Fakeradar

Name: Fakeradar
Rating: 5.0 (1 reviews)

Real-time deepfake protection for video calls

5.0•1 review•

534 followers

Real-time deepfake protection for video calls

5.0•1 review•

534 followers

Visit website

FakeRadar.io protects your sensitive data by instantly detecting whether you’re speaking with a real person or a deepfake — in real time, with just one click. Stay confident in every conversation and be sure the person on screen is truly who they claim to be.

Free Options

Launch tags:Fintech•Artificial Intelligence•Security

Launch Team / Built With

Wispr Flow: Dictation That Works Everywhere — Stop typing. Start speaking. 4x faster.

Stop typing. Start speaking. 4x faster.

Promoted

Fakeradar

Maker

📌

Hi Product Hunters!

I’m Artem Anikeev, founder of FakeRadar.io — a real-time deepfake detection tool for video calls.

Over the last 18 months, our team has built technology that instantly verifies whether the person on the other side of a call is real or fake.

How it works

Runs in real time during Zoom, Google Meet, Teams, Discord, and more.
No recordings, no audio access, no data stored — full privacy.
Detects deepfakes, static photos, and suspicious signals instantly.
Currently protects against 8 deepfake generators — and the number keeps growing.

Who it’s for?

Recruiters → avoid fake candidates in interviews.
Fintech & banks → verify high-risk clients.
Any team running video calls → protect against fraud.

Coming next

Voice deepfake detection & synthetic text analysis
A unified anti-fraud platform combining video, audio & text in real time
Adaptive learning system that auto-updates as new deepfake methods appear
Behavioral analytics: pauses, facial expressions, speech patterns
A global database of deepfake “fingerprints”
API for banks, governments & enterprises to provide large-scale fraud protection

We’d love your support, feedback, and ideas!

Try FakeRadar.io today and make sure every video call you make is with a real person.

Report

6mo ago

Scade.pro

@artem_anikeev Interesting and relevant product. Well done, guys!

I'm off to test it out)).

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6mo ago

Fakeradar

Maker

@maria_anosova Thank you so much for the kind words! Happy testing!

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6mo ago

Guitar Wiz

@artem_anikeev Particularly relevant in the present context.

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6mo ago

Fakeradar

Maker

@bijoythangaraj Thank you for your comment. It's very encouraging for all of us.

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6mo ago

Scade.pro

@artem_anikeev Guys, you're great! This product is very relevant these days. I've encountered a couple of instances of video call spoofing myself - it's sad that this happens((

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6mo ago

Fakeradar

Maker

@nastassia_k It is especially sad when older people suffer.

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6mo ago

PicWish

@artem_anikeev This is super timely especially when hiring fraud and fake client scams are on the rise

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6mo ago

Fakeradar

Maker

@mohsinproduct Yes, there's a lot of cyber fraud and it's growing. This growth needs to be stopped.

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6mo ago

@artem_anikeev sounds like something we need!

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6mo ago

Fakeradar

Maker

@islam_midov1 Not everyone needs this today, but I'm afraid that everyone will need it tomorrow.

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6mo ago

Wow, really love the idea! It's getting really hard to spot deepfakes, so this tool could be a real lifesaver for someone :)
Does it work on mobile devices?

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6mo ago

Fakeradar

Maker

@helga_impalpable Thank you for your words of support! The mobile version is currently in development. We'll make it for both Android and iOS.

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6mo ago

Fakeradar

Maker

@helga_impalpable We plan to release a mobile app for Android this year.

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6mo ago

minimalist phone: creating folders

When I saw that product, I was just thinking whether there was some workaround to not be detected :D How did you test it against some speculators who would like to cheat this system? :D

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6mo ago

Fakeradar

Maker

@busmark_w_nika The neural network learns from the examples we provide it. To do this, we had to understand which deepfake generators are most commonly used by scammers and delve into each one. We now repeat this process constantly.

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6mo ago

This is a great and much needed solution. Congrats guys ! Curious to know if Fakeradar is capable to detect fakes in group calls as well as a single candidate/client calls ?

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6mo ago

Fakeradar

Maker

@simona_o_neill3 Yes, we can already analyze up to 6 people simultaneously in a group call.

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6mo ago

@artem_anikeev great ! 👌🏻

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6mo ago

remio - Your Personal ChatGPT

Congrats on your launch, Artem! Real-time deepfake detection with full privacy across major video call platforms is exactly the kind of tool needed to ensure trust and security in remote communication. The upcoming features like voice deepfake detection and behavioral analytics sound very promising to stay ahead of evolving threats. What industries or use cases have you seen show the most interest or traction so far?🤔

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6mo ago

Fakeradar

Maker

@lvyanghuang Currently, financial and recruiting companies are using it. However, the rate of fraud is growing very rapidly. Therefore, we expect that soon all companies that use video conferencing in their work will use it. We also expect demand among individuals.

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6mo ago

BlogBowl

Congratulations on the launch!
Curious if you have your own AI models for that or you use some of the existing?

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6mo ago

Fakeradar

Maker

@danpole Thank you for the kind words and the professional question! We have our own unique models. We also have many unique developments – our own neurons and error functions. We have the best mathematicians on our team. They are constantly coming up with new things.

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6mo ago

Congratulations on the launch! 🎉

Deepfake detection is so important these days. Just yesterday I saw a video ad here in my country with a trusted public figure promoting a scam. The lip sync, the video, and the voice were so good that for several seconds I thought it was real…

This is going to become an exponential problem really soon.

Maybe it’s a bit early to ask, but are you planning to incorporate ad deepfake detection in the future?

I wish you the best!

Report

6mo ago

Fakeradar

Maker

@jtarletta Thanks for the example! Fake Radar only works in real time. We strive for 998 out of 1000 accurate predictions, hence the limitations. We'll be adding more tools over time.

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6mo ago

Fakeradar

Maker

@jtarletta We've been developing this project for 1.5 years. Throughout this time, we've seen an increase in deepfake attacks on public figures.

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6mo ago

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5.0

Based on 1 review

Review Fakeradar?

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Most Informative

Hi Product Hunters!

I’m Artem Anikeev, founder of FakeRadar.io — a real-time deepfake detection tool for video calls.

Over the last 18 months, our team has built technology that instantly verifies whether the person on the other side of a call is real or fake.

How it works

Runs in real time during Zoom, Google Meet, Teams, Discord, and more.
No recordings, no audio access, no data stored — full privacy.
Detects deepfakes, static photos, and suspicious signals instantly.
Currently protects against 8 deepfake generators — and the number keeps growing.

Who it’s for?

Recruiters → avoid fake candidates in interviews.
Fintech & banks → verify high-risk clients.
Any team running video calls → protect against fraud.

Coming next

Voice deepfake detection & synthetic text analysis
A unified anti-fraud platform combining video, audio & text in real time
Adaptive learning system that auto-updates as new deepfake methods appear
Behavioral analytics: pauses, facial expressions, speech patterns
A global database of deepfake “fingerprints”
API for banks, governments & enterprises to provide large-scale fraud protection

We’d love your support, feedback, and ideas!

Try FakeRadar.io today and make sure every video call you make is with a real person.