CHAINTEL: On-Chain Analytics and Blockchain Intelligence Suite

SHORT SUMMARY 

The On-Chain Analytics and Blockchain Intelligence Suite provides a dedicated environment for ingesting, processing, and analysing large-scale public blockchain data, with a primary focus on Bitcoin and Ethereum networks. Built on NVIDIA RTX 6000 ADA and H100 NVL GPUs combined with high-capacity storage infrastructure, CHAINTEL is configured to handle the volume and complexity of on-chain transaction data, supporting graph-based analytics, machine learning-driven pattern recognition, and temporal analysis of blockchain activity. Unlike general-purpose data analytics platforms, CHAINTEL is specifically oriented toward the structural and analytical characteristics of distributed ledger data, including UTXO and account-based transaction models, address clustering, and network topology analysis. The platform supports research and applied use cases spanning transaction flow analysis, entity identification, market behaviour modelling, and the study of emergent network phenomena on public chains. This testbed contributes to the CITADELS Framework by providing accessible infrastructure for blockchain intelligence research at a scale and specificity not typically available in standard academic computing environments.

HOSTING INSTITUTION AND PI INFO

Name of Host Organization NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa
Department or Lab MagIC (Information Management Research Center) – the NOVA Information Management School research and development center
Name of Building Manuel Vilares Building
Physical Address Campus de Campolide, 1070-312 Lisboa
Website Links https://www.novaims.unl.pt/
Institutional contact name Cristina Oliveira
Institutional contact email magic@novaims.unl.pt

APPLICATION CASES 

Application case: Short description:
Bitcoin Transaction Graph Analysis Construct and analyse large-scale transaction graphs derived from the Bitcoin UTXO model, applying graph analytics and network science methods to study transaction flow patterns, address clustering, and the structural properties of the Bitcoin transaction network over time.
Ethereum On-Chain Behaviour Modelling Process and analyse Ethereum account-based transaction data to study wallet behaviour, token transfer patterns, and interaction networks between addresses, including the identification of smart contract interactions and decentralised application usage patterns.
Anomaly and Suspicious Pattern Detection Develop and evaluate machine learning models for detecting anomalous transaction patterns on public blockchains, exploring approaches applicable to the identification of structuring behaviour, mixing services, and other patterns of interest for compliance and research purposes.
Temporal Analysis of Blockchain Network Evolution Analyse how Bitcoin and Ethereum network topology, transaction volumes, and participant behaviour have evolved over time, supporting longitudinal studies of adoption, market cycles, and the impact of protocol changes on network activity.
MSc and PhD Research in Blockchain Analytics The platform supports graduate students conducting dissertation and research projects in blockchain data science, providing the storage capacity and compute required to work with full or partial chain datasets in a reproducible academic research environment.

POTENTIAL STAKEHOLDERS

Non-academic stakeholders

Industrial Partners, Startups, Professional Associations, SMEs, Government Bodies

Academic stakeholders

Undergraduate students, PhD students, MSc students, Researchers

Privacy Preference Center