AI video analytics for textile and garment factories
For factory owners, compliance managers and plant heads running sewing floors, dye houses and finishing halls with CCTV already installed. Eye AI runs on a computer at your factory, reads those camera streams and logs entries into machine and dye zones, people lingering near hazards and counts at floor entrances, each with a snapshot and time. It gives audits and buyer inspections a record instead of a promise.
What goes wrong on sites like yours
People enter machine or dye areas that should be limited to trained staff.
Walkways and fire routes get stacked with fabric, trolleys or cartons.
Buyer and brand audits ask for proof of controls that exist only on paper.
Floor entrances are crowded at shift change and nobody has counts.
A camera is down for hours and the gap is found at the worst moment.
What Eye AI does here
| Analytic | What it does on your site | Status |
|---|---|---|
| Restricted-area alerts | Logs entry into machine, dye or store zones you mark | Live |
| Line crossing and counting | Counts people in and out at floor entrances | Live |
| Loitering detection | Logs people staying in a hazard area longer than your threshold | Beta |
| Nothing-is-silent safety net | Shows movement the AI could not name | Live |
| Stream health | Records whether each camera was working | Live |
| Event history and reports | Searchable history with CSV export | Live |
| Blocked exits and fire routes | Flags objects left in exit zones | Launching with pilot partners |
| PPE compliance | Helmet and vest checks in defined areas | Launching with pilot partners |
A day on your kind of site
Imagine a garment unit with a cutting hall, a dye area and one main floor entrance. The compliance manager marks the dye area as restricted, sets a loitering threshold near the boiler zone and draws a counting line at the entrance. During the shift, a visitor steps into the dye area; the entry is logged with a snapshot. Near the boiler, a person remains still beyond the threshold and a loitering event appears, flagged as Beta so the manager checks the image before acting. At shift change, the line shows how many people passed in each direction. Before the next buyer audit, the manager exports the zone-entry history to CSV and attaches the camera uptime record.
Reports and evidence you get
- Zone-entry and loitering events with snapshots
- In and out counts by hour at floor entrances
- Day-by-hour grid and CSV export
- Camera uptime history for audits
Why existing cameras matter here
Most units already have cameras over the floors and exits. Eye AI reuses those through one on-site computer, so there is no re-cabling and footage stays inside your premises.
Honest limits for this industry
- Lint, dust and steam in the air, plus bright windows, reduce accuracy.
- Dense rows of seated workers hide people behind one another and counts may be missed or merged.
- Loitering is Beta and has not been validated on large amounts of real footage.
- Per-shift headcount is raw entrance counts, not a finished shift report.
- Blocked-exit and PPE checks are launching with pilot partners and are not available today.
Questions
Can it detect blocked fire exits?
Not today. It is launching with pilot partners.
Does it check PPE?
Not yet. PPE is launching with pilot partners.
Will it work with our dense sewing floors?
Overhead and angled views vary. The free check tells you what is realistic.
Does it track individual workers?
No. It logs events and counts, not identities.
Which of this looks like your site?
We read every request and reply within 24–48 hours (working days, Monday to Friday) with questions and a proposed solution.
Request a solution