TrustLevel Integration into SNET/AI Marketplace

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Dominik Tilman
Project Owner

TrustLevel Integration into SNET/AI Marketplace

Funding Awarded

$21,920 USD

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Status

  • Overall Status

    🥳 Completed & Paid

  • Funding Transfered

    $15,648 USD

  • Max Funding Amount

    $21,920 USD

Funding Schedule

View Milestones
Milestone Release 1
$2,592 USD Transfer Complete 19 Jan 2024
Milestone Release 2
$8,352 USD Transfer Complete 26 Jan 2024
Milestone Release 3
$4,704 USD Transfer Complete 08 Aug 2024
Milestone Release 4
$792 USD Pending 08 Aug 2024
Milestone Release 5
$5,480 USD Pending 08 Aug 2024

Status Reports

May. 7, 2024

Status
🧐 Fair, but could have been better
Summary

We have come to the conclusion that LLM now works better than NLP models - which means that we are changing the TrustLevel model for assessing bias in news articles from NLP to LLM. Therefore, we are still working on our model to reach a level that makes publication meaningful. This has so far taken more time than expected (and the conversion of our model is not part of the proposal itself). We hope to finalise the whole project in May.

Full Report

Project AI Services

No Service Available

Overview

TrustLevel is seeking $21,920 USD in funding to integrate its trustworthiness assessment solution into SingularityNet's AI marketplace. TrustLevel combines AI/ML and blockchain technology to evaluate the reliability and objectivity of online content and sources, aiming to combat the proliferation of unreliable information on the internet. The project addresses the challenges of information overload, fake news, and limited media literacy.

TrustLevel's solution includes a browser extension that uses AI to analyze website content, a reputation scoring algorithm to assess content and source quality, and the use of the Cardano blockchain for storing reputation scores. The proposal outlines four milestones, including kick-off and framework mapping, API development, publishing on the AI Marketplace, and documentation.

To mitigate potential risks, TrustLevel will conduct comprehensive technical assessments, thorough testing, and maintain open communication with SingularityNet's technical team during integration. Additionally, they plan to encourage user adoption through educational initiatives, feedback mechanisms, and incentives for early adopters.

Revenue generation will come from API calls, with 10% of additional revenue beyond $1,000 per month going back into SNET/DeepFunding wallets for five years. TrustLevel also plans to release its solution as open source in the future to enhance transparency.

Proposal Description

AI services (New or Existing)

Compnay Name

Trustlevel

Service Details

The proposal aims to integrate the first part of TrustLevel into SingularityNet's AI marketplace. TrustLevel uses AI/ML and blockchain technology to assess the trustworthiness of content, objectivity and reliability of sources to combat the problem of unreliable online information and to increase online credibility.

Problem Description

Today's online information is hard to verify and therefore often not trustworthy. Information overload, fake news, lack of accountability on the internet and limited media literacy compound this problem. With TrustLevel, we set out to solve this challenge by combining AI/ML and blockchain technology to create trust on the internet. 

On SingularityNet's AI Marketplace you can already find several services that can check texts for different criteria and patterns (e.g. semantic similarity, emotionality, hate speech detection, opinion barometer). However, there are already many more algorithms in this area that check the quality of texts and their sources. With this proposal, we would like to use the possibilities of TrustLevel to contribute to increasing the quality and quantity of these services on SNETs AI marketplace.

Solution Description

TrustLevel evaluates and verifies the trustworthiness, objectivity and origin of online information such as news, reviews or social media accounts by leveraging AI/ML and blockchain technology. On top of that we build an online reputation system that addresses the challenges posed by misinformation, confirmation bias, and lack of accountability in today's digital world. Our system consists of a browser extension that uses AI to analyze website content, a reputation scoring algorithm that evaluates content and source quality, and the storage of reputation scores on the Cardano blockchain.

With this proposal we are asking the community for 21,920 USD to integrate the first part of our solution into SingularityNet's AI Marketplace.

The TrustLevel score is composed of a variety of parameters. A few of these algorithms already exist, others are still under development. One important parameter that is already advanced is called the ‘Content Quality Score’. This is composed mainly of these three variables: (1) Context setting (factual information), (2) sentiment analysis (objectivity of information), (3) clickbait-probability (promotional information): 

  1. Context Setting: the AI performs a text analysis to understand the content of the Internet source and find clues to possible subjective or objective elements (including the amount of factual information contained in the article, including citations and references).
  2. Sentiment polarity (negative, neutral, positive): Using sentiment analysis algorithms, the AI detects the subjective tone or emotional charge of the text. A higher objectivity score indicates that the text is more factual and free of subjective evaluations.  
  3. The probability that the article is "clickbait” and or of promotional nature.

