Staff filtering and unique visitors with anonymous re-identification.

A unique ID per person - across cameras, across visits, completely anonymous.

KSI has developed proprietary anonymous re-identification technology that assigns a unique ID to each person, without storing images or personal data. It solves two critical problems at once: automatically filtering out staff so they don't contaminate your metrics, and counting true unique visitors instead of repeat visits from the same customer.

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KSI Vision · Anonymous re-id
Live
Unique visitors
6,480
+7.1% vs. yesterday
Repeat visits
1,230
Entry-exit matches
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Anonymous · GDPRStaff excluded

The two problems it solves

Without re-identification, your numbers are lying to you.

Standard people counters cannot tell who is who. They count entries - every entry. That means staff walking in and out look like customers, and a single customer who returns three times in a week looks like three different visitors. Both errors compound silently and break your conversion math.

Staff contaminate your metrics

Without re-identification, every staff member entering and leaving counts as visitor traffic. Your conversion drops artificially and your peak-hour readings are inflated. Filtering by uniform or schedule is unreliable.

Repeat visits inflate your traffic

A loyal customer who visits 3 times this week looks like 3 visitors in your dashboard. You cannot measure real reach, real loyalty, or real conversion per person.

How it works

One person, one anonymous ID - even across cameras and visits.

KSI extracts a morphological signature from each person - anonymous body and gait features, never facial data. The same person captured by two different cameras, or returning some time later, gets matched to the same anonymous ID. The original images are never stored: only the signature and the ID.

What this unlocks

Capabilities only re-identification makes possible.

True unique visits

Stop counting the same person multiple times. Get accurate reach by store, by zone, by mall - and measure real loyalty.

Automatic staff exclusion

No uniforms, no manual tagging. Staff are recognized from their behavior pattern and excluded from conversion math.

Real per-visitor dwell time

Measure how long each individual stayed - not an average smudged across all entries. Spot bouncers, browsers and converters separately.

Full journey reconstruction

If a person passed through this zone, then that one, then left - we know. Reconstruct the actual path each customer took.

Customer-level conversion

Match transactions to behavior at the person level: who looked, who tried, who bought, who came back.

Privacy-safe by design

No facial recognition. No personal data. No image storage. The same anonymous ID is the only thing that travels between cameras.

Side by side

What you measure with vs without re-identification.

Without re-IDWith KSI re-ID
Visitor countInflated by staff and repeat visitsTrue unique visitors, staff excluded
Conversion rateDiluted by non-customer trafficReal conversion per unique customer
Dwell timeAveraged at the doorMeasured per individual visitor
Customer journeyAggregate flow onlyReconstructed path per person
Privacy complianceOften relies on facial recognitionAnonymous body signature, GDPR-compliant

By industry

What re-identification unlocks across industries.

Retail

Real conversion per customer. Bouncing-customer detection. Dwell time per individual. Loyalty measurement based on actual return visits.

Shopping malls

Unique mall visitors vs repeat visits. Path reconstruction across zones, floors and tenants. Per-tenant capture rate from real foot traffic.

Airports

Passenger journey from entry to gate. Real wait-time per passenger across queues. Re-encounter rate at non-aero retail.

Supermarkets

Filter out staff and stockers. Measure shopper dwell vs employee movement. Per-customer basket projection from behavior.

Privacy by design

Anonymous from the first frame to the last byte.

KSI re-identification uses anonymous morphological features only - never facial data. Original images are never stored. The unique ID generated for each person is locally scoped, cannot be reverse-engineered into a personal identity, and complies with GDPR, ISO 27001 and the strictest privacy regulations worldwide.

GDPRLGPDCCPAISO 27001Privacy by DesignAnonymous ID

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