Alex Svanevik: Nansen excels in blockchain data attribution, the importance of quality assurance in labeling, and how data harmonization drives insights | Epicenter

Nansen's advanced labeling techniques transform blockchain data into actionable insights for traders and investors.

Listen on Epicenter

Share

Add us on Google by Editorial Team Apr. 10, 2026

Key takeaways

• Transforming raw blockchain transactions into insights involves multiple data processing layers.
• Nansen excels in the attribution layer, crucial for understanding on-chain flows.
• The attribution layer for labeling addresses includes both algorithmic and human efforts.
• Quality assurance is critical in maintaining trust in data labeling processes.
• Every label in the database is backed by compiled evidence to ensure accuracy.
• Public information on blockchains can be used to label addresses, with removal rights for individuals.
• Blockchains are inherently public and transparent, making information immutable.
• Labeling blockchain addresses involves studying behaviors and deterministic smart contract events.
• Data harmonization across different chains is essential for deriving meaningful insights.
• Address labeling has evolved to include agentic and algorithmic methods.
• The integrity of blockchain data labeling relies heavily on quality assurance.
• Blockchain technology’s transparency and immutability have significant privacy implications.
• Nansen’s labeling infrastructure provides real-time insights for investors and traders.
• Understanding blockchain transactions requires a combination of inference and flow analysis.
• The complexity of on-chain analytics highlights the need for advanced data processing techniques.

Guest intro

Alex Svanevik is the CEO and Co-founder of Nansen, a blockchain analytics platform pioneering AI-driven agentic trading. He previously served as Chief Data Scientist at CoinFi, where he built a crypto database and back-tested trading signals. Svanevik holds an MSc in Artificial Intelligence from the University of Edinburgh.

The process of transforming blockchain data

• Raw blockchain data must be extracted into a more efficient storage and compute layer.

• The most basic thing you have to solve is to get the raw on chain data into a more convenient storage and compute layer

  — Alex Svanevik

• Data harmonization across different chains is crucial for effective analytics.

• You need to kind of harmonize all that data

  — Alex Svanevik

• The attribution layer involves labeling addresses to provide context to blockchain transactions.

• The third part… is the attribution layer where you label the addresses

  — Alex Svanevik

• Nansen excels in the attribution layer, critical for understanding on-chain flows.

• We probably are the best in the world at the attribution layer

  — Alex Svanevik

• Transforming raw transactions into insights requires multiple data processing layers.

• You need to get the raw entredata into something that is more convenient for running analytical queries

  — Alex Svanevik

• The process involves both algorithmic and human efforts in address labeling.

• We’ve kind of evolved our approach to labeling addresses over the years

  — Alex Svanevik

The importance of data harmonization and attribution

• Harmonizing data across chains is essential for deriving meaningful insights.

• The second layer is you have to kind of harmonize the data cross chains

  — Alex Svanevik

• Address labeling has evolved to include both agentic and algorithmic methods.

• We also do a lot of algorithmic work that is not agentic but is still super important

  — Alex Svanevik

• The attribution layer is crucial for interpreting blockchain transactions.

• The third part which we i would say probably are the best in the world at is the attribution layer

  — Alex Svanevik

• Nansen’s expertise in attribution helps investors make informed decisions.
• The complexity of on-chain analytics highlights the need for advanced data processing techniques.
• Understanding blockchain transactions requires a combination of inference and flow analysis.

• You can literally send some money to binance and see where the flows go

  — Alex Svanevik

• Labeling wallets involves studying transaction behaviors and deterministic events.

Labeling blockchain addresses

• The process involves studying behaviors and deterministic smart contract events.

• You have to study the behaviors of different entities

  — Alex Svanevik

• Smart contracts provide deterministic events for labeling.

• Some behaviors are deterministic because they’re smart contract driven

  — Alex Svanevik

• Labeling wallets requires inference and transaction flow analysis.

• You can literally send some money to binance and see where the flows go

  — Alex Svanevik

• Quality assurance ensures trust in data labeling processes.

• We do focus a lot on quality assurance

  — Alex Svanevik

• Every label in the database is backed by compiled evidence.

• You cannot add a label to the database unless you’ve compiled the evidence for it

  — Alex Svanevik

• Public information is used for labeling, with removal rights for individuals.

• We rely on public information right information that’s in the public domain

  — Alex Svanevik

Quality assurance in data labeling

• Quality assurance is critical for maintaining trust in data labeling.

• It’s very it’s it takes a long time to gain trust but it’s very easy to lose trust

  — Alex Svanevik

• Every label is backed by evidence to ensure accuracy.

• You cannot add a label to the database unless you’ve compiled the evidence for it

  — Alex Svanevik

• The integrity of blockchain data labeling relies heavily on quality assurance.
• Ensuring high precision in data processing is essential for credibility.
• The rigorous approach to data labeling enhances reliability and reduces errors.
• Nansen’s commitment to quality assurance builds trust with users.
• Accurate labeling is crucial for interpreting blockchain transactions.
• The process of labeling involves both algorithmic and human efforts.
• Quality assurance practices are vital for maintaining data integrity.

Public information and privacy on blockchains

• Public information on blockchains can be used to label addresses.

• We rely on public information right information that’s in the public domain

  — Alex Svanevik

• Individuals have the right to request the removal of labels.

• If you come to us and you say hey I actually want that label removed as an individual you can do that

  — Alex Svanevik

• Blockchains are public and transparent by default.

• Look this is actually on the blockchain like this is not it’s like immutable

  — Alex Svanevik

• Information on blockchains is immutable and cannot be erased.

• Even if we remove it from our database the ens name is always gonna be etched into that address

  — Alex Svanevik

• The transparency of blockchain technology has significant privacy implications.
• Understanding the principles of blockchain data treatment is crucial.
• The distinction between individual and corporate identities is important in labeling practices.
• Ethical considerations are integral to operational policies regarding blockchain data.
• Public and transparent nature of blockchains affects data permanence.

Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.