VISION AI FOR OPERATIONS
We build a vision pipeline for your sites that labels what happens on camera, checks it against your operational data and flags the cases a person should review. People stay anonymous throughout.
Simulation of the pipeline view. Every person is reduced to an anonymous shape before analysis results are stored. No faces, no identities.
Warehouses and stores run dozens of cameras, but footage only gets checked after something went wrong. Meanwhile the small breaks add up every day: a pallet left in the walkway, a shelf restocked hours late, goods leaving through the wrong door, a cleaning round that never happened. A vision model trained on your own sites watches for exactly those moments and tells the right person while there is still time to act.
Process events
Unattended items, blocked walkways, open dock doors. Each event opens a case with a short anonymised clip.
Restocking and picking
When shelves were refilled and picks confirmed, measured against the times your plan expects.
Compliance and safety
Exits, walkways, hygiene and safety zones watched continuously, with rules you define per zone.
Loss prevention
Goods set aside in blind spots or leaving through the wrong exit become cases for your team, never accusations against a person.
Process events
Unattended items, blocked walkways, open dock doors. Each event opens a case with a short anonymised clip.
Restocking and picking
When shelves were refilled and picks confirmed, measured against the times your plan expects.
Compliance and safety
Exits, walkways, hygiene and safety zones watched continuously, with rules you define per zone.
Loss prevention
Goods set aside in blind spots or leaving through the wrong exit become cases for your team, never accusations against a person.
STEP 1
A classification pipeline trained on your footage labels events in the camera feed: objects, zones, movements. People become anonymous shapes at the source.
STEP 2
Each event is matched with the data you already have, such as orders, scans, stock movements and shift plans, so the pipeline sees context, not just pixels.
STEP 3
Only events that break a rule or contradict your data become cases. Each case says why it needs a review, and your team decides.
STEP 4
People stay invisible by default. If a reviewer needs more for a non-compliant case, footage is unlocked through a documented approval and every access is logged.
No facial recognition
No identification of individuals
No individual performance scoring
Every footage access logged
Hosted in the EU or on site
Floor walk
We walk one site with your operations lead, review camera angles and agree the events that cost you most.
Zones and events
Exits, walkways, shelves and docks are mapped. Every event gets a clear rule and an owner on your side.
Train and tune
Models are trained and thresholds tuned on your footage until the cases your team sees are worth their time.
Integrate and roll out
We connect the pipeline to your WMS, ERP or shop systems, run it with your team and roll it out to the next sites.
Floor walk
We walk one site with your operations lead, review camera angles and agree the events that cost you most.
Zones and events
Exits, walkways, shelves and docks are mapped. Every event gets a clear rule and an owner on your side.
Train and tune
Models are trained and thresholds tuned on your footage until the cases your team sees are worth their time.
Integrate and roll out
We connect the pipeline to your WMS, ERP or shop systems, run it with your team and roll it out to the next sites.
For
Operations, loss prevention and site leads in retail, quick commerce and logistics
Pilot
One site, 6 to 8 weeks to the first reviewed cases
Team
Computer-vision engineer, product lead and DevOps from HUBBLR
Runs on
Your existing IP cameras, in your cloud or on site
You keep
The trained models, the pipeline, the back office and the documentation
Usually not. The models work with the IP cameras most stores and warehouses already run. During the floor walk we check angles and resolution and tell you honestly where a camera would need to move.
People are reduced to anonymous shapes before results are stored. The system does not recognise faces, does not identify individuals and does not score employee performance. If a reviewer needs to see more for a case, footage is unlocked through a documented approval and every access is logged. We document the data flow so your data protection officer and works council can review it before the pilot starts.
We train it on your footage for the events that matter to you. Common starting points are people, vehicles and objects such as bags, totes and pallets. Events are rules on top: an object staying too long in a zone, a shelf not being serviced, a walkway being blocked.
In your cloud account or on hardware on site. We deploy, monitor and maintain the pipeline, or hand it over to your team with the documentation to run it.
