BitMind

Our updated mobile app allows you to generate AND detect deepfakes in seconds. Create, verify, and explore AI-generated content all in one place. Try BitMind's AI Detector & Creator app here: bitmind.ai/mobile

One question reaches our inbox every week. We built the answer. "Is this image AI-generated?" BitMind gives you more than yes/no. → Which model likely generated it → Which regions were manipulated → Confidence score your team can act on Free tier. No credit card. No demo call. Try it on the hardest image you have. If we get it wrong — we genuinely want to know. That's how the model improves.

CysecOnline, South Africa's trusted digital forensics experts, is now integrating BitMind into their services to detect deepfakes with industry-leading accuracy. Protecting clients from synthetic media, fraud & misinformation like never before. Real-time AI verification meets expert forensics. Secure what's real.

See our founder @kenjon talk @bitmind with the @twistartups !

The EU AI Act, Article 50: platforms must label AI-generated content starting August 2026. Non-compliance: fines up to 6% of global revenue. That's not a suggestion. That's a legal requirement for every platform serving EU users. Oftentimes this becomes global policy (e.g. EU car emissions) The infrastructure to detect and label this content at scale doesn't exist at most companies. We've spent 2 years building it.

@VCavs87 @ncbtrades yes revenue / profit to buy back token 🫡

@bitmind @ncbtrades Is there a roadmap for value accrual to alpha holders?

Q1 2026 has been a breakout quarter for BitMind. We made significant strides toward our mission of creating a decentralized Trust Layer for the internet, delivering real product progress, enterprise traction, and ecosystem collaboration on the Bittensor network. Here is what we accomplished: Launched the Human Face Competition We kicked off our first major community-driven data initiative, the Human Face Competition. This open call is crowdsourcing diverse, high-quality face data to accelerate training of our specialized deepfake detection models and directly support our key partnerships. Formalized Strategic Partnership with Yanez (@yanez__ai)After months of technical integration, we officially partnered with Yanez to co-build a fine-tuned face deepfake detection model optimized for biometric-grade attacks. Yanez brings 20+ years of identity security expertise, patents, and a proprietary face dataset, while we contribute our proven AI-generated content detection model and Top 20 subnet infrastructure. This collaboration is already delivering a model neither subnet could build alone and is aimed squarely at the exploding deepfake fraud problem in crypto, finance, and identity verification. First Enterprise Customers and Revenue We closed our first enterprise contracts and generated real revenue from production deployments. These wins validate both the demand for our technology and our ability to serve serious customers who require reliability, compliance, and measurable performance. Complete Infrastructure Refactor We rebuilt our core infrastructure from the ground up. The result is major performance gains, dramatically improved scalability, and full readiness for SOC 2 certification with a strict zero-data-retention policy. This puts us in a strong position to meet the security and privacy standards enterprise and regulated customers demand. New Reporting Feature with Explainability We shipped a powerful new reporting dashboard that gives users clear, human-readable explanations for every detection decision. Transparency and trust are now built into the product, not added later.

been cooking @bitmind 🔥 big breakthrough: ensembles our top miners’ insanely diverse models (CNNs, SoTA ViT architectures, CLIP, VLM vision encoders + more) trained an attention layer on top. huge performance jump… and it nailed the in-the-wild vibe test. applied on images, videos coming soon new products + research report on the way 🫡

We are officially formalizing our partnership with @yanez__ai to build a specialized face deepfake detection model on the Bittensor network. This has been months in the making and it’s going to be a game-changer. Here’s why we’re so excited. Deepfake fraud isn’t coming, it’s already here. One finance employee was tricked into wiring $25 million after a video call with AI-generated executives. Finance deepfake attempts are up 2,137%, and identity fraud via deepfakes surged 3,000%. Most existing detectors weren’t built for biometric-grade face attacks. We’re fixing that. What @bitmind brings: A battle-tested AI-generated content detection model already serving enterprise clients. What @yanez__ai brings: 20+ years of biometrics and identity security expertise, a portfolio of patents, a proprietary high-quality face dataset, and deep experience in fraud prevention and compliance sales with existing relationships at major identity verification providers. Together we’re building something of incredible importance: a fine-tuned face deepfake detection model specifically optimized for real-world identity verification, KYC, onboarding, and liveness checks. This is collaboration that is meaningful and makes sense. To accelerate the partnership and crowdsource even more diverse, high-quality face data, we just launched our Human Face Competition! This partnership also gives us immediate enterprise traction. Yanez’s proven track record in fraud and compliance sales means we’re not just building tech - we’re building something that can ship to real customers fast. The big vision? A fully open-source software identity system on Bittensor: a decentralized Trust Layer for the Internet. We’re creating cryptographically sound proof of human and uniqueness that solves the growing “one person, many wallets/keys/bots” problem. Model fine-tuning is already underway. We’ll be sharing regular technical updates, benchmarks, and progress on the full proof-of-humanhood product.

Viral deepfake video: Scammer asked to put 3 fingers over his face to prove he’s real… instant glitch. But with generative AI advancing this fast, these manual tricks will be solved very soon. Real-time security tools are now essential to secure business communications. We’ve already been in contact with several companies who’ve interviewed (and hired) fake candidates with malicious intent. Time to protect your organization.

Very excited to announce our partnership with @yanez__ai to build out face deepfake detection models more details below

How do you know if a war video online is real? In moments of conflict, content spreads faster than verification. Thousands of clips circulate daily — and most people aren’t equipped to analyze them frame by frame. That’s the gap. Not just misinformation. But the speed at which it moves. Human skepticism alone isn’t enough anymore. Truth needs infrastructure. BitMind helps detect AI-generated content in real time — so decisions aren’t made on what looks real, but what is.

As anything can be generated, trust can’t rely on what we see; verification has to go beyond the human eye.

The new risk isn’t perfect AI. It’s “good enough” AI going viral. BitMind detects what slips past human intuition

IM LIVE: Trump's TACOs Aren't Working... - IRAN vs USA Continues, TAO is RIPPING, Crypto is BACK!? Interviewing @const_reborn (4pm et) Twitch.tv/threadguy twitter.com/i/broadcasts/1…

100% satisfaction” badges. Official-looking certificates. Everything about this looks designed to build trust. That’s exactly the point. A recent investigation highlighted how AI is being used to generate convincing medical ads at scale—complete with fake doctors, fabricated endorsements, and polished visuals that mimic legitimate.

Something looks off. Not obvious. Not immediate. But in the details. Frame by frame, the signals break. Physics doesn’t hold. Structure shifts. These are the details humans miss. BitMind detects what the eye can’t see by analyzing patterns across frames and motion. Because in today’s content, looking real isn’t enough.

A revealing moment from a clip with Joe Rogan. He initially believes an AI-generated video — not because it’s perfect, but because it fits something he already believes. That’s the real challenge in the AI era. Synthetic media doesn’t need to fool everyone. It only needs to confirm what some people already think is true. The future of detection isn’t just technical. It’s about understanding how human bias and AI media interact.

A fascinating example shared by Manoharan B.. He received an SMS with what looked like an official court notice for a toll violation, court header, case number, judge name, even a QR code for payment. It looked real. And that’s exactly the point. In the AI era, scams no longer rely on bad spelling or obvious design flaws. Generating something that looks official now takes seconds. Which means detection is changing. It’s no longer about spotting visual mistakes. It’s about verifying process, source, and context. Does the institution actually communicate this way? Does the payment workflow make sense? Does the process match how the system normally operates? As AI lowers the barrier to creating convincing scams, verification will become just as important as generation.