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About Our €900k Fundraise to Solve the Ethereum Transaction Fee Problemby@pauliusuza
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About Our €900k Fundraise to Solve the Ethereum Transaction Fee Problem

by Paulius UzaJune 12th, 2020
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At Upvest, we've secured almost €900k Euro in project funding from the Investitionsbank Berlin (IBB) and the European Regional Development Fund (ERDF) as part of the IBB ProFit program. The funding is used to further support the development of Upvest’s transaction fee recommendation/estimation engine.

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At Upvest, we've secured almost €900k Euro in project funding from the Investitionsbank Berlin (IBB) and the European Regional Development Fund (ERDF) as part of the IBB ProFit program. The funding is used to further support the development of Upvest’s transaction fee recommendation/estimation engine.

The IBB only selects a handful of startups each year, and Upvest was among those selected in 2020.

Fee estimation on Ethereum is risky and cost-inefficient

Transaction fees are a complex topic that platforms have to deal with when building applications on Ethereum. On the decentralized network, the execution speed of a transaction is dependent on the network traffic at a given time, as well as on the transaction fee, which is sent along with the transaction.

Thus, setting a fixed fee for every transaction will likely result in an overfunding or underfunding of the transactions. Overfunded transactions quickly add up in terms of cost, especially when the amount of transactions sent is very high. Underfunded transactions, on the other hand, come with the risk of being dropped and never included in mined blocks. Underfunded transactions get stuck in the mempool, and it requires signing another transaction to replace the underfunded one.

As of today, existing fee estimation approaches are simplistic and do not come with uptime guarantees or enterprise support.

Fee estimation neural network

Upvest developed a fee recommendation engine and high availability API powered by a continuously evolving machine learning model. The engine is constantly collecting real-time network signals from numerous independent data sources, including for example the number of unconfirmed transactions or the number of active miners, which are then used to trained the neural network.

Currently deployed model has been trained with Ethereum network signals gathered over a period of one month.

The initial benchmark results against the competing fee recommendation solutions promises crucial performance improvements of around 18% - that's significantly cheaper fees for the same transaction performance.

Why should I use it?

Upvest fee recommendation engine is designed for startups and companies that are executing a large number of transactions on the network. These companies are dependent on a meaningful fee recommendation system to optimize their operating costs.

Moreover, the transaction execution speed is optimized while locking up capital is avoided entirely. It is relevant to highlight that these benefits gain importance for an increasing transaction count and/or transaction volume.

Upvest offers the service in the form of an easy to use API, which does not require any blockchain specific knowledge. You can achieve the execution speed that you need without worrying about fees.

How can I participate and get access?

If you are company or a startup working with Ethereum transactions and would like to try the fee recommendation API, apply using this form or write to us directly to get access to fee estimation private beta. We are very excited to hear your feedback.

Learn more about the project in the technical blog post and fee estimation product page.