Computer Vision in Crypto & Web3
7 companies using computer vision technology in the crypto & web3 sector. Image and video processing, OCR, and document extraction
Directory
Companies by Funding
OpenAI
ChatGPT powers many fintech applications
Incode
AI identity verification with deepfake detection
Onfido (Entrust)
AI document and biometric verification
Veriff
AI identity verification
Jumio
AI-powered identity proofing
AU10TIX
AI-powered ID authentication and fraud prevention
Sumsub
AI all-in-one verification platform
Related
Other AI Technologies in Crypto & Web3
Related
Computer Vision in Other Segments
Frequently Asked Questions
How is Computer Vision used in crypto & web3?
Image and video processing, OCR, and document extraction In the crypto & web3 sector, Computer Vision is applied by 7 companies tracked by AIFI Map, with $59.1B in combined funding. Leading companies include OpenAI (ChatGPT powers many fintech applications); Incode (AI identity verification with deepfake detection); Onfido (Entrust) (AI document and biometric verification).
Which crypto & web3 companies use Computer Vision?
The AIFI directory tracks 7 crypto & web3 companies using Computer Vision, with a combined $59.1B in funding. OpenAI, Incode, Onfido (Entrust), Veriff, Jumio, and 2 more. (Source: AIFI Map directory.)
What is the most funded Computer Vision crypto & web3 company?
OpenAI is the most funded company using Computer Vision in crypto & web3, with $57.9B raised. ChatGPT powers many fintech applications Followed by Incode ($407M).
How does Computer Vision compare to other AI technologies in crypto & web3?
In the Crypto & Web3 segment, Computer Vision ranks #3 out of 8 AI technologies by adoption, with 7 companies and $59.1B in combined funding. The most widely adopted technologies in crypto & web3 are Infrastructure (28 companies, $1.1B funded); Agentic AI (8 companies, $153M funded); Computer Vision (7 companies, $59.1B funded). While Computer Vision focuses on image and video processing, ocr, and document extraction, alternative approaches include Infrastructure, which ai/ml infrastructure, compute networks, and tooling, and Agentic AI, which autonomous ai agents that execute actions independently.