• CryptoAngel is a virtual life assistant based on a powerful AI models, that works on an individual input, and outputs the best model that suits particular user needs.
  • CryptoAngel is a virtual life assistant based on a powerful AI models, that works on an individual input, and outputs the best model that suits particular user needs.



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  • Their idea is putting intelligence on the blockchain, or more specifically, using blockchain architecture to instantiate thinking machines.
  • They are focusing on AI’s assistive role, emphasizing the fact that it is designed to enhance human intelligence, it is the idea of a system that supplements and supports human thinking, analysis, and planning, leaving the intentionality of a human actor at the heart of the human-computer interaction.



  • They are currently in talks with a host of partners and hopefully will make some announcements soon.


  • In recent years, AI researchers have finally solved problems that they’ve worked on for long, from AlphaGo to human-level speech recognition, and AI is finally starting to deliver real-life benefits.
  • AI, in broadest sense, is simulation of human intelligence processes by machines and computer systems. These processes include: learning, reasoning and self-correcting and improving. AI can interact with the environment, perceive it, and take actions that are going to maximize its chances to succeed at some goal.
  • Machine learning is the subset of Artificial Intelligence with an emphasis on “learning” rather than just computer programming. The idea behind machine learning is the following: In order to “simulate” complex systems (like human intelligence for example), traditional approach would be to write a computer program that simulates the behavior of such systems.
  • Deep learning, a subset of machine learning, takes computer intelligence even further. It uses massive amounts of data and computing power to simulate Deep Neural Networks.
  • Machine learning focuses on the development of computer programs that can learn for themselves, given the collection of examples (data) and the goal that needs to be met.
  • Machine Learning is divided into supervised learning and unsupervised learning. In supervised learning label data is given to the machine, which then uses this data to build the model of it and use it on newly seen data to make predictions or label them.
  • In unsupervised learning, and it operates on raw data (not labeled) and is able to find hidden patterns or anomalies inside the dataset, or it can be used to split into clusters of similar point.
  • Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed. Machine learning is a data analytics technique that teaches computers to do what comes naturally to humans and animals: learn from experience.
  • Deep learning is a particular kind of machine learning that achieves great power and flexibility by learning to represent the world as nested hierarchy of concepts, with each concept defined in relation to simpler concepts, and more abstract representations computed in terms of less abstract ones.
  • Deep learning refers to artificial neural networks that are composed of many layers (called hidden layers). The ‘deep’ refers to multiple layers. A Deep Learning network can be seen as a Feature extraction layer with a Classification layer on top. The power of deep learning is not in its classification skills, but rather in its feature extraction skills. Feature extraction is automatic (without human intervention) and multi-layered.
  • Deep learning is especially effective in image recognition, which is due to its ability to extract and abstract features.
  • Artificial intelligence needs data to learn, and it requires hundreds of thousands of times more information than humans to understand concepts or recognize features.
  • Application domains where deep learning is successful today are those where a lot of data can be acquired, such as speech and image recognition. Big tech giants (like Google and Facebook) have access to mountains of data (for example, your voice searches on Android), making it much easier to create useful tools.
  • The value of data is increasing and all the dynamics of data ownership is amplified when AI enters the equation leading to virtuous cycle – more data means better machine and deep learning, which means better services and more users, which means more data.
  • They want to ensure these people can readily access the knowledge and tools they need to make their contribution to the field of AI, and to inspire capable people all over the world to dedicate their talents to value creation through AI.
  • Blockchain technology, which underpins the second generation of the Internet, will significantly improve the efficiency of supercomputing. It enables the capability to integrate computational power across systems and thus produce supercomputing that is faster and cheaper.
  • Many experts have defined the ability to generalize learning as one of the differences between how a neural network attacks a learning problem versus how a human does.
  • An AI that can generalize between learned activities could use its vast storehouse of learned models to attack any new activity with a level of sophistication only dreamed of by humans.
  • Blockchain could be the missing link in AI achieving high levels of generalization, since it can democratize it, provide shared computing resources and generally build a whole ecosystem around it, where users share dataset, train models and use them, while also improving the central, common AI at the same time.
  • Differential Neural Computer (DNC) which was also used on AlphaGo, relies upon a high throughput external memory device to store previously learned models, combined with a system for generating new neural networks based upon the archived models.
  • Their vision is the democratization of AI – a shift that will transform and change our society in fundamental ways.
  • CryptoAngel project aims to provide business ecosystem which will accelerate development of generalized and democratized AI in decentralized manner.
  • CryptoAngel will provide a framework as a tool for external users to build AI models, provide data training sets and to contribute to the development of what they call Common AI in return for Angel cryptocurrency.
  • The application is AI-powered “consultant”, virtual advisor which is super smart, interactive and has the answer to almost every question and problem one person is facing around the world.
  • CryptoAngel’s business model is a marketplace for categories of AI models, with a supply and demand side.
  • The supply side of our business model allows external AI developers to contribute to the development of categories of knowledge which will be offered to users of our AI mobile application.
  • The demand side of our business model is driven by usage of our mobile application. It provides generalized AI technology with wide variety of default features and possibility for end user to buy additional categories of knowledge using Crypto Angel currency, which is then distributed to all developers that contributed to the development of bought category.
  • Crypto Angel has 3 main objectives:
    • To democratize AI by onboarding broader community to be part of development process of “Common AI”
    • To make generalized AI application that offers comprehensive knowledge that is continuously learning
    • To make marketplace where end user can buy various categories of knowledge
  • Their strategy to capture the value from the market is to attract key players by differentiating our core economic levers and offering them possibility to enter new revenue streams.
  • CryptoAngel ecosystem is created in such manner that all the participants function independent of each other while remaining connected through CryptoAngel value chain.
  • Their platform, crowdsourced by AI domain experts and combined with carefully designed incentive structures will lead to organic and sustainable growth of the system itself.
  • They will use Nash equilibrium criterion to achieve stable state (equilibrium) where participants contribute to platform’s growth and pursue their own economic interests at the same time.
  • Developer is rewarded with Angel cryptocurrency if output of his model exceeds predefined output threshold, which is measured once process of model training is finished.
  • Decision system, which is part of their platform, maintains the logic for triggering model training. The system is extracting, transforming and loading processed and normalized data into smaller subsets of training data.
  • AI and blockchains are complementary and synergistic, and AI can add intelligence and insight to decision making process. Blockchain, in its role, adds integrity, assurance and decentralization to the core transactional environment and can help enormously in process improvement.
  • Crypto Angel is outlined as an input-processing-output computational system. CryptoAngel AI ecosystem is a framework where there are inputs which are processed and turned into outputs.
  • The inputs are brought into a Data supply portal for processing. The outputs might include taking an action, storing something back into memory, send notifications to users via CA mobile app or into system or smart contracts, conducting a transaction, or making a note or trigger for some sort of future action.
  • Dataset inputs will make to Crypto Angel central intelligence through life logging plugins, which will track user online activities. Crypto Angel will be used not only to orchestrate digital mindset files in the present, but also be an important management tool for the future.
  • Three areas in the CA blockchain thinking architecture of input-processing-output are outlined: memory, storage, and processing; and utility functions and output.
  • Golem is a platform that provides distributed computing on the blockchain, where applications (requestor) can rent compute cycles from providers. Benefit to using Golem is the incentivization of resource sharing.
  • CryptoAngel blockchain is giving rise to a new form of consensus model called Proof of intelligence. This will be for higher-level CA Central intelligence smart network operations rather than simple transaction recording. In one way, proof of intelligence will serve as a reputational qualifier; as a proof of ability to participate. In another way, proof of intelligence will be an indication that some sort of ‘mental’ processing has taken place.



