Building Trust in an AI-Powered World
BitMind secures the data businesses depend on to make decisions. We verify the authenticity of every data point before automated systems act on it, so your AI never operates on synthetic media, deepfakes, or AI-generated fraud.
The team
Ken Miyachi
Co-founder, CEO
Former Senior Tech Lead at NEAR Foundation and founder of LedgerSafe. Previously Amazon Engineer with deep expertise in large-scale distributed infrastructure.
Dylan Uys
Co-founder, Head of AI
ML Engineer at ViaSat and Poshmark with extensive experience in computer vision and fraud detection systems.
Canh Trinh
Head of Engineering
Engineering Lead at Axelar with prior experience at JP Morgan and Deutsche Bank. Specializes in enterprise integration and distributed systems.
Bruce Lou
Head of Marketing
California Congressional District 11 Candidate, with a background in executive search. Jeoporady Champion. Social Media Marketing Expert.
Alexey Zenin
Infrastructure Engineer
Founder of 2BeBuilt and former Gaming & BD at NEAR. PhD Candidate at Texas A&M specializing in distributed systems.
Andrey Gruzdev
Backend Engineer
Co-founder of 2BeBuilt and Software Engineer at NEAR with expertise in scalable backend systems.
Eli Lamb
Full Stack Engineer
Specializes in frontend development and design with a focus on creating exceptional user experiences.
Hem Gurung
AI Engineer
AI development specialist focused on building and optimizing machine learning models for detection systems.
Nas Mahmoud
Digital Marketing
Digital Marketing lead at DLX and Director at Jabari, driving growth through strategic campaigns.
Our Story
Protecting trust through technology.
Enterprise AI now reads inputs and makes decisions in milliseconds: a customer's face on a video call, a vendor's invoice, a prompt sent to a support agent. Every one of those inputs is an attack surface. BitMind is building the trust layer that verifies them before they reach your systems.
We started with deepfake detection because it's the highest-stakes input integrity problem in the world today, with nearly $900M in reported fraud in 2025 alone. The adversarial architecture we built for synthetic media generalizes. Prompt injection and document integrity are next, on the same platform, with the same accuracy and latency guarantees.
Our team comes from Amazon, NEAR Foundation, ViaSat, JP Morgan, Deutsche Bank, and Axelar. We are building this because no one else is.
Our Values
The principles that guide our work and shape our approach to AI fraud detection technology.
Technical Excellence
We maintain the highest standards in AI research and development, continuously pushing the boundaries of AI fraud detection technology.
User-Centric Design
Our solutions are built with users in mind, ensuring accessibility and ease of use across all platforms and use cases.
Transparency & Trust
We believe in open-source principles and transparent communication, building trust through verifiable results and clear documentation.
Continuous Innovation
Our GAN-style architecture ensures we stay ahead of evolving threats through continuous competition and improvement.