Questions worth exploring
Ask what sits behind a label.
When evaluating entity intelligence, begin with the information your team needs to assess a reference. Ask where a label comes from, what it describes, and which parts remain uncertain. Entity Intelligence pairs address clustering with sourced references, so every label carries its evidence and a confidence indicator.
Illustrative examples with fictional entities and sample data.
- Keep in view · 01
Source context
Specify the source details, dates, and supporting material your reviewer would want to examine. Ask how changes or conflicting references would be explained.
- Keep in view · 02
Attribution boundaries
Distinguish the questions your team has about an address, a service, and a legal entity. Ask which relationships can be supported by available evidence.
- Keep in view · 03
Use in a review
Describe where entity context would be used in your workflow and who would assess it. Make the required review context explicit before discussing any output.
Entity profile demonstration
One profile. Every claim with its evidence.
An entity profile brings together the category, the addresses, the activity and the sources in one place, and shows how confident each part of the attribution is.
Illustrative demo data with a fictional entity. No live data is shown or looked up on this website.
Address clustering
See how addresses connect, and how sure we are.
Line style shows the strength of the evidence behind each connection. Solid mint is confirmed. Solid teal is evidence-supported. Dashed is possible. Dotted grey is unverified.
Illustrative demo data with a fictional entity and addresses.
Attribution evidence
Every label explains itself.
Open any item to see the source, its date, the wallet it refers to, what was observed, how confident it is and who last reviewed it. Conflicting evidence stays next to the label, not hidden behind it.
1Entity public disclosureSelf-reported statementHigh
- Source date
- Sep 12, 2024
- Referenced wallet
- 0x3be0..5d17
- Supporting observation
- Address listed in the entity’s published statement of hot wallets.
- Confidence
- High
- Last reviewed
- Oct 24, 2024
- Reviewer notes
- Statement is dated. Re-check on each update.
2Address clustering analysisBlockchain analysisMedium
- Source date
- Oct 24, 2024
- Referenced wallet
- 0x9c41..e07a
- Supporting observation
- Deposit address sweeps to the hot wallet within minutes, repeatedly.
- Confidence
- Medium
- Last reviewed
- Oct 24, 2024
- Reviewer notes
- Pattern is strong but observed on few occasions.
3Third-party label setPublic referenceLow
- Source date
- Aug 03, 2024
- Referenced wallet
- 0x7d0f..c81e
- Supporting observation
- Listed under the same label as the hot wallet.
- Confidence
- Low
- Last reviewed
- Oct 22, 2024
- Reviewer notes
- Secondary source. Do not rely on it alone.
4Behavioural heuristicAutomated patternLow
- Source date
- Oct 24, 2024
- Referenced wallet
- 0x2ac9..04f6
- Supporting observation
- Withdrawal batches resemble those of the hot wallet.
- Confidence
- Low
- Last reviewed
- Oct 24, 2024
- Reviewer notes
- Similarity only. Kept as a possible relationship.
Exchange (example)
Medium Evidence-supported, under review
- 4 supporting sources
- 1 conflicting source
- Oct 24, 2024 last reviewed
Community label list
Labels 0x7d0f..c81e as an “OTC desk” (Jul 2024). Source confidence: Unverified.
Status: Unresolved. Kept visible. Reviewer note: do not merge labels without source review.
- Aug 03Label added from a third-party set
- Sep 12Entity statement published
- Oct 24Reviewed; confidence Low → Medium
Illustrative demo data with a fictional entity.
Entity search and exploration
Search by name, address, hash or category.
Explore entities by name, wallet address or transaction hash, then narrow by category, network, jurisdiction and risk indicator. Every result shows its confidence.
- EXExchange (example)Centralised exchange · Ethereum, Bitcoin, Tron
- CUCustody service (example)Custody provider · Ethereum, Arbitrum
- PAPayment processor (example)Payment service · Ethereum, Tron
- MIMixing service (example)Mixing service · Ethereum, Bitcoin
- DEDeFi protocol (example)DeFi protocol · Ethereum, Arbitrum
- UNUnattributed clusterUnattributed · Bitcoin
No entities match these filters. Loosen a filter to see more.
Illustrative demo data with fictional entities. This search does not query any real data.
Attribution boundaries
Know what a label can and cannot tell you.
Responsible use of entity intelligence starts with its limits. These five principles apply to every label, on every page of the product.
- 01
A label does not establish legal ownership
AddressServiceLegal entityNot established by a label - 02
Confidence can differ between addresses
0x3be0..5d17High0x7d0f..c81eMedium0x2ac9..04f6Low - 03
Sources may change over time
AugLabel addedSepSource updatedOctConfidence revised - 04
Entity information requires human review
Reviewer decidesLabel and confidence are inputs, not outcomes. - 05
Conflicting or incomplete evidence stays visible
Source AExchangeSource BOTC deskBoth shown, neither hidden
Responsible use. Entity Intelligence supports a reviewer. It does not decide who owns an address, and its labels are not legal determinations.
Prepare a focused conversation
Bring a scenario. Define what you want to learn.
For an evaluation, use a fictional entity label and outline the supporting information you would expect to see. We’ll walk through source provenance, confidence language, and the update process for your scenario.
- 1Identify the context needed
- 2Question the attribution
- 3Plan the review
A simple way to structure your evaluation call.
Identify the context required
Specify the entity categories
Select relevant networks
Define acceptable evidence
Define required confidence
Lower-confidence labels stay visible and are marked.
Plan the review workflow
Choose the expected output
Product verification
What needs confirmation
Entity Intelligence combines address clustering with sourced entity references, so reviewers can see where a label comes from and how confident it is. Use these questions to confirm the details that matter for your evaluation.
- Ask · 01
Supported entity categories
Which kinds of entity are covered, and which are not?
- Ask · 02
Supported networks
Which networks can be attributed for your use case?
- Ask · 03
Address-clustering methodology
How are addresses grouped, and how is that explained to a reviewer?
- Ask · 04
Evidence sources
Which sources support a label, and how are they weighted?
- Ask · 05
Confidence calculation
How is a confidence level derived, and can it be inspected?
- Ask · 06
Update frequency
How often are labels and sources refreshed?
- Ask · 07
Historical attribution
Can earlier labels and their changes be reviewed?
- Ask · 08
API availability
Which entity data can be retrieved through the API?
- Ask · 09
Export options
Which formats can entity evidence be exported in?
- Ask · 10
User permissions
Who can view, review and change an attribution?
These are evaluation questions, not guaranteed functionality. Answers depend on your deployment and are agreed with the team during your evaluation.
Before your demo
Entity Intelligence: questions and answers
Does an entity label establish ownership?
An entity label reflects a sourced reference, not a legal determination of ownership. Each label includes its source and a confidence indicator so your team can judge how much weight to give it.
Which entities are covered?
Coverage spans exchanges, services, and other frequently referenced entities identified through address clustering and sourced intelligence. Ask for the current coverage summary for your use case.
Can entity information be accessed by API?
Yes, through the Risk & Compliance API. See that page for endpoint and integration details.
Start a conversation
Explore your entity-intelligence questions
Tell us which context, sources, and attribution details your reviewers need.