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Trust & Reputation
in Web3

Our mission is to build trust on the internet by making the integrity and reliability of information, data and users measurable with our reputation-based evaluation protocol (REP). 

Reputation-based Evaluation Protocol

The REP is the core of TrustLevel and serves as the basis to ensure data integrity by creating and identifying trustworthy and reliable information, activities and users for various industries.

Evaluation Layer

Through this structured framework users can provide systematic objective and subjective evaluation and classification of information.

AI Layer

Through various algorithms and techniques (Knowledge Graphs, LLMs)  patterns of reliable or unreliable contributions and users are recognized.

Blockchain Layer

This ensures transparency, security and immutability by recording all activities, reviews and decisions in a decentralised ledger.

Use Cases

Web3 Governance Tool


For the evaluation of grant and governance proposals and activities.

Decentralized Governance

REP improves decentralised governance by better ensuring that decisions are made on the basis of assessments by reputable and knowledgeable participants, thereby promoting trust and integrity in the whole process.

Grants Programs

REP optimizes grant programs by ensuring that the credibility of proposers and the feasibility of projects can be reliably verified, ensuring that funds are awarded to the most deserving and impactful initiatives.

Impact Assessments

REP improves impact assessments by combining subjective and objective evaluation methods to more reliably measure and verify the effectiveness and outcomes of different projects and initiatives.

AI Services


News Bias Detector

News articles often suffer from bias and manipulation, making it hard to find objective reporting. Our LLM-powered News Bias Detector detects bias of news article, and presents a balanced, reliable summary, ensuring you receive unbiased and credible information.


Product Review Analyzer

Product reviews are increasingly unreliable due to the growing spread of manipulated reviews. We are therefore developing an AI tool that generates an adjusted, more reliable product review and product rating by collecting reviews from different e-commerce platforms for a searched product and using AI to detect and remove bias and manipulation.



Proposal Reviewer

The more successful Web 3 Grant programmes are, the more difficult it becomes to identify the really good proposals from the masses. We are developing an LLM-based proposal reviewer that helps to automatically weed out bad proposals so that the community can focus on evaluating the really relevant proposals. 




TrustLevel was founded by Dominik Tilman with the vision to develop methods and protocols to make the reliability of data and information measurable. Since then, we have received various grants (Cardano, SingularityNet, Arbitrum) and projects that have continuously improved our knowledge and developed tools and enabled us to provide better reviewing and voting processes and systems in decentralized communities.


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