> CAPABILITY / 01_FACE

Face Recognition.

Real-time face matching against watchlists, blacklists, and VIP lists.

Identity & AccessFEATURED

REQUEST_DEMO ALL_CAPABILITIES

CAM_04 · LOBBY_ENTRANCE

LIVE

EDGE-NODE-01 · ON-PREM

INFERENCE …

> THE_PROBLEM

Why it matters.

Manual checks at entrances depend on a guard's memory and attention. They do not scale to hundreds of people a day, and people of interest slip through.

> HOW_IT_WORKS.exec()

How it works.

DETECT

Faces in the live camera stream.

MATCH

Each face against enrolled lists on the edge box. Face images never leave your network.

ACT

Log the visit, raise an alert, or signal your access control.

LIVE

RUNNING

T+000 [DETECT] CAM_04 · faces in the live camera stream

> OUTPUT.schema()

What you get.

Data it produces

Person IDNameGenderAge rangeList (Employee / VIP / Blacklist)ConfidenceCameraTimestampFace snapshot

What it can trigger

Dashboard alert
Notification to staff by email or messaging
API/webhook to access control

> SCENARIOS.list()

Where it helps.

VIP or returning-customer recognition at reception

Blacklist alert at a store or branch entrance

Contactless staff access and attendance

Used inRetail Banking & Finance Manufacturing & Industry

> REQUIREMENTS.check()

Camera & deployment.

Face at least ~80 px wide (120 px or more recommended)
Mostly frontal, within ~30° of straight-on
Even lighting, avoid strong backlight

Privacy & compliance

Processing runs on-premise, inside your network, and video does not leave it. Access is controlled with role-based permissions and audit logs. Use should follow your internal policy and the data protection rules that apply to you, such as Indonesia's PDP Law.

> FAQ.query()