A sale walked out.
The camera had the answer.
Someone waited 41 seconds at an ice pop shop and left. Vision Ops turned that moment into an insight to help decide how to serve the queue.
Real finding · a Saturday at an ice pop shop
Data analytics with computer vision. We are starting with restaurants and food businesses, without facial recognition.
From a moment to a finding.
They waited 41 seconds and left.
Your cameras already see your business. We turn it into data.
Vision Ops is the data analytics of Alba Vision: it connects the cameras you already have and turns what happens in your operation into times, zones, findings and decisions.
In operation · we start with restaurants and food businesses
Scroll to see how it works
- What gets detectedPeople, loads or parts: everything that moves in front of the camera becomes an anonymous dot. Never a face.
- The pathsVision Ops follows each dot while it is in frame and rebuilds where it went.
- Zones and their timesThe floor is split into zones: how long people wait, how long things take and how much each one is used.
- The patternsDay after day, the peak hours and the places where everything piles up show up.
- The findingWhat matters is flagged on its own, with the frame that backs it up.
- The dashboardIt all arrives in a clear report, and you can ask it questions in your own words.
In your operation, every day.
Not a table. A sentence you can use.
- The reportEvery day, by email, with the findings in plain language.
- The evidenceThe frame behind every number.
- The checksEvery figure is verified before it is sent.
- Ask it«When was it busiest?» and it answers with your data.
Email · Daily report
Vision Ops
«You lost a sale at 6:12 pm: someone waited 41 seconds in line and left. With this volume you need another person at the counter at that time.»
A real finding, from a Saturday at an ice cream shop.
Illustration · Recreated evidence
- Joined the queue
- 18:11:19Checked
- Left without ordering
- 18:12:00Checked
- Wait time
- 41 sChecked
- Result
- 1 walk-outChecked
18:12:00 − 18:11:19 = 41 seconds
Example data: this is how every figure is checked before it is sent.
When were the most people here?
Between 6 and 7 pm: 46 people.
A day of operation, in twenty seconds.
6 pm
6 people in the queue. The hour with the longest wait.
From the first camera to the whole operation.
- AssessmentWhat you want to know and which cameras you already have.
- PilotOne camera, a few weeks and real numbers from your operation.
- IntegrationA connector on your network reads the video, with no open ports and no new cameras.
- ScalingMore cameras and more locations. Pricing is per camera.
Example
We count what happens. We recognize no one.
- No facial recognitionIt detects silhouettes and follows them while they are in frame. It does not know who anyone is.
- Encrypted and deletedThe video travels encrypted and the original is deleted on its own after 30 days.
- Only the evidenceThe moment of each finding is kept, and deleted with the rest.
- The connector is yoursIt reads only the video you authorize and you can remove it whenever you want.
We start with restaurants.
Today Vision Ops analyzes restaurants, taco shops, food trucks and food businesses. For warehouses, production lines and other operations, we build it to measure.
The pilot starts with a question.
What do you want to know about your operation?
Tell us what happens in your business and which cameras you have. We will tell you what we can measure and how to start with a pilot.