infrastructure
AWS
Azure
CH 12BPrinciples
What separates a working deployment from a shelved one
Camera-agnostic, always
We work with the cameras, NVRs and DVRs you own. If a specific detection genuinely needs a lens moved or added, that appears in the audit rather than after the invoice.
Calibration is not optional
Geometry decides accuracy as much as the model does. Every camera is calibrated to its premises and its use case before a single alert is switched on.
Precision before breadth
An alert stream nobody trusts is worse than no alerts. We tune for precision first, confirm events across frames, and build the operator feedback loop into version one.
Video plus your business data
Unpaid goods, register fraud, order accuracy and financial impact are not solvable from pixels alone. POS, ERP, WMS, HRMS and access control integration makes those events provable rather than guessed.
Privacy by architecture
Anonymous tracking covers most use cases. Where identity is genuinely needed it ships as a separately controlled module with consent capture, retention limits and audit trails.
Built to be handed over
Multi-tenant architecture, role-based permissions, audit logging, encrypted storage and billing — the unglamorous portion of the build that decides whether a pilot ever becomes a product.
CH 12CEngagement models
Three ways to start, depending on where you are
Start here
Proof-of-value pilot
One site, one camera cluster, a defined detection set. Ends with a measured accuracy figure on your own footage.
- Feasibility audit and calibration
- 2–4 detections live
- Alerts to phone or email
- Written accuracy report
- 4–8 weeks
Most common
Custom platform build
A full AI camera intelligence product built for your operation, owned by you, rolled out site by site.
- Web dashboard and mobile apps
- Multi-site, multi-tenant, role-based access
- POS / ERP / HRMS integrations
- On-premise, cloud or hybrid
- Source code and IP transfer
- 3–6 months to first release
For resellers
White-label SaaS
Launch your own branded video-intelligence product with tiered plans and subscription billing built in.
- Your brand, your domain
- Starter / Professional / Enterprise tiers
- Subscription billing and provisioning
- Tenant onboarding workflows
- Ongoing model maintenance
CH 13Design system
The AI video analytics visual language
A control-room palette: deep navy panels, an electric blue for interface and focus, and three signal colors reserved for status, so operators read an alert by color before they read its text. Type is IBM Plex Sans, with IBM Plex Mono for figures, step numbers and data labels.
Palette
- Signal Blue#2D8CFFPrimary actions, focus and live streams
- Clear Green#2BD98AOnline cameras and confirmed-safe states
- Amber Warning#FFC048Warnings and items awaiting review
- Alert Red#FF5A5FCritical alerts and incident clips
- Night Ink#05090FPage background
- Panel Navy#0B121DCards, tiles and panels
- Frost#E9EFF7Primary text on dark
Typography
IBM Plex Sans
Headings, interface and body
- 400 Regular
- 500 Medium
- 600 Semibold
- 700 Bold
Theft flagged in aisle 4, clip attached
IBM Plex Mono
Figures, step numbers, kickers and data labels
- 400 Regular
- 500 Medium
CAM 04 · CONF 0.94 · 0123456789
UI components
- cctv
- scan face
- siren
- shield check
- eye
- bell
- chart column
- video
CH 00Free feasibility audit
Send us three things and we will tell you what your cameras can already do
Share your camera makes and rough count per site, one or two short sample clips, and the outcome you want. We return a free written feasibility assessment covering supported detections, hardware and a realistic timeline.
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