With this proposal, we would like to transfer the first variable to SNET, firstly to successfully master the process for the transfer and secondly to keep the scope of our first proposal in DeepFunding within a reasonable framework. The goal is then to transfer further elements from TrustLevel to SNET. As mentioned before, in order to have a realistic scope for this proposal, we have decided to implement only one of the three variables mentioned above as a first step. We will choose the one that is the most advanced at the time of the voting result (from today's point of view, the clickbait detector).

Milestone & Budget

The proposal is structured into four milestones, including kick-off and framework mapping, API development, publishing on the AI Marketplace, and documentation.

Please check the Google Spreadsheet with a more detailed budget breakdown:

Milestone 1: Kick-Off & Framework Mapping

  • Milestone Description: Kickoff meeting to define and map the framework and the exact technical implementation with the team. The team also instals and tests the necessary environment and tools (Dockers, etc.) to ensure that the implementation phase runs smoothly. 
  • Milestone deliverable: 
    • 1. Final documentation of mapping and framework 

    • 2. Functional setup

  • Milestone related budget: $2.592 USD
  • Period: weeks 1 - 2

Milestone 2: Write Code, Clients and API for gRPC

  • Milestone Description: To implement TrustLevel services on SingularityNET we must provide our API in gRPC, an open-source universal RPC framework. This milestone includes (1) the creation of the protocol buffers; (2) the server logic and code for the web server and gRPC server that can handle request for our TrustLevel services; (3) the code that creates a gRPC client that can call the ‘Content quality’ method of our Trustlevel service.
  • Milestone deliverable: 
    • 1. API between TrustLever server and gRPC ready to publish 

    • 2. API Documentation

  • Milestone related budget: $8.352 USD
  • Period: weeks 3 - 5

Milestone 3: Publishing on AI Marketplace

  • Milestone Description: To publish our TrustLevel service on the AI Marketplace as SNET services we must accomplish the following tasks: (1) specify the services model using protobuf file; (2) create the services metadata; (3) create account and publish the service; (4) (test-) run SNET Deamon; (5) testing API call capabilities. 
  • Milestone deliverable: 
    • 1. Published TrustLevel service on SNET

    • 2. Successful test run of TrustLevel service on SNET

  • Milestone related budget: $4.704 USD
  • Period: weeks 6 - 7

Milestone 4: Documentation 

  • Milestone Description: As documentation is mandatory for any service published on SNET, we will create a repository on how to test and use our services. Furthermore, we will publish a closeout report for the community.
  • Milestone deliverable: 
    • 1. README

    • 2. User guide

    • 3. LICENSE with SNET standard license

    • 4. Project closeout report for the community

  • Milestone related budget: $792 US
  • Period: week 8

Budget Summary: 

Total requested amount: $21.920 USD in AGIX

  • Milestone 1: $2.592 USD
  • Milestone 2: $8.352 USD
  • Milestone 3: $4.704 USD
  • Milestone 4: $792 USD
  • Hosting/API Call Usage: $5.480 USD (25% of the budget)

Note: Project management and marketing costs are not included in the proposal budget as they are covered by TrustLevel itself.

Revenue Sharing

API Calls:

We will onboard one TrustLevel service on the platform as part of this proposal. If this service crosses the threshold of $1.000 USD revenue per month, 10% of the additional revenue will be fed back into the SNET/DeepFunding wallets. This condition will remain valid for five years after first onboarding the service and will be applicable to this service or any subsequent iteration of this service on the platform.

Marketing & Competition

Communication Strategy:

Our marketing strategy emphasizes user engagement and partnerships. We plan to actively engage with potential users, seek feedback, and optimize our services. At the current stage of TrustLevel, the most important thing is to be in close contact with first users and potential users, as this is the only way we can determine and optimise the quality and relevance of our services.

We are therefore planning to go to a number of events and conferences in the field of blockchain, startups and media in the coming months. Partly with our own booth (WebSummit in Lisbon or Bits&Pretzel in Munich) or as a participant (Blockchain Conventions in Dubai and Barcelona; Cardano Summit in Dubai, Token2049 in Singapore, etc.) to talk about our solution and to attract new users and partnerships.

