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Harvest Keeper Project Bridges Crypto and AI

Daniela Kirova
Daniela Kirova
Daniela Kirova
Author:
Daniela Kirova
Writer
Daniela is a writer at Bankless Times, covering the latest news on the cryptocurrency market and blockchain industry. She has over 15 years of experience as a writer, having ghostwritten for several online publications in the financial sector.
February 13th, 2023
  • The project’s smart contract underwent testing to confirm its safety and security
  • A bot applies algorithms to analyze the factors, risks, and patterns based on past experiences

Disclaimer: The following information is based on a press release and not substantiated by Bankless Times research.

Harvest Keeper is an innovative project bridging AI and cryptocurrencies. It eliminates the human factor from trading, making it possible to trade around the clock according to a press release.

The project’s smart contract underwent testing to confirm its safety and security. The platform was proven to be defect-free.

Reduced market risk

Market risk is reduced thanks to the project’s AI capabilities, improving trading opportunities in adverse market conditions and making it possible to allocate assets more reasonably. The platform’s referral system gives investors a chance to grow their daily earnings.

You can invite friends to the platform and collect up to 8% per day of their earnings depending on the referral level. You get 3% of Level 2 referrals and 5% of Level 1 referrals.

AI-based bot workflow

The Harvest Keeper bot applies algorithms to analyze the factors, risks, and patterns based on past experiences. This is especially effective for the crypto market, which is active 24 hours a day. The bot takes actions based on objective data, excluding hypotheses and assumptions.

The bot enables automated trading, which is highly effective and efficient because of the maximum formalization. The creators of Harvest Keeper wrote the bot algorithm in utmost detail in order to reduce the likelihood of blind spots. The lack of certain conditions for entering or exiting the market can result in poor decisions.

Simulating multiple market conditions

After creating the algorithm, the development team collaborated with real traders to carry out a number of important tests and simulate market conditions such as:

· Bear market

· Bull market

· Crisis in select asset segmentation

· Prolonged sideways movement

· Volatility (dramatic price swings, crashes)

· Whale activity affecting the market, etc.

Contributors

Daniela Kirova
Writer
Daniela is a writer at Bankless Times, covering the latest news on the cryptocurrency market and blockchain industry. She has over 15 years of experience as a writer, having ghostwritten for several online publications in the financial sector.