Cardano Data Sync for AI Developers

[Proposal setup] Proposal title

Please provide your proposal title

Cardano Data Sync for AI Developers

[Proposal Summary] Budget Information

Enter the amount of funding you are requesting in ADA

100000

[Proposal Summary] Time

Please specify how many months you expect your project to last

6

[Proposal Summary] Translation Information

Please indicate if your proposal has been auto-translated

No

Original Language

en

[Proposal Summary] Problem Statement

What is the problem you want to solve?

Cardano lacks proper tools for AI developers. Current data solutions like cardano-db-sync rely on SQL databases, which are not optimized for AI, limiting ability to leverage Cardano’s data for AI devs

[Proposal Summary] Supporting Documentation

Supporting links

• https://github.com/RManLuo/Awesome-LLM-KG?tab=readme-ov-file#kg-enhanced-llms
,
• https://www.w3.org/RDF

[Proposal Summary] Project Dependencies

Does your project have any dependencies on other organizations, technical or otherwise?

No

Describe any dependencies or write 'No dependencies'

No dependencies

[Proposal Summary] Project Open Source

Will your project's outputs be fully open source?

Yes

License and Additional Information

The project will be released under the Apache 2.0 License, ensuring community access to copy, inspect, and modify the codebase. High-quality documentation, including setup guides and usage references, will be provided at MOBR’s public GitHub repository to serve the Cardano community.

[Theme Selection] Theme

Please choose the most relevant theme and tag related to the outcomes of your proposal

AI

[Campaign Category] Category Questions

Mention your open source license and describe your open source license rationale.

The project will use the Apache 2.0 License, chosen for its permissive nature, allowing broad community access to copy, modify, and distribute the codebase. Focusing on collaboration and innovation. Apache 2.0 ensures compatibility with other open-source projects, encourages adoption by AI and Web3 developers, and supports interoperability with tools like Apache Jena.

How do you make sure your source code is accessible to the public from project start, and people are informed?

To ensure public access from project start, the cardano-rdf-sync codebase will be hosted on MOBR’s public GitHub repository, with all commits, issues, and pull requests visible. A dedicated project page will be created, linked from MOBR’s website and shared via Cardano community channels (e.g., forums, X posts). Regular updates on development progress will be posted on GitHub and social platforms to keep the community informed. The repository will include a README with setup instructions and contribution guidelines to encourage early engagement and feedback from developers.

How will you provide high quality documentation?

Documentation will follow best practices, using clear, concise language and visual aids. Community feedback will be incorporated through GitHub issues to ensure clarity and usability, enabling developers to effectively utilize cardano-rdf-sync for building AI-driven applications on Cardano. The final walkthrough video will include setup guides, SPARQL query examples tailored for AI developers and will be hosted on YouTube.

[Your Project and Solution] Solution

Please describe your proposed solution and how it addresses the problem

cardano-rdf-sync will synchronize Cardano blockchain data (e.g., transactions, accounts, datums, etc.) into a triplestore according to the recently developed Cardano Ontology (https://mobr.ai/cardano)..) A triplestore can be considered as a database optimized for semantic queries using RDF.

This enables developers to query blockchain data using SPARQL, a query language ideal for graph-based data, which is more suitable for AI applications than traditional SQL databases.

The tool will include:

• Sync Engine: Extract data from cardano-node
• Data Transformer: Apply ontology rules to produce RDF
• Triplestore Loader: Insert RDF into a triplestore
• Documentation & Examples: For AI and Web3 developers

This solution addresses the problem by providing an AI-tailored data access layer, enabling faster development of innovative applications like analytics dashboards, graph building for LLM integration, fraud detection systems, or knowledge graphs for Cardano’s ecosystem.

[Your Project and Solution] Impact

Please define the positive impact your project will have on the wider Cardano community

cardano-rdf-sync will enhance the Cardano developer ecosystem by:

• Enabling AI Innovation: Providing AI developers with semantic data access to build advanced dApps, such as predictive analytics for DeFi, AI-driven governance tools, Large Language Models, fraud detection systems, or knowledge graphs for Cardano’s ecosystem.
• Improving Developer Experience: Simplifying data querying with SPARQL, reducing development time for some applications.
• Driving Adoption: Attracting AI and data science communities to Cardano, expanding the developer base and supporting ecosystem growth.
• Supporting Interoperability: Enabling integration with other semantic web technologies, enhancing Cardano’s role in cross-chain ecosystems.

In addition, cardano-rdf-sync can be highly significant for projects like the Cardano Analytics Platform (CAP) (https://milestones.projectcatalyst.io/projects/1300034) which relies on knowledge graphs to enable semantic querying and natural language processing. Unlike cardano-db-sync, which stores blockchain data in a PostgreSQL database requiring additional storage and transformation to align with CAP’s ontology, cardano-rdf-sync will directly sync Cardano data into an RDF model, inherently suited for knowledge graphs. This eliminates complex data transformation pipelines, ensuring semantic consistency with CAP’s ontology (covering concepts like transactions, stake pools, and governance) and enabling efficient SPARQL queries for use cases such as transaction analysis or governance engagement. By streamlining knowledge graph population and aligning data with Cardano’s unique features (e.g., extended UTXO, Ouroboros protocol), cardano-rdf-sync enhances CAP’s ability to deliver precise, context-aware analytics to diverse users, from developers to enthusiasts. CAP’s milestone 1 technical report details impactful use cases with queries including:

• Largest ADA transactions in the last 24h
• Monthly smart contract deployments
• Vote counts on governance proposals
• NFT minting activity
• Stake pool engagement metrics

[Your Project and Solution] Capabilities & Feasibility

What is your capability to deliver your project with high levels of trust and accountability? How do you intend to validate if your approach is feasible?