In addition, with the beta release of our browser extension (in the first step for Chrome and Brave) in autumn of this year, we will promote on social media channels about our solution in general, but also about the availability of our technology on the AI Marketplace on SingularityNet. The company behind Trustelevel is Conu21, a kind of incubator with excellent marketing expertise, which will support us in the visibility and reach of our marketing activities. 

Market Analysis:

Trends

The market for online information quality and reputation systems is a growing and promising one, as more and more people are becoming aware of the challenges and risks posed by misinformation, confirmation bias, and lack of accountability in today’s digital world. According to a report by

, the global market for content intelligence solutions is expected to grow from USD 485 million in 2019 to USD 1.956 billion by 2024, at a compound annual growth rate (CAGR) of 32.2%. 

 

Target Audience: 

Our solution addresses the growing concern over unreliable online information and the need for trustworthy content evaluation. We aim to appeal to a diverse range of individuals, businesses, and organizations that are invested in ensuring the accuracy, reliability, and credibility of online information. The primary target audience includes:

  • General Internet Users: Everyday internet users who consume online content, including news articles, social media posts, and reviews. These users are concerned about the accuracy of information and seek tools that help them distinguish between reliable and unreliable sources.
  • Journalists and Fact-Checkers: Professionals involved in journalism, media, and fact-checking can use TrustLevel to verify sources, detecting misinformation, and maintaining journalistic integrity.
  • Educational Institutions: TrustLevel can be used in schools and universities by educators to teach media literacy, critical thinking, and research skills. TrustLevel can be used as a tool to educate students about evaluating the credibility of online information.
  • Researchers and Academics: Researchers and academics who rely on credible sources for their work can use our tools to quickly assess the trustworthiness of sources, saving time and ensuring the quality of their research.
  • Businesses and Brands: Companies can use our reputation scoring algorithm to assess the credibility of online reviews, mentions, and news articles related to their products or services.
  • Governments and NGOs: TrustLevel can help institutions to maintain the integrity of public information by helping them ensure that the information they share is accurate and reliable.

Competitive Landscape:

The landscape for online information verification, reputation scoring, and content evaluation is evolving rapidly, reflecting the increasing awareness of misinformation and the need for reliable sources. We operate within this dynamic environment alongside several players developing similar or related solutions. Various platforms leverage AI and natural language processing to analyze content for sentiment, emotion, and credibility. Some of these platforms offer API services for sentiment analysis, hate speech detection, and credibility assessment.

In the midst of this competitive landscape, we differentiate ourselves through the integration of AI/ML and blockchain technology, combined with a comprehensive approach to evaluating not only the content but also the source's trustworthiness. Our protocols, reputation scoring algorithm, and blockchain-based storage offer a holistic solution to tackle misinformation, confirmation bias, and accountability issues.

Related Links

www.trustlevel.io

Long Description

Company Name

Trustlevel

Summary

The proposal aims to integrate the first part of TrustLevel into SingularityNet's AI marketplace. TrustLevel uses AI/ML and blockchain technology to assess the trustworthiness of content, objectivity and reliability of sources to combat the problem of unreliable online information and to increase online credibility.

Funding Amount

$21.920 USD

The Problem to be Solved

Today's online information is hard to verify and therefore often not trustworthy. Information overload, fake news, lack of accountability on the internet and limited media literacy compound this problem. With TrustLevel, we set out to solve this challenge by combining AI/ML and blockchain technology to create trust on the internet. 

On SingularityNet's AI Marketplace you can already find several services that can check texts for different criteria and patterns (e.g. semantic similarity, emotionality, hate speech detection, opinion barometer). However, there are already many more algorithms in this area that check the quality of texts and their sources. With this proposal, we would like to use the possibilities of TrustLevel to contribute to increasing the quality and quantity of these services on SNETs AI marketplace.

Our Solution

TrustLevel evaluates and verifies the trustworthiness, objectivity and origin of online information such as news, reviews or social media accounts by leveraging AI/ML and blockchain technology. On top of that we build an online reputation system that addresses the challenges posed by misinformation, confirmation bias, and lack of accountability in today's digital world. Our system consists of a browser extension that uses AI to analyze website content, a reputation scoring algorithm that evaluates content and source quality, and the storage of reputation scores on the Cardano blockchain.

With this proposal we are asking the community for 21,920 USD to integrate the first part of our solution into SingularityNet's AI Marketplace.

