NBAI Blockchain Platform

about nbai platform

NBAI is an artificial intelligence (AI) computing blockchain platform that enables developers to safely and reliably develop, compute and deploy AI applications with high efficiency, low cost and without worrying about the underlying system configuration.

We connect AI computing power around the world, forming a decentralised network, effectively eliminating the need for AI users to invest in their own expensive hardware.


use case 1

quant ai

Quant AI is Nebula’s cutting-edge trading price prediction DAI App. Quant AI analyzes time series and trains deep learning models based on AI algorithm to forecast real-time trends.

use case 2

crowd intelligence

Crowd intelligence is supporting building sentiment evaluation model for business needs. By sentiment annotation and enrichment, crowd intelligence offers novel possibilities to integrate machine and human intelligence at a large scale, enabling the development of AI task with the wisdom of community.

use case 3

sentiment analysis

AI Sentiment Analysis is a natural language processing DAI App developed by Nebula AI. It helps users classify the polarity of a given text and extract the attitude of the writer. It is currently used as a price prediction model for trading, evaluation of consumer inclination, online conversations positioning and content inclinations.

use case 4

biomedical ai

Biomed AI is a medical imaging evaluation tool that offers a paradigm shift in streamlining of electronic medical records (EMRs). Biomed AI improves medical imaging practice, diagnosis of illness, treatment planning and results assessment. It identifies high risk patients earlier, facilitate disease prevention programs, optimizes worklist prioritization for urgent cases and manages population health programs to reduce cost of care.

AI algorithms are trained using vast numbers of exams to determine what normal anatomy looks like on scans from CT, magnetic resonance imaging (MRI), ultrasound or nuclear imaging. Then abnormal cases are used to train the eye of the AI system to identify anomalies, with performance & accuracy close to those of clinicians.