One bag, forty screens.
The feed that shows it is rarely the one being watched.
Who left this, and when?
Spot what’s left behind. Every bag. Every owner. Every minute it waits.
See it worked throughA bag on its own
is easy to miss.
In a busy space, an unattended bag looks like any other. Operators watching a wall of feeds rarely see the moment it was left, or where its owner went.
The owner is already gone.
By the time someone notices, the person who left it is out of the camera’s view.
False alarms wear people out.
Bags set down for a moment raise as many alerts as bags left for good.
What the AI reads.
Every camera feed, watched for objects that stay put after their owner leaves, with the owner’s route kept as evidence.
In
- Camera feeds
- Site layout
- Operating rules
- Staff roster
- Incident log
- Timetables
At work
- Sense Watches every camera feed as it happens.
- Understand Tracks people and objects, and links each object to the person who left it.
- Check Applies the dwell rule for each zone, so a bag at a café table isn’t treated like a bag on a platform.
- Anticipate Flags a bag as soon as its owner walks away, before the dwell limit is reached.
- Operate Alerts the nearest responder with the clip and the owner’s route.
Out
One object watch. Every alert carries its clip.
Every object.
Every owner. Traced.
Control-room operators see what has been left, for how long and where its owner went, before they decide what to do.
9 attended · 1 watch · 1 alert
| Track | Object | Status | Owner | Camera |
|---|---|---|---|---|
| Waiting hall | ||||
| ID 22 | Bag, seat row C | Alert | Owner left through Exit B, 42 s ago | CAM 03 |
| ID 47 | Rucksack, bench 4 | Watch | Owner 18 m away, at the kiosk | CAM 04 |
| ID 58 | Holdall, bench 2 | Attended | Owner seated beside it | CAM 03 |
| ID 61 | Suitcase | Attended | Owner in the ticket queue | CAM 05 |
| Café & kiosks | ||||
| ID 31 | Case, café table 6 | Attended | Owner at the counter; café dwell rule | CAM 07 |
| ID 40 | Luggage trolley | Attended | Owner beside it | CAM 07 |
| ID 66 | Shopping bags | Attended | Owner seated | CAM 08 |
| Gates & desks | ||||
| ID 52 | Box, gate desk | Staff | Staff item in the desk zone | CAM 11 |
| ID 70 | Buggy | Attended | Owner at the gate | CAM 12 |
| ID 73 | Case, gate 14 | Attended | Owner in the boarding queue | CAM 12 |
| ID 75 | Rucksack | Attended | Owner seated | CAM 12 |
14:01:36
Bag set down at seat row C by track ID 14.
CAM 03 · waiting hall14:01:37
Owner walks away. The dwell clock starts.
Track 14 · leaves a 3 m radius14:01:52
Owner leaves the hall through Exit B, towards the platforms.
CAM 03 → CAM 09 handover14:02:18
Unattended for 42 seconds. The waiting-hall limit is 30.
Rule UO-2 · waiting hall
1Alert
1Watch
9Attended
Actions taken
- AlertOfficer sent to seat row C, 14:02:30 Control room
- WatchOwner found on platform 4 and brought back for the bag Platform staff
- AttendedAlert closed: bag reunited, no threat Control room
Sign-off
- Control room operator Pending
- Duty manager Pending
Every alert ends with a person's decision on record.
Illustrative example. Site, cameras, tracks and times are fictional.
Built to watch responsibly.
Watching people is sensitive. The AI is designed around that from the start.
Movement, not identity.
It follows objects and the routes of the people who left them. No face recognition by default.
Security & trust ↗Runs beside the cameras.
On-premise or at the edge. Footage never has to leave the site.
Deployment options ↗Every alert can be checked.
The clip, the track and the rule travel with every event.
Video intelligence ↗Same records.
Other problems.
The same cameras answer other questions too.
What here isn’t safe?
Safety checks
Flag what’s unsafe or incomplete.
See how →Which animals passed, and are they hurt?
Wildlife monitoring
Identify species, spot injuries and flag poachers from camera traps.
See how →Is this part defective?
Defect inspection
Catch defects on the line, not at the customer.
See how →Bring us an hour of footage.
We’ll show you what the AI sees in it, and what it would have flagged.
Talk to us →LondonDiscovery AI Limited · United Kingdom
HyderabadReDscvry Technology Private Limited · India
ChennaiReDscvry Technology Private Limited · India