Enterprise Face Recognition SDK Built for Private Deployment
Add high-performance 1:1 face verification and 1:N face identification to your applications with FacePlugin. Built on NIST FRVT-evaluated algorithms, the SDK delivers fast, accurate biometric matching entirely on infrastructure you own – so every face template and biometric record stays private and under your control.
Production-Grade Facial Recognition That Runs Where Your Data Lives
FacePlugin’s Face Recognition SDK gives development teams production-grade facial recognition that runs on your own servers, private cloud, or directly on a mobile device – wherever your data already lives. Under the hood it converts a face image into a compact, irreversible biometric template, then compares templates either for 1:1 verification (does this face match the one on file?) or 1:N identification (which identity in a gallery of millions does this face belong to?).
Because the SDK is deployed on-premises, biometric data and every match decision stay off third-party APIs entirely. That makes it a strong fit for banks, government agencies, healthcare providers, and any organization bound by strict data-residency, privacy, or air-gap requirements. You license the software once and run unlimited matches afterward – there are no per-call fees and no usage metering to track.
Precise 1:1 Verification and Large-Scale 1:N Search
Confirm identity in real time for login and onboarding, or search a single face against a gallery of millions of templates in milliseconds. Both modes draw on the same underlying models, so you can scale from simple verification to large-scale identification without a re-integration.
Enrolled Face
Live Capture
Query Face
Everything a Face Recognition Integration Needs
From detection and alignment to template extraction and comparison, all in one SDK.
1:1 verification
Confirm a face matches a registered template with high confidence for login, payments, and access control.
1:N identification
Locate a person inside a gallery of millions through fast, scalable template matching on your own hardware.
On-premises server
Deploy on Linux with Docker; biometric data and match results never leave your infrastructure.
Liveness-backed matching
NIST-evaluated face recognition combined with presentation-attack detection stops photos, videos, and masks.
On-device mobile
Run face recognition fully offline on iOS, Android, Flutter, and React Native, with no round-trip to a network.
Fast matching
Sub-second template extraction and comparison keep the user experience smooth at any scale.
Deploy on Your Servers or Directly on the Device
Run the server SDK on your own Linux backend, or embed the native library on Android, iOS, Flutter, C++, and .NET for fully offline recognition. Whichever path you choose, biometric templates never leave an environment you control.
- Server SDK (Linux / Python) for your backend
- Air-gapped and VPC-friendly deployment
Frequently Asked Questions
Does FacePlugin send biometric data outside our systems?
No. Every stage of face recognition and biometric processing happens within your own servers, private cloud, or on-device environment, so your data always stays under your control.
What’s the difference between face verification and face identification?
Face verification (1:1) compares two faces to confirm they belong to the same individual, while face identification (1:N) searches one face against a database to surface a matching identity.
Which development platforms does the SDK support?
FacePlugin ships native SDKs for Linux, Android, iOS, Flutter, Windows C++, and .NET, so you can integrate seamlessly into your applications without relying on cloud APIs.
How reliable is FacePlugin’s face recognition?
The SDK runs on algorithms evaluated in industry-recognized benchmarks, and its configurable matching thresholds let you tune the balance between security and usability for your own use case.
Are there usage-based or transaction fees?
No. Once the SDK is licensed, you can run unlimited face matching and verification on your own infrastructure with no per-call or per-match charges.
Integrate Face Recognition in Three Steps
Enroll
Capture a face, generate a biometric template from it, and store the resulting vector in your own database.
Match
Compare a live capture against a single template (1:1) or the entire gallery (1:N).
Decide
A similarity score and threshold decision come back for your application to act on instantly.
Pairs Well With
Deploy Biometric AI on Your Own Terms
Talk to our team about on-premises face recognition, liveness, and eKYC — or dive into the developer docs.