DEEPINGSOURCE

SAAI PRODUCTS

The answer your space holds, SAAI.

SAAI is an AI built to read space.

From the cameras already installed it reads behavior rather than people, and proposes what to change with the grounds for it.

Experience stays in the space, not in the payment record. A store, a showroom, a distribution center.

Request a consultationStart with the three questions

Uses existing cameras · no identity retained

How to read this page

A space always asks three things.

  1. 01SenseWhere do we look first, right now?saai care
  2. 02AnalyzeWhy did the result come out different?saai insight
  3. 03ThinkWhat should we change?saai agent

Question 01 · Sense

Where do we look
first, right now?

Nobody can watch the screens all day.

TODAY

saai care

What needs attention?

It watches stock-outs · fridge temperature · queues · odd routes.

Past the threshold, the person in charge gets told. The store that needs a hand rises to the top of the list.

What it reads
Crowding · queue · stockout · anomaly
What you get
Live detection and alerts
What it runs on
The cameras already installed
Look at saai care

A screen example. Metrics and thresholds are set to the space.

  • An empty shelf goes unnoticed and is found far too late

    A stock-out signal points to the shelf to refill first

  • Someone has to watch the monitors all day

    An alert only when something is off, and a check when you need one

Question 02 · Analyze

Why did the result
come out different?

Sales tell you the outcome. The reason stays in the space.

YESTERDAY

saai insight

Why did it happen?

Today, 30 days and a year of accumulated patterns.

Zone flow and response read on the same screen, and kept as the grounds for a decision.

What it reads
Pass-by · capture · path · dwell · gaze · pick-up
What you get
Time series, patterns, hypotheses
Unlike the POS
Pre-purchase behavior stays too
Look at saai insight

saai insight

Today

Store Analytics Dashboard

Visits peak at 2–4 PM

Est. daily sales
0.0k
Total visitors
0
Avg. dwell time
0.0min
Shelf conversion
0%

Beverage shelf dwell time is 2x the usual. New-product promotion effect confirmed.

A screen example. Metrics and thresholds are set to the space.

  • Every store runs at its own level

    Stores run to one head-office standard

  • The reason explained from experience and guesswork

    Evidence compared over the same period and the same zone

Question 03 · Think

What should
we change?

There is always more than one thing you could change.

The decision stays with the operator.

TOMORROW

saai agent

What should we do?

It points at what to change.

Every proposal comes with its grounds, and the person who runs the space decides.

What it reads
Drop-off · return · restocking · staff conversation
What you get
Priorities and proposed actions
Where the line is
AI proposes. A person decides
Look at saai agent

A screen example. Metrics and thresholds are set to the space.

  • A meeting decides what to change first, and next month’s sales tell you how it went

    Candidates arrive with their grounds, and the same metric checks the change

  • What the best store does stays in that store

    Proposed as a candidate to try in another store on the same terms

SPATIAL AI

Your space needs an AI that understands it.

Generic AI trained on text does not know your space.

SAAI reads approach, dwell, and pick-up from camera feeds.

Same Question

"Yesterday evening, which product drew the longest dwell?"

Generic AI chatbot
Type a message…

* Both screens show simulated demo data for a virtual store.

See why generic AI falls short

SAAI

Four letters, one promise

Spatial Anonymized Agentic Intelligence

Anonymized Spatial AI — everything begins on anonymization.

Four foundations, one loop.

  1. S01Sensesaai careSpatial · Reads the space, beyond the POS.
  2. 02Analyzesaai insightPuts the same signals into a time series and a pattern.
  3. A03Thinksaai agentAgentic · Points to what to change, with the evidence.
  4. 04ActPeople · robots · machinesWhere no product sits.
  5. I05Verify & LearnFolded into the next judgmentIntelligence · Gets sharper the more you use it.
05 → 01 · What you verified returns to the next sense
AAnonymizedLeaves no one identifiable. Where everything begins. All five steps of the loop turn on top of it.

What acts is not the AI. It is the people and equipment in the space. Steps 04 and 05 are where no product sits.

Three technologies underneath SAAI

Learn more
  1. 03Agentic AIAgentic AI proposes the next operating action./technology/agentic-ai
  2. 02Spatial IntelligenceSpatial AI analyzes anonymous behavior signals./technology
  3. 01AnonymizationVideo is anonymized at input (SEAL), and the original is never stored./technology/anonymizer

MULTI-STORE OPERATIONS

Many stores. One operating standard.

The three products run on the same data.

However many stores you have, the same metric compares them.

  • saai careStore-level issue detection
  • saai insightSpace-level operating analysis
  • saai agentHQ action history

On the right, branches placed side by side over the same period and the same metric.

View the enterprise package

Same period, same metric, read branch by branch

Same period, same metric, read branch by branch
Visitor mixVisitsZone movesAvg. dwell
Branch AAll · all ages1,5761,6722.9s
Branch BFemale · under 302874302.3s
Branch CMale · 30 to 492872391.9s
Branch DAll · 50 and over4302875s

Seven-day basis. What separates the branches is the visitor mix, and every figure comes from the same analysis.

CAPABILITY CATALOG

We have solved a different problem in each space. The ones nobody has raised yet, we solve together.

saai count

Footfall & occupancy

Counts who passes the door and who walks in.

See details

saai queue

Queues & crowding

Detects queues and crowding in real time.

See details

saai ads insight

Exposure and response around in-store media

Compare passersby, approach, attention, and action in one flow.

See details

04+

More modules

A problem nobody has raised yet lands here.

* Capability scope and data connections are configured around the customer environment and available data.See how each capability works across Sense, Analyze, and Think

saai count

Sense

saai care

Live occupancy and crowding, with alerts when a threshold is crossed

Analyze

saai insight

Daily, weekly and monthly footfall trends by weekday, hour and year over year

Think

saai agent

Staffing, opening hours and promotion timing proposed from forecast demand

USE CASES

Capability choices lead to changes on the floor.

These cases read different questions in different spaces, then examine the next operation under the same conditions.

Convenience · Unmanned stores

Centre-aisle biscuit sales +35%

BEFORE
Low back-zone visits · scattered shelves
AFTER
Category reset · same-condition remeasurement
Read the case

Drugstore chain

First shelf by age and gender

BEFORE
Experience-led display
AFTER
First shelf by customer segment
Read the case

Shopping mall · large-format retail

Entry inflow and dwell heatmaps

BEFORE
One combined entrance total
AFTER
Entry-by-entry inflow · dwell zones
Read the case

What should your space start with?

Tell us about your space and challenge. We will help choose the right product.

Request a consultationSee how my space reads