Our team has experience in blockchain technology, data analytics, and AI. We have successfully delivered a Decentralized Fact-Checking Toolkit project on Catalyst Fund 13 (1300076) and have an ongoing project also on Catalyst Fund 13 to leverage LLMs on an analytics platform (1300034).

Our background in ontology development and data extraction techniques that we have experienced as former IBMers, makes our approach both feasible and innovative. We are confident in our ability to deliver the project successfully due to our track record in similar projects.

[Milestones] Project Milestones

Milestone Title

Project Setup and Proof-of-Concept

Milestone Outputs

1. A public GitHub repository initialized with the project structure and Apache 2.0 license.
2. A working proof-of-concept sync engine that extracts instances of a single ontology class (i.e., cardano:CNT) from cardano-node.
3. Unit tests covering the basic functionality of the sync engine.
4. A walkthrough video demonstrating project setup, the sync engine, and test execution.

Acceptance Criteria

1. The GitHub repository is accessible to the public and contains the license, documentation, and initial codebase.
2. The sync engine can extract the blockchain data for the single ontology class and store it as RDF in a local triplestore (e.g., Virtuoso or Jena).
3. Unit tests validate the integrity of the extraction pipeline and run without errors.
4. The walkthrough video explains the POC build, execution and test execution.

Evidence of Completion

1. A GitHub link to the project.
2. Sync engine code extracting, transforming, and loading data of the single ontology class is available on GitHub link.
3. Source code of unit tests is available in the GitHub repository along with test results.
4. A walkthrough video link (unlisted YouTube URL) demonstrating all deliverables and verifying correct operation.

Delivery Month

1

Cost

20000

Progress

20 %

Milestone Title

Extraction Components

Milestone Outputs

1. Sync engine that extracts Cardano data across main ontology classes.
2. Unit tests covering the basic functionality of the sync engine.
3. A walkthrough video demonstrating project setup, the extraction components, and test execution.

Acceptance Criteria

1. The sync engine is capable of extracting multiple Cardano data types (blocks, transactions, governance, datum, etc.).
2. Unit tests are included in the public repository.
3. The walkthrough video presents the extracting components in execution and the tests execution.

Evidence of Completion

1. A GitHub link to the extractors code.
2. A GitHub link to the unit test files.
3. A walkthrough video link (unlisted YouTube URL or a google drive url) demonstrating all deliverables and verifying correct operation.

Delivery Month

3

Cost

30000

Progress

50 %

Milestone Title

Transforming and Loading Components

Milestone Outputs

1. A data transformer and loader components that align extracted data with the Cardano Ontology, generating compliant RDF triples.
2. Unit and Integration tests verifying transformer and loader components from Cardano node to triplestore (e.g., Virtuoso or Jena).
3. A walkthrough video showing sync engine execution, triplestore queries, and tests execution.

Acceptance Criteria

1. The data transformer component maps extracted data (blocks, transactions, governance, datum, etc.) to the Cardano Ontology and the loader component injects the transformed data into the triplestore.
2. Integration and unit tests validate both RDF generation and triplestore ingestion.
3. The walkthrough video shows the sync engine execution, triplestore queries, and tests execution.

Evidence of Completion

1. A GitHub link to the transformers and loader components code.
2. A GitHub link to the unit test files.
3. A walkthrough video link (unlisted YouTube URL or a google drive url) demonstrating all deliverables and verifying correct operation.

Delivery Month

5

Cost

30000

Progress

80 %

Milestone Title

Final Milestone

Milestone Outputs

1. A final closeout report summarizing the system architecture, use cases, lessons learned, and future roadmap.
2. A final walkthrough video demonstrating full end-to-end functionality and recommended deployment practices.
3. A release of the cardano-rdf-sync tool with installation instructions, documentation, and default configuration files.

Acceptance Criteria

1. The final report is publicly available on GitHub and includes technical documentation.
2. The video presents the sync engine execution, triplestore usage examples, and tests execution.
3. The GitHub repository includes tagged release of cardano-rdf-sync, and quick-start guide.

Evidence of Completion

1. Link to the final report published in the GitHub repository.
2. Final walkthrough video publicly hosted on YouTube.
3. A GitHub link to the cardano-rdf-sync code repository.

Delivery Month

6

Cost

20000

Progress

100 %

[Final Pitch] Budget & Costs

Please provide a cost breakdown of the proposed work and resources

Budget Distribution

Conceptual Design: 15,000 ADA

Development: 60,000 ADA

Testing: 15,000 ADA

Operational Costs: 10,000 ADA

Milestone costs

Milestone 1 (1 month): 20,000 ADA

Milestone 2 (2 months): 30,000 ADA

Milestone 3 (2 months): 30,000 ADA

Final Milestone (1 month): 20,000 ADA

[Final Pitch] Value for Money

How does the cost of the project represent value for the Cardano ecosystem?

cardano-rdf-sync delivers a reusable, open-source tool for AI developers, drives ecosystem adoption, and supports Cardano’s transparency goals. The project’s budget ensures efficient resource use, with tangible outputs (sync engine, rdf transformers, etc.) that provide long-term value to the community.

[Required Acknowledgements] Consent & Confirmation

Terms and Conditions:

Yes