The solutions that Avorak will provide will apply to both retail and commercial requirements, a key aspect of Avorak’s growth plan.


For image creation, rather than an image scraper that scours the internet for reference images to work from, Avorak is testing a pure language-to-image process that is based on prebuilt and to-be-learned descriptors. Once the alpha stage has finished, beta testers will simultaneously be teachers alongside providing feedback, feeding the informational language structure and models into the machine to hone the image generation process. This is crucial for two reasons:

1: Image scrapers essentially ‘paraphrase’ existing artwork, thereby functioning and profiting on the work of others. This is unethical.

2: Image scraping AI is unable to develop an understanding of requirements on its own and simply uses existing art as a base point. This limits the output potential.

By working with language-to-art models, the potential of Avorak’s output becomes limitless, and no other existing work is being copied from, making Avorak the ethical choice for image generation.


Many trading APIs or bots are set up to work with one particular asset class or exchange. Some can be difficult to set up; some require code-based command entering, making it out of reach for non-power users, and some have incredibly low levels of security, as has been seen by recent API key leaks. Avorak will approach the trading market with a simple command line input, programmable with a standard script, for example: ‘in my Binance futures account when BTC reaches 30000 short 5 BTC at 5X’ or ‘in my Kucoin spot account when ETH reaches 1201 buy 7.5 ETH’ or ‘in my Kraken spot account market buy 4000usd of MATIC’ This will make trading bots simpler for large multi-exchange trading funds to use simultaneously, in addition to allowing retail users access to these powerful tools, linked to services such as TradingView for easy visuals. Avorak Trading will encompass both an automated API and have the ability to generate a large set of indicators for traders, using both overlays and notification systems to alert users of trend or pattern changes. The automated API will encompass these indicators and make automated trades on your behalf. A full separate product whitepaper will be released shortly before public beta testing begins.

Text generation:

Most text-generating AI will use internet scraping to create language style or pull information about the subject. One main issue with this technology is repetition or plagiarism that can occur with such a process. Avorak AI will combine internet scraping with a prewritten language bank, in addition to integrating plagiarism-detecting APIs with the view to autocorrecting and editing any text before displaying it to the querying user. This will ensure a clean, plagiarism-free experience from Avorak AI.

Worldwide Service Access:

The majority of AI systems will require some form of credit card for payment, which for many, is an inaccessible form of payment. By using a token payment system, it is possible to buy services from anywhere in the world using blockchain, making Avorak AI the most accessible to everyone.

Last updated