The TrustLevel score is composed of a variety of parameters. A few of these algorithms already exist, others are still under development. One important parameter that is already advanced is called the ‘Content Quality Score’. This is composed mainly of these three variables: (1) Context setting (factual information), (2) sentiment analysis (objectivity of information), (3) clickbait-probability (promotional information): 

  1. Context Setting: the AI performs a text analysis to understand the content of the Internet source and find clues to possible subjective or objective elements (including the amount of factual information contained in the article, including citations and references).
  2. Sentiment polarity (negative, neutral, positive): Using sentiment analysis algorithms, the AI detects the subjective tone or emotional charge of the text. A higher objectivity score indicates that the text is more factual and free of subjective evaluations.  
  3. The probability that the article is "clickbait” and or of promotional nature.

With this proposal, we would like to transfer the first variable to SNET, firstly to successfully master the process for the transfer and secondly to keep the scope of our first proposal in DeepFunding within a reasonable framework. The goal is then to transfer further elements from TrustLevel to SNET. As mentioned before, in order to have a realistic scope for this proposal, we have decided to implement only one of the three variables mentioned above as a first step. We will choose the one that is the most advanced at the time of the voting result (from today's point of view, the clickbait detector).

Marketing Strategy

Communication Strategy:

Our marketing strategy emphasizes user engagement and partnerships. We plan to actively engage with potential users, seek feedback, and optimize our services. At the current stage of TrustLevel, the most important thing is to be in close contact with first users and potential users, as this is the only way we can determine and optimise the quality and relevance of our services.

We are therefore planning to go to a number of events and conferences in the field of blockchain, startups and media in the coming months. Partly with our own booth (WebSummit in Lisbon or Bits&Pretzel in Munich) or as a participant (Blockchain Conventions in Dubai and Barcelona; Cardano Summit in Dubai, Token2049 in Singapore, etc.) to talk about our solution and to attract new users and partnerships.

In addition, with the beta release of our browser extension (in the first step for Chrome and Brave) in autumn of this year, we will promote on social media channels about our solution in general, but also about the availability of our technology on the AI Marketplace on SingularityNet. The company behind Trustelevel is Conu21, a kind of incubator with excellent marketing expertise, which will support us in the visibility and reach of our marketing activities. 

Market Analysis:

Trends

The market for online information quality and reputation systems is a growing and promising one, as more and more people are becoming aware of the challenges and risks posed by misinformation, confirmation bias, and lack of accountability in today’s digital world. According to a report by

, the global market for content intelligence solutions is expected to grow from USD 485 million in 2019 to USD 1.956 billion by 2024, at a compound annual growth rate (CAGR) of 32.2%. 

 

Target Audience: 

Our solution addresses the growing concern over unreliable online information and the need for trustworthy content evaluation. We aim to appeal to a diverse range of individuals, businesses, and organizations that are invested in ensuring the accuracy, reliability, and credibility of online information. The primary target audience includes:

  • General Internet Users: Everyday internet users who consume online content, including news articles, social media posts, and reviews. These users are concerned about the accuracy of information and seek tools that help them distinguish between reliable and unreliable sources.
  • Journalists and Fact-Checkers: Professionals involved in journalism, media, and fact-checking can use TrustLevel to verify sources, detecting misinformation, and maintaining journalistic integrity.
  • Educational Institutions: TrustLevel can be used in schools and universities by educators to teach media literacy, critical thinking, and research skills. TrustLevel can be used as a tool to educate students about evaluating the credibility of online information.
  • Researchers and Academics: Researchers and academics who rely on credible sources for their work can use our tools to quickly assess the trustworthiness of sources, saving time and ensuring the quality of their research.
  • Businesses and Brands: Companies can use our reputation scoring algorithm to assess the credibility of online reviews, mentions, and news articles related to their products or services.
  • Governments and NGOs: TrustLevel can help institutions to maintain the integrity of public information by helping them ensure that the information they share is accurate and reliable.

Competitive Landscape:

The landscape for online information verification, reputation scoring, and content evaluation is evolving rapidly, reflecting the increasing awareness of misinformation and the need for reliable sources. We operate within this dynamic environment alongside several players developing similar or related solutions. Various platforms leverage AI and natural language processing to analyze content for sentiment, emotion, and credibility. Some of these platforms offer API services for sentiment analysis, hate speech detection, and credibility assessment.

