We build real-time video analytics that convert continuous streams into structured events, behavioral insight and cross-camera understanding, so operators act on signals instead of watching screens.
Intelligent video analytics is the layer above raw perception. Detection tells you a person is in the frame; analytics tells you that person crossed a restricted line at an unusual hour, lingered longer than expected, or appeared on three cameras in sequence. It combines detection, tracking and scene logic into events with business meaning.
Most organizations already own more cameras than anyone can watch. Footage is reviewed after an incident, if at all, and motion-based alerts generate so many false triggers that operators learn to ignore them. The video is an asset that is almost never converted into operational knowledge.
Our video analytics service delivers systems that watch continuously, apply configurable rules on tracked trajectories, correlate activity across cameras and surface only the events that matter, with the evidence attached.
The building blocks we combine for each engagement. Scope is defined by the problem, not by a feature list.
Line-crossing, zone intrusion, loitering, abandoned objects and direction-of-travel rules evaluated on tracked trajectories rather than raw pixel motion.
Dwell time, path analysis, group formation, running, falling and other patterns derived from how tracked objects move and interact over time.
Density estimation and occupancy counting for spaces where individual tracking breaks down, with threshold alerts for safety and capacity management.
Re-identification and spatial calibration link observations across overlapping and non-overlapping cameras into a single site-level picture.
Temporal smoothing, cooldown windows and cross-rule logic that prevent a single incident from generating dozens of alerts.
Each event stores clips, thumbnails and structured metadata so incidents can be reviewed, audited and searched by attribute instead of by scrubbing timelines.
A reliable analytics system separates what the model sees from what the business cares about. Keeping those layers distinct is what makes the system tunable without retraining.
RTSP and ONVIF streams are decoded with hardware acceleration, frame rates are scheduled per camera based on scene activity, and camera geometry is calibrated so pixel positions map to real-world zones.
Optimized detectors run per stream and a multi-object tracker maintains identities, producing trajectories with position, velocity and class attributes for every object.
Zones, lines, schedules and behavioral conditions are expressed as configuration, evaluated on trajectories in real time and tuned by operators without code changes.
Events from multiple rules and cameras are merged in a stateful processor that suppresses duplicates, attaches evidence and assigns severity.
Events reach dashboards, video management systems and webhooks through APIs, and operator feedback on each alert feeds back into rule tuning and model improvement.
Practical applications we design for, each anchored to an operational decision.
Intrusion, tailgating and loitering detection with far fewer false alarms than motion sensing.
Crowd density, flow and occupancy monitoring for stations, venues and civic spaces.
Queue formation, dwell at displays and footfall patterns across a store estate.
Detecting line stoppages, blocked walkways, forklift and pedestrian interactions and unsafe behavior.
Platform crowding, wrong-direction movement and unattended object alerts in high-throughput environments.
Operators respond to events, not to hours of unwatched footage.
Rules are configurable by your team without retraining models.
Events arrive with clips and metadata, ready for review and audit.
One analytics layer spans new and existing camera estates.
Cross-camera correlation gives a site-level view, not isolated feeds.
Alert volume stays manageable through deduplication and severity scoring.
Our five-stage process, applied to this service.
We map camera coverage, review historical incidents and define which events matter, how fast they must be detected and who should receive them.
Zones, event types, severity levels and integration points are specified alongside the compute placement for each camera group.
Detection, tracking and rule evaluation are built and tuned on recorded footage until false-alarm rates meet the agreed threshold.
The system runs alongside existing operations on a subset of cameras, integrated with your VMS or control room tools, before full rollout.
Operator feedback on each alert is tracked and used to adjust rules, retrain models and extend coverage to new scenarios.
Person detection, multi-object tracking and zone intelligence that turn passive camera estates into active monitoring systems.
People counting, traffic analytics and public-space monitoring that give city operators a live, measurable view of how spaces are used.
Customer movement, queue and shelf analytics that give physical retail the operational visibility e-commerce takes for granted.
Tell us what you wish your cameras would tell you. We will map it to detection, tracking and rules, and show you what it takes to deliver.