  • 33.5 K + telegram users, 445 followers on Facebook and 8.5K+ Twitter followers.
  • They have got 66 subscribers for their YouTube Channel and 1.8K views for their official video.
  • 3.8 ratings on ICO bench.


  • They want to create worlds decentralized brain by interconnecting all crucial AI market drivers into business ecosystem backed by our cryptocurrency.
  • They also want to build an environment that is smart to understand your intentions, in some cases predicting them before you even become aware of them.


  • “Great project! Looking forward for success. But need more business people in the team.”- Nikolay Zvezdin(CIO at Envinary)
  • “Sorry I meant a 3 rating for a team. I deduct one point because your team is not a 5-star yet and I also deduct one point because you have an advisor who has not proactively had I icobench remove his rating. I saw your reply, but on the Ico expert side we all agree to terms that states we are to have our rating removed upon becoming advisors to an Ico, it’s a bias and ethics issues. I gave a 3 * for vision because how you will scale needs to improve and your target audience needs to be defined better. I gave you a three on products because there is no product but it’s a great concept and viable, 4 for a beta, 5 for an alpha” – Joseph Lowe(ICO Advisor | Integration Strategy l Certified Cryptocurrency Expert |


Pre – Sale Price N/A
Price in ICO 0.001 ETH
Country Serbia
Platform Ethereum

Whitelist/KYC None
Restricted Areas Restrictions apply with countries whose regulatory controls restrict from investing in ICOs.
Pre – Sale Pre-sale or private sale is still an option if you are interested. You will be directed to the founder.
Public-Sale 7th July – 7th Aug 2018 or once the hard cap is reached
Tokens for Sale: 70,000,000
Soft Cap 15000000
Hard Cap 70000000
Total Token Supply 88,000,000
Token Supply Breakdown ICO – 79.5%
Team – 18%
Advisors – 2.5%
Bonus Hard Cap Bonus %
18,000,000 – 26,400,000 30%
26,400,000 – 39,600,000 20%
39,600,000 – 52,800,000 10%