Best Deepface Detection API Providers in India (2026)

Picking a deepface detection API is not like picking any other KYC provider. Some tools only do face match or liveness. Others can spot AI-made faces, face swaps, and other fake media. If you pick the wrong one, fake identities can still slip through your checks.

 

To make this easier, we compared the major deepface detection API providers in India. We looked at what they actually offer to the public, how they detect fakes, how they integrate, and how well they fit digital identity verification.

How We Picked These Providers?

This list is based on product pages, developer docs, and real capabilities. We compared providers on a few simple points: do they have real deepface detection, what kinds of fakes they catch, whether they offer an API, how well they support digital KYC and video KYC, their track record in identity verification, and their fraud prevention features. It is not ranked by company size. It is ranked by how well each one handles deepfaces for digital onboarding.

List of 6 Best Deepface Detection API Providers

Here is the list of providers who offer the best Deepface Detection API:

Surepass

Surepass has a Deepface Detection API made to catch AI-made and manipulated face images before they enter your flow. It works with Face Match, Liveness, and Video KYC to make onboarding stronger. You send a selfie, and it returns a score with risk signals, so you can approve or reject users automatically without a manual review on every case.

 

Deepface Detection Highlights

• Detects AI-generated faces
• Detects face swaps
• Detects fake or manipulated selfies
• Catches video replays and masks
• Returns a score with risk signals
• Real-time, with results in seconds and bulk support
• Plugs into KYC and Video KYC through an API

HyperVerge

HyperVerge offers deepface detection as part of its identity verification platform. It focuses on spotting AI-made faces, deepface videos, replay attacks, and injection attempts during onboarding. It works together with face authentication and liveness, so it suits companies that want extra cover against AI-powered fraud in remote checks.

 

Deepface Detection Highlights

• AI-generated face detection
• Deepface video detection
• Replay attack detection
• Injection attack detection
• API and SDK integration
• Works with liveness and face authentication

Signzy

Signzy offers a Deepface Detection API inside its fraud prevention platform for financial firms. It checks videos, images, and voice recordings, not just photos. It catches AI-made content, face swaps, fake ID photos, altered selfies, and voice spoofing before a user is verified. It runs in real time, uses encryption, and fits into your existing onboarding.

 

Deepface Detection Highlights

• AI-generated face detection
• Face swap detection
• Video deepface detection
• Voice spoofing detection
• Altered selfie and fake ID detection
• Real-time checks, encrypted, REST API

IDfy

IDfy combines face verification, liveness, and AI-based fraud detection to catch suspicious onboarding attempts. Its public offering leans more toward identity verification than a standalone deepface API, but its face technology is built to make remote onboarding safer and cut identity fraud. The APIs fit easily into digital KYC.

 

Identity Security Highlights

• Face verification
• Liveness detection
• AI-based fraud detection
• Facial authentication
• REST API
• Digital onboarding support

Arya.ai (by Perfios)

Arya.ai is the AI arm of Perfios, with a dedicated Deepface Detection API that checks video, images, and audio in one call. It uses deep learning and forensic checks to spot fakes in pixels, metadata, and facial expressions, and returns an instant fraud score at upload or during a live stream.

 

Deepface Detection Highlights

• Detects deepfaces across video, image, and audio
• AI-generated face and content detection
• Instant fraud scoring at upload or live stream
• Built for high volumes
• REST API on the Arya Apex platform

AuthBridge

AuthBridge builds deepface and spoofing checks into its background verification and onboarding, rather than selling a separate deepface API. Because the check runs inside a flow made for Indian compliance, you get audit-ready records with little extra work. It suits businesses that verify identity and screen people at the same time, like in hiring.

 

Identity Security Highlights

• Deepface and spoofing checks
• Face verification and facial authentication
• Liveness detection
• AI-based fraud detection
• REST API integration
• Enterprise-scale verification

Conclusion

All of these providers help you improve identity verification and cut the risk of AI-powered fraud, but they are strong in different ways. The right one depends on your industry, your volume, and how much security you need. If you want a dedicated deepface API sitting inside a full KYC stack, Surepass is a strong first pick. If voice scams are a worry, Signzy covers voice too. For pure background checks, AuthBridge fits well.

FAQs

Ques: Which Is the Best Deepface Detection API in India?

Ans: The top options in India are Surepass, HyperVerge, Signzy, Arya.ai, IDfy, and AuthBridge. For a dedicated deepface API inside a full KYC stack, Surepass is a strong first pick. For voice deepfaces, Signzy and Arya.ai also check audio.

 

Ques: Can a Deepface Detection API Stop Video KYC Fraud?

Ans: Yes, it identifies face swaps, AI-generated faces, and replayed videos during onboarding, so a fraudster cannot pass your video KYC with a fake identity.

 

Ques: What Is the Difference Between Liveness and Deepface Detection?

Ans: Liveness detection checks that a real, live person is in front of the camera. Deepface detection checks whether that face is genuine or made by AI. Liveness stops photos and masks. Deepface detection stops AI faces and face swaps. Most businesses use both together.

 

Ques: Do These APIs Detect Voice Deepfaces?

Ans: Yes, Signzy and Arya.ai APIs check audio to identify voice spoofing or cloned voice.

 

Ques: How Accurate Are Deepface Detection APIs?

Ans: Leading providers often claim accuracy in the 90–95% range, though real-world results vary by dataset and conditions.