Sold by: Oz Forensics
Deployed on AWS
OZ Biometric Liveness combines advanced AI-driven liveness detection with biometric face-to-face media verification, secure and seamless user authentication against spoofing and deep-fake threats.
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Overview
OZ Biometric Liveness is an enhanced AI-powered authentication solution that extends the capabilities of Oz Liveness with biometric face verification based on media comparison. It allows organizations to validate user identity by comparing two independent media sources in real time — ensuring that the same person appears in both. This feature is designed for high-security scenarios such as KYC, remote onboarding, and transaction authorization.
Fully compliant with ISO/IEC 30107-3 standards, OZ Biometric Liveness employs advanced AI models to detect spoofing, replay, or manipulation attempts, providing unmatched accuracy even in low-bandwidth environments through offline mode support. Whether integrated into financial, governmental, or healthcare systems, OZ Biometric Liveness delivers a seamless user experience with robust fraud prevention and top-tier biometric security.
Highlights
- Instant, secure liveness verification with biometric face verification for enhanced identity assurance anti-spoofing and anti-deep fake protection.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24 LTS
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
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Dimension | Description | Cost/unit |
|---|---|---|
Per one completed Liveness analysis method call | - | $0.07 |
Per one completed Face Matching analysis method call | - | $0.07 |
Per one completed transaction with Liveness Check and/or Face Matching | - | $0.14 |
Liveness Check | Per one completed Liveness analysis method call | $0.07 |
Face Matching | Per one conclusive Face Matching analysis method call | $0.07 |
Dimensions summary
This listing charges by usage, so you pay per method call rather than a fixed subscription. Two check types are billed separately. Liveness Check counts each completed Liveness analysis method call, which confirms a real, live person is present. Face Matching counts each conclusive Face Matching method call, which compares two faces to confirm they belong to the same person. A combined dimension counts one completed transaction that includes Liveness Check and/or Face Matching together. You choose the calls your workflow needs, and costs rise with the number of completed calls you make.
Top-of-mind questions for buyers
A Liveness call is one check that confirms a real, live person is at the camera, not a photo, replay, mask, or deepfake. The default passive selfie captures in about 0.7 seconds, then server-side analysis reviews the video. Each completed check counts as one billable call.
Face Matching compares two faces to confirm they belong to the same person, such as a selfie against an ID photo. The Face Matching dimension counts each conclusive analysis call. Calls that do not reach a conclusive result are not counted under this dimension.
You can bill Liveness and Face Matching separately by call, or use the combined dimension that counts one completed transaction including Liveness Check and/or Face Matching. Separate dimensions charge each call independently. The combined transaction dimension counts the bundled workflow as a single unit.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
API version update Models update
Additional details
Usage instructions
ssh to the instance public IP and login as 'ubuntu' user using the key specified at launch time. Use 'sudo su -' in order to get a root prompt. For more information please visit the links below:
Getting started: https://oz-napi.s3.us-east-1.amazonaws.com/getting_started.pdf
Connect to your Linux instance from Windows using PuTTY: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/putty.html
Connect to your Linux instance using SSH: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html
Resources
Vendor resources
Support
Vendor support
24 hours support@ozforensics.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Support services for Oz Biometrics and Liveness API
Customer reviews
Andrew Z.
Reliable and efficient liveness detection solution
Reviewed on Nov 08, 2023
Review provided by G2
What do you like best about the product?
We needed a liveness detection solution for mobile devices for our line of work, so we were very happy that the app was very easy to set up and integrate with our systems (we mostly use the Android app). It makes it so much easier to do liveness checks. Our IT guys say that Oz Forensics face liveness detection api is very intuitive and the tech support has been a great help.
What do you dislike about the product?
I can’t say there are any critical liveness detection downsides because we’ve only been using it for a couple of months.
What problems is the product solving and how is that benefiting you?
We don’t have an extensive IT team so Oz Liveness proved to be the best anti spoofing software for us because it was the easiest to integrate with our systems. The liveness check process is basically seamless. We haven’t come across any successful attacks and that is a good facial liveness detection product in my book.
Roma K.
liveness verification in dating app
Reviewed on Jul 06, 2022
Review provided by G2
What do you like best about the product?
quality of recognition
ready-to-use sdk
fast and helpfull support
ready-to-use sdk
fast and helpfull support
What do you dislike about the product?
documentation some times not enough (but support reply fast)
What problems is the product solving and how is that benefiting you?
liveness verification in dating app