The FlowLens toolset
Tools for tracking wallets and reading activity
Three instruments, each aimed at one step of a session: read a wallet's recent activity, group addresses that look related, and get a plain-language recap before you open the raw data. This page covers what each tool does, what it leaves to you, and how outside data sources fit in.
The Wallet Tracker
Start with an address, finish with a question
The tracker takes an address, a set of addresses, or a case you have already saved, and returns recent activity with the counterparties and tokens involved. It is a starting point for reading a wallet rather than a verdict about it. Most sessions begin here and move to clustering once the basic activity is clear.
Exporting the activity list keeps the work auditable. If a conclusion later depends on a specific transfer, you have the record.
Wallet Clusters
Grouping you are allowed to disagree with
Wallet Clusters groups addresses that show signals of shared control. Common funding sources, timing patterns, and repeated interaction with the same contracts all feed the grouping, and the view shows which signals applied to each cluster rather than only the finished group.
That transparency matters more than the grouping itself, because it lets you disagree with the tool. Clusters are hypotheses. Treat them as such, and the grouping becomes a way to reframe a question rather than a claim to defend.
Review Wallet Clusters
AI Activity Summary
A first pass, written in plain words
AI Activity Summary produces a plain-language recap of what a set of wallets did in a chosen window. It is designed for the first pass: an unfamiliar address, or a cluster with too many transactions to read line by line.
Generate an AI Activity SummaryHow a summary arrives
Transfers, counterparties, tokens, and timing across the wallets and the window you select, not the whole history of the chain.
Patterns worth a second look, with the specific transactions that drove each one named alongside, so the recap can be checked rather than trusted.
It is a summary, not an analysis. Confirm anything you intend to use against the raw transactions, and check whether the summary's window matches the period you actually care about.
Re-read the flagged transfers, note the window you used, and carry both into a research note so a later reader can retrace the step.
The summary is generated from the data the tracker returns in your session. Where a window is too thin to say anything useful, it says so instead of filling the gap.
Referencing third-party sources without over-claiming
Analysts work across several products, and research notes frequently cite outside sources for context. Those notes are stronger when the source is named, the method is stated, and no relationship is implied where none exists. This is how outside references are handled in a FlowLens session.
Each of the products below is independent. FlowLens references them where a method needs their data, and does not present any of them as a partner, sponsor, or endorser.
The rule that holds
When two sources disagree, note the disagreement and check the transactions yourself.
A disagreement is data. It usually means the two products are measuring different things, or the same thing at different times, and finding out which is part of the work.
Outside sources a session may cite
A familiar reference for wallet labeling and smart-money tracking across many blockchains.
A common free starting point for DeFi market structure and total-value-locked comparisons.
Cited for exchange-flow work, where the question is what moved toward or away from trading venues.
A reference for derivatives positioning when a token flow question reaches the futures side.
Sits in the query-driven category for custom analysis, useful when a standard view does not answer the question.
Belongs to investigations and risk workflows, where provenance and counterparty screening carry the weight.
Names appear here because methods reference them, not because of any commercial relationship. Where a source is used in a note, the note states what was taken from it.
GMGN
Using GMGN as a data source
GMGN is supported as a third-party analytical data source that can be consulted during a research session. It is a source you can pull alongside the Wallet Tracker when a flow needs a second read, and it can be named in a note the same way any other outside reference is named.
FlowLens does not claim a partnership with GMGN, and nothing on this site should be read as an endorsement by that product. Where its data is used, note the source, the time of the reading, and what question it was answering.
The practical rule is simple: when two sources disagree, note the disagreement and check the transactions yourself.
Where portfolio trackers fit
Some questions are about positions rather than behavior. Zapper and CoinStats cover that ground, letting you see holdings across wallets and exchanges, and they are typically the right first stop when the question is what these wallets hold rather than what they have been doing.
FlowLens does not replace a portfolio view. The two answer different questions, and a session often uses both: the portfolio view to see what is held, the tracker and clusters to see what moved and when.
Holdings across wallets and exchanges in one view.
The same positional question, answered with a different interface.
How the toolset grows
The architecture is built to accept new data sources and analytical modules without redesigning the workflow around them, so a tool you learn today keeps its shape when the analyst behind it changes.
When a new source is connected
The tool notes which chains it can query and how fresh the data is, so you know the reach of the reading before you rely on it.
When a new module is added
It ships with a method note before it becomes a default part of a session.
That order is intentional. A module without documented method is just an opinion with an interface.
Working within the tool's limits
No tracker sees everything. Coverage varies by chain, labels go stale, and clustering can be wrong. The interface exposes those limits in the data it returns, and research notes repeat them where they matter.
If a question cannot be answered with the data available, the tool will not invent an answer. That restraint is part of the design, not a missing feature, and it is the reason a note built on these tools can be handed to someone else.
Ask about a data source
If you want to know whether a particular source or chain is covered, or how a method would be documented before it is adopted, send the question with the workflow you have in mind.
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Questions that come up
Which chains does the tracker read?
Coverage varies by chain, and the tracker states which chains a view can query before it returns anything. Where a chain is not covered, the tool says so rather than showing an empty result you might read as inactivity.
What does the export actually contain?
The activity list for the addresses and the window you selected: transfers with counterparties and tokens, so a later reader can trace the specific transaction a conclusion rests on. It is a record of what the view returned, not an interpretation of it.
Can I rely on a cluster as a conclusion?
Treat it as a hypothesis. The view lists the signals that produced the grouping, so you can test it against the transactions and keep it, narrow it, or drop it. A cluster you disagree with is still useful, because it tells you where the evidence stops.
How current are the figures?
Every source carries its own freshness, and the tool shows the timestamp it is working from so you can judge whether a reading fits the period you care about. When you write the finding down, record that timestamp next to it.
Is FlowLens partnered with any of these products?
No. Products named on this site, including GMGN, Nansen, DeFiLlama, CryptoQuant, CoinGlass, Flipside, Elliptic, Zapper, and CoinStats, are independent third parties referenced as sources and comparison points. No partnership, sponsorship, or endorsement is claimed in either direction.
Take one question into the toolset
Pick an address you have been meaning to understand, run it through the tracker, and let the cluster view and the summary tell you what else is worth asking. If the first reading raises a question about method or coverage, that is the right moment to ask.
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