In the midst of this competitive landscape, we differentiate ourselves through the integration of AI/ML and blockchain technology, combined with a comprehensive approach to evaluating not only the content but also the source's trustworthiness. Our protocols, reputation scoring algorithm, and blockchain-based storage offer a holistic solution to tackle misinformation, confirmation bias, and accountability issues.

Our Project Milestones and Cost Breakdown

The proposal is structured into four milestones, including kick-off and framework mapping, API development, publishing on the AI Marketplace, and documentation.

Please check the Google Spreadsheet with a more detailed budget breakdown:

Milestone 1: Kick-Off & Framework Mapping

  • Milestone Description: Kickoff meeting to define and map the framework and the exact technical implementation with the team. The team also instals and tests the necessary environment and tools (Dockers, etc.) to ensure that the implementation phase runs smoothly. 
  • Milestone deliverable: 
    • 1. Final documentation of mapping and framework 

    • 2. Functional setup

  • Milestone related budget: $2.592 USD
  • Period: weeks 1 - 2

Milestone 2: Write Code, Clients and API for gRPC

  • Milestone Description: To implement TrustLevel services on SingularityNET we must provide our API in gRPC, an open-source universal RPC framework. This milestone includes (1) the creation of the protocol buffers; (2) the server logic and code for the web server and gRPC server that can handle request for our TrustLevel services; (3) the code that creates a gRPC client that can call the ‘Content quality’ method of our Trustlevel service.
  • Milestone deliverable: 
    • 1. API between TrustLever server and gRPC ready to publish 

    • 2. API Documentation

  • Milestone related budget: $8.352 USD
  • Period: weeks 3 - 5

Milestone 3: Publishing on AI Marketplace

  • Milestone Description: To publish our TrustLevel service on the AI Marketplace as SNET services we must accomplish the following tasks: (1) specify the services model using protobuf file; (2) create the services metadata; (3) create account and publish the service; (4) (test-) run SNET Deamon; (5) testing API call capabilities. 
  • Milestone deliverable: 
    • 1. Published TrustLevel service on SNET

    • 2. Successful test run of TrustLevel service on SNET

  • Milestone related budget: $4.704 USD
  • Period: weeks 6 - 7

Milestone 4: Documentation 

  • Milestone Description: As documentation is mandatory for any service published on SNET, we will create a repository on how to test and use our services. Furthermore, we will publish a closeout report for the community.
  • Milestone deliverable: 
    • 1. README

    • 2. User guide

    • 3. LICENSE with SNET standard license

    • 4. Project closeout report for the community

  • Milestone related budget: $792 US
  • Period: week 8

Budget Summary: 

Total requested amount: $21.920 USD in AGIX

  • Milestone 1: $2.592 USD
  • Milestone 2: $8.352 USD
  • Milestone 3: $4.704 USD
  • Milestone 4: $792 USD
  • Hosting/API Call Usage: $5.480 USD (25% of the budget)

Note: Project management and marketing costs are not included in the proposal budget as they are covered by TrustLevel itself.

Risk and Mitigation

We see the main risk for the successful implementation of this proposal in technical challenges in the integration process. 

1. Main Risk: Technical Integration Challenges

Integrating our solution into SingularityNet's AI Marketplace may encounter technical challenges. The integration process might involve compatibility issues, unexpected dependencies, or complexities that could delay the implementation timeline.

However, the guidelines for integrating new services into SNET are well documented, so we believe we are already well prepared..

Nevertheless we will adopt following strategies to address the risk:

Mitigation:

  • Comprehensive Technical Assessment: Before initiating the integration, we will conduct an in-depth technical assessment of both TrustLevel's solution and SingularityNet's AI Marketplace to identify potential points of conflict, such as differing programming languages, communication protocols, or data formats.
  • Thorough Testing: We will conduct comprehensive testing of the integration process in a controlled environment before deployment. This will help identify and rectify any technical issues early on.
  • Collaboration with SNET: We will maintain open communication with SingularityNet's technical team throughout the integration process. This collaboration can lead to quicker problem-solving in case of technical roadblocks.
  • Use of Standard Protocols: Whenever possible, we will use standard protocols and APIs for integration. Standardized protocols reduce the likelihood of compatibility issues and simplify the integration process.

2. Risk: User Adoption and Engagement

Despite working with a great team on a robust solution, there might be challenges in attracting users to TrustLevel's services on the AI Marketplace. User adoption may not meet expectations, leading to underutilization of the developed capabilities.

