DEEPINGSOURCE

Solutions by space

A different space, a different answer.

We have built reading standards across more than 100 spaces. Pick the space closest to yours and a signal, and we will show what gets read there and how.

Request a consultationSee how my space reads

Reading standards

The same signal reads in reverse from space to space.

Three minutes

A good signal in a café. Right before a walkout at the till.

Six in line

An incident in a convenience store. A hit in a popular gallery.

A long route

A sales opening in a hypermarket. Pure cost in a warehouse.

What we sell is not camera analysis. It is that reading standard.

Space atlas × signal dictionary

Twelve spaces × six signals.

Pick a group to unfold just that set. Pick a cell to open how that pair is read.

Convenience stores · Drugstores · Unmanned stores · Hypermarkets

How much people pile up at one point. It shows first at checkouts, entrances and popular zones.

Where the scale splits · Acceptable queue length differs by sector, and in event spaces crowding is a hit.

Showing 4 of 12 spaces

Current pairRetail storesConvenience storesQueue & crowding

Six in line is an incident here. Shoppers leave instead of waiting.

Normal range
Even at peak the line stays within three.
When it counts as off
The line passes the threshold while self-checkout sits idle.
What operations do
Guide shoppers to self-checkout, or move staff over.
Talk to us about this pair

How we read it

Anonymization comes first.

A comparison view where identity is erased from the source footage while people and behavior remain detectedActual result

01 · At input

Identity is removed, behavior stays

The original is not stored. We read what is happening, not who it is.

Example floor plan

Each camera on its own

???

One path connected by SAAI

123
  • Behavior marks
  • Stop
  • Pick-up
  • Backtrack

02 · Across cameras

Scattered views join into one route

The same person, the same trip. Where they stopped, picked up and doubled back all stay on one plan.

Screen example
Six in line · checkoutNow

The threshold is crossed and two self-checkouts are idle. Consider guiding shoppers over first.

See the groundsIs it the same at other stores

03 · On that space’s scale

A next action, proposed with its grounds

AI proposes. A person decides.

* 01 is an actual anonymization result. 02 is an example floor plan and 03 is a screen example.

Spaces not listed here

Even a space we have never seen has an axis.

People flow, stop and double back anywhere. Finding that axis follows four set steps.

  1. 01 · 1–2 weeks

    Observe

    Only anonymized flow, on the cameras already installed. That becomes the baseline.

  2. 02 · Together

    Agree the scale

    What counts as normal and what counts as an incident is known best by the people running it.

  3. 03 · Pilot

    Validate in one place

    One site, not every site. The result decides whether it spreads.

  4. 04 · After that

    It becomes that space’s scale

    The scale of a new space becomes the starting point for the next one.

Tell us what kind of space it is and we will come and look at it with you.

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Problems we have solved on site

Start with the problem closest to your space

Find it in the list

Narrow by industry

21 problems

Neither route found a close problem?

Tell us about your space and what is getting in the way. We will start with the closest case.

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Measured cases

See what changed after the change.

5 case studies

Convenience · Unmanned stores

A hypothesis, a shelf change, and a second measurement

Centre aisle · biscuit sales

The back zone drew few visits, and the centre aisle held no clear category focus→Ice cream moved to the back zone, snacks and biscuits to the centre aisle, then we measured again under the same conditions
Read the case

Fashion · Sports

Footfall went up. Walk-ins went down

Footfall during the holiday

The team had not seen the pattern where holiday crowds push the capture rate down, nor the gap between the core target and the age band actually walking in→The weak capture windows and the target gap became the basis for the next holiday plan: entrance display, in-store promotion and targeted advertising
Read the case

Drugstore

Self-checkout went in. Face-to-face service did not go down.

Checkout duration (three months in · range across stores)

Queueing and paying at the counter took a long time→Checkout duration fell sharply, while staff and shopper contact at the fixtures held or rose, store by store
Read the case

Change rates are measured values. Store names and absolute figures are reconstructed to protect customers.

Explore adoption

Tell us what is getting in the way. We will help you find where to start.

Tell us what kind of space you run and what needs attention. We will start with a similar case.

Request a consultationSee how my space reads