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The AI Solution for Trust Benchmarking | Web 3.0 Analyses | Blockchain Technology Validation | Investment Signals | Fraud Monitoring
Check Whitepaper
While blockchain technology is now the de facto driver of innovation via transmission of value, its accessibility is far from ideal. Comprehension, reliability, and transparency of blockchain fully automated analytics remain massive roadblocks with relatively steep learning curves.
In just over five years, daily transactions across the Bitcoin, Ethereum, and other networks increased tenfold — going from just 250,000 to more than 2.5 million transactions a day. Growth in the blockchain and crypto space is fast, but the lack of reliable data sources and accessible analytics for non-native consumers is a massive barrier to entry and a hurdle in the way of mass adoption.
The disruptive potential of blockchains, digital assets and Web 3.0 technologies is now acknowledged by the mainstream. The crypto market, at its peak in 2021, was valued around $3 trillion and included more than 12,000 projects. With events like El Salvador's adoption of Bitcoin, Walmart's food traceability system, J.P. Morgan's Interbank Information Network for cross- border payments and Twitter's BTC and NFT adoption - more and more governments, investment funds and corporations are seeking exposure to this space and growth is projected to continue into the future.
On the funding side, the venture capital industry has poured a record $33 billion into crypto investments as of 2021, which is more than the total amount raised in all previous years combined. According to the latest stats, the number of Crypto unicorn companies increased by a whopping 491% in 2021.
Web 3.0 describes the evolution of the internet, going from a centralized and platform-based web towards a decentralized network-based internet, powered by a crypto-based value exchange model.
However, in this evolution of the internet from Web 1.0 to Web 3.0, the various issues related to scalability, security and performance have, in various ways, persisted, and continue to challenge experts. These concerns and challenges are even more pronounced with Web 3.0 as it merges public and private data without there being any centralized gatekeeper.
Aiming to give control back to users along with interoperability, blockchain technology, and Web 3.0 infrastructure face unique challenges of a trust-less system, where users retain custody of everything, and everything is immutable without there being an“undo” button or a support helpline to call.
The security implications of such a system are also many, some of which include:
Given the sheer volume of data generated by blockchains today, manual analysis can be easily thwarted by artificial data overload. For instance, several bad actors intentionally execute a large number of transactions to obfuscate their tracks, making manual analysis virtually redundant.
This leaves the implementation of machine learning and artificial intelligence as one of the biggest opportunities in the space.
We believe the opportunity today goes beyond basic smart contract auditing and requires the combination of various data points obtained via deep analyses of smart contracts, blockchain transactions, market activity, tokenomics and more.
Our mission is to make reliable trust benchmarking available to all stakeholders in the crypto and blockchain space.
We see TrustCheck as an ever-evolving, real-time software that grows along with the crypto/blockchain market and becomes a cornerstone solution for investment-focused decision-making.
Our vision for TrustCheck is to make it the de facto trust-benchmarking protocol for both platforms and end-users, who benefit from our breakthroughs in fraud prevention and detection via automated blockchain analysis.
We are specifically focused on the values of transparency, reliability, optimization, evolution, automation and data-backed decision-making.
We are simultaneously solving the pain points mentioned above using machine learning and artificial intelligence.
Our solution is a B2B2C real-time transaction analysis and tracking software that sits on a different blockchains full nodes to deliver reliable and relevant information along with real-time benchmarking signals to ascribe levels of trustworthiness.
Examples of such signals include: sale bans, backdoor mint and rebase functions, smart contract plagiarism, liquidity quality and origin of initial liquidity funds, price and volume manipulation, extreme slippage, project wallet transactions, and movement of team allocations among others.
Meet us @:
Pilatusstrasse 50,
Hergiswil, Switzerland
Mail us @:
Provided to you by:
Dragonlabz GmBH.
Swiss Office
www.trustcheck.me
TrustCheck builds AI analytics protocol for automation of time-consuming Web3 real-time verifications.
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