Request-driven capture
Define one to twelve image slots with a unique label and instructions for each required view.
Face Detection
Better photos. A smoother start.
A missing face or a face too far from the camera can turn a simple upload into another support conversation. VeriqoCheck Face Detection helps your service recognise common photo problems and guide a better submission. Collect the views your workflow needs and keep each result connected to the correct image.
Make the first submission more useful.
Catch missing faces, group photos and unsuitable captures before they slow down your onboarding team.
Catch common photo problems
Use face presence, count and the available capture measurements to identify submissions that need attention under your policy.
Make retries understandable
Turn returned reasons into useful guidance, such as asking for one clearly visible face instead of a group photo.
Give reviewers a better start
Keep detection evidence and completed image slots together, so your team can focus on the submissions that need a decision.
From request to structured result.
Define the request
Specify the image views needed for the use case, including clear capture instructions.
Guide the capture
The applicant sees only the requested images and completes them through a focused mobile flow.
Receive results
Each accepted slot returns its own state and detection data for downstream review or automation.
Give customers an understandable next action
An upload error leaves someone guessing. An image-level reason lets your service explain the correction at the point of capture. Match the message to the returned evidence and your requested photo rules.
Keep each result with its image
Named slots and client references help your team identify the submission being reviewed. Available measurements can support a consistent capture policy; a missing required measurement should remain visible.
Operational use cases
- ✓Remote onboarding evidence
- ✓Controlled portrait capture
- ✓Multi-angle face collection
- ✓Pre-screening image quality workflows
What the product returns
- ✓Per-image completion state
- ✓Detected face count
- ✓Orientation-normalised bounding boxes
- ✓Stable image-slot identifiers
How this check fits the platform
AI locates faces and supports capture checks. Where enabled, additional profile-photo screening assesses visible photographic form. It cannot prove image provenance or identity.
Our AI and verification approach →i
Product boundary
Face Detection locates faces within submitted images. It does not compare identities, search a stored population, or by itself prove who a person is.
Questions your team may ask.
Africa first means starting with the markets, documents and devices your customers use. Coverage and capture readiness are confirmed for your deployment; no universal document support or guaranteed compliance is implied.
Does a passed photo prove identity?
No. It means the image satisfies the applicable capture checks. Document authenticity and the relationship between a person and their document need separate evidence.
Does Face Detection establish liveness?
No. A still-image face check does not establish that a person was physically present during a live capture.
Can I request multiple photos?
Supported request-driven capture can collect between one and twelve named images. Your integration should use the limits and capture instructions supplied for its session.
Make the first step easier.
Bring your photo rules and representative submissions. Let’s define a capture journey customers understand.
Get started with VeriqoCheck