Mitigation: To mitigate this risk, we encourage user adoption:

  • Educational Initiatives: We will launch educational and promotional campaigns to raise awareness about the importance of online information verification and the benefits of using TrustLevel's services. 
  • Feedback Mechanism: We will implement a feedback mechanism to gather user insights and suggestions for improvement. This will allow the team to address user concerns promptly and enhance the service based on real-world usage.
  • Early Adopters: We consider offering incentives, such as rewards or discounts, to early adopters who use TrustLevel's services. This can motivate users to try out the solution and provide valuable feedback.

Voluntary Revenue

API Calls:

We will onboard one TrustLevel service on the platform as part of this proposal. If this service crosses the threshold of $1.000 USD revenue per month, 10% of the additional revenue will be fed back into the SNET/DeepFunding wallets. This condition will remain valid for five years after first onboarding the service and will be applicable to this service or any subsequent iteration of this service on the platform.

Open Source

TrustLevel is not open source yet. 

However, we expect that TrustLevel will contribute to more trustworthiness on the internet, and therefore, we plan to release all elements of TrustLevel (including the algorithm, KG/KB) in open source in order to make TrustLevel itself transparent as well. But details (licence model) have not been decided at this stage of the project. 

Our Team

Team Lead: Dominik Tilman 

Dominik is founder of TrustLevel and will be the lead on this proposal. He has been active in the blockchain scene for several years and is deeply involved in Cardano's Project Catalyst (the counterpart to Deep Funding) since the beginning. He has 15+ years in innovation management and company building. With his company CONU21 he mainly advises startups and actively helps in the founding phase to develop the right business model and to market the ideas successfully.

TrustLevel's AI & Blockchain Experts and Data Scientists:

Thomas Zuchtriegel: 15+ years in building teams, building products and building companies. Deep passion for emerging technologies to create innovative digital experiences. Co-founder Corticore (make pro athletes better using AI & VR), Co-founder bluquist (AI-driven talent & potential platform), managing partner metaverse GmbH (Innovation consultancy).

Dr. Margarita Diaz Cortes: 10+ years in AI research, Optimization algorithms, Machine Learning, Computer Vision, and applications in Engineering and Medicine; NLP techniques including Ontologies and LLMs.

Sergey K.: Experience: Former student assistant in the field of quantum supervised ML + experience in Blockchain technology.

Iddo Lev (PhD): 20+ Years of Research and Engineering Experience in AI, NLP, Knowledge Representation, Logic.

Ohad Koren: 10+ Years experience as full stack developer and data scientist.

 

Zsolt Kallos: 15+ Years experience in software development, AI/Machine Learning, GAI, Generative Adversial Networks

 

Related Links

AI Services

Proposal Video

TrustLevel Integration into SNET/AI Marketplace - #DeepFunding IdeaFest Round 3

26 September 2023
  • Total Milestones

    5

  • Total Budget

    $21,920 USD

  • Last Updated

    12 Aug 2024

Milestone 1 - Kick-Off & Framework Mapping

Status
😀 Completed
Description

Kickoff meeting to define and map the framework and the exact technical implementation with the team. The team also instals and tests the necessary environment and tools (Dockers, etc.) to ensure that the implementation phase runs smoothly. 

Deliverables

Budget

$2,592 USD

Milestone 2 - Write Code, Clients and API for gRPC

Status
😀 Completed
Description

To implement TrustLevel services on SingularityNET we must provide our API in gRPC, an open-source universal RPC framework. This milestone includes (1) the creation of the protocol buffers; (2) the server logic and code for the web server and gRPC server that can handle request for our TrustLevel services; (3) the code that creates a gRPC client that can call the ‘Content quality’ method of our Trustlevel service.

Deliverables

Budget

$8,352 USD

Milestone 3 - Publishing on AI Marketplace

Status
😀 Completed
Description

To publish our TrustLevel service on the AI Marketplace as SNET services we must accomplish the following tasks: (1) specify the services model using protobuf file; (2) create the services metadata; (3) create account and publish the service; (4) (test-) run SNET Deamon; (5) testing API call capabilities. 

Deliverables

Budget

$4,704 USD

Milestone 4 - Documentation

Status
😐 Not Started
Description

As documentation is mandatory for any service published on SNET, we will create a repository on how to test and use our services. Furthermore, we will publish a closeout report for the community.

Deliverables

Budget

$792 USD

Milestone 5 - Hosting/API Call Usage

Status
😐 Not Started
Description

Deliverables

Budget

$5,480 USD

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