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DAC | Digital Asset Claims
Transaction Graph Analysis

Digital Asset Claims Asset Relationship & Entity Mapping

Asset Relationship & Entity Mapping builds a documented relationship map between wallets, transactions, contracts, platforms, domains and other digital identifiers, showing how observed elements connect and on what evidential basis each connection rests.

Typed graph of wallets, entities and domains with evidenced, weighted connections

Why Isolated Findings Do Not Show Structure

Individual findings — an address here, a domain there, a company name in a filing — sit as separate facts until the relationships between them are made explicit. Structure only becomes visible when the links are drawn and each link is justified.

The risk is the opposite failure: drawing a graph that looks convincing while some of its edges rest on nothing more than coincidence. A mapping is only useful when every edge carries the reason it exists and the strength of the support behind it.

Scope Of Relationship Mapping

This is Transaction Graph Analysis extended across all forms of digital identifier relevant to a matter, not only wallet addresses. It links wallets to the transactions and contracts they have interacted with, links those contracts and platforms to any associated domains, and links digital identifiers (usernames, email addresses, wallet labels) to the entities they are associated with in the available evidence.

The result is a network view: a graph in which each node is a wallet, contract, platform, domain or identifier, and each edge represents a documented relationship such as a transaction, a shared identifier, a domain registration link or a corroborated public association.

Entity Resolution

Where multiple identifiers (an address, a username, a domain) are found to relate to a single underlying entity, that resolution is recorded together with the specific evidence supporting it, distinguishing entity resolution supported by direct evidence from resolution based on circumstantial pattern alone.

Cross-Domain Linking

Where a wallet or contract is publicly associated with a domain or platform (for example, through a published address on a website, or a domain used in a labelled scam report), that association is recorded as a graph edge with its supporting source.

Inputs That Feed A Map

The outputs of prior work (a transaction reconstruction, an OSINT research file, an infrastructure profile) or a fresh set of identifiers to map. Mapping is generally most effective as a synthesis step once other Digital Asset Claims services have produced their own documented findings.

How Connections Are Established

Each documented relationship from the underlying evidence is added to the map as an edge with its source reference. Relationships are never inferred purely because two elements appear near each other in time; every edge in the final map traces back to a specific piece of supporting evidence, which is available for review alongside the map itself.

What A Mapping Engagement Produces

A visual and written relationship map, with an accompanying index that lists every node and edge together with the evidence supporting it.

What A Map Deliberately Leaves Open

A relationship map documents observed connections; it does not establish legal ownership, control or liability on its own. Where the underlying evidence for a relationship is weak or single-source, the map marks that edge accordingly rather than presenting every connection with equal weight.

Technology

Technology Applied To Entity Mapping

  • Graph modelling

    Addresses, entities, domains and identifiers are modelled as typed nodes with typed, evidenced edges.

  • Edge provenance tracking

    Every connection stores the specific source record that established it.

  • Cluster overlay

    On-chain clustering results are overlaid on off-chain entity data to show where the two agree.

  • Weighted confidence scoring

    Edges are weighted by the strength of their supporting evidence rather than presented uniformly.

Data

Data Examined In Entity Mapping

  • Wallet addresses and their clustering relationships
  • Corporate registry records, officers and registered addresses
  • Domains, hostnames and shared infrastructure links
  • Contact identifiers appearing across multiple sources
  • Publicly documented platform and service affiliations
  • Transaction relationships between mapped addresses
  • Timing coincidences that suggest, but do not prove, coordination

How Entity Mapping Runs

  1. Step 01

    Inventory the entities

    Every known address, name, domain and identifier is listed as a candidate node.

  2. Step 02

    Type the nodes

    Nodes are classified so on-chain and off-chain objects are never silently conflated.

  3. Step 03

    Draw evidenced edges only

    A connection is drawn only where a specific source record supports it.

  4. Step 04

    Record edge provenance

    Each edge stores its supporting record so it can be checked in isolation.

  5. Step 05

    Weight the edges

    Edges are graded by strength, so weak links are visibly weak.

  6. Step 06

    Test alternative readings

    Where a cluster could be explained innocently, that alternative is recorded alongside it.

  7. Step 07

    Publish the map

    The map is delivered with a written key explaining every node and edge type.

Deliverables

Output 01

Relationship Graph

Visual map of wallets, contracts, platforms, domains and identifiers with documented connections.

Output 02

Edge Evidence Index

Every connection in the graph cross-referenced to its supporting source material.

Output 03

Entity Resolution Log

Identifiers resolved to a single entity, with the evidence and confidence for each resolution.

Output 04

Unresolved Node List

Elements that could not be connected to the wider map with available evidence.

Evidence Confidence Classification

Every finding is graded so that what is established, what is indicative and what remains unresolved are never presented as the same thing.

Verified
Independently confirmed by two or more unrelated sources.
Strongly Supported
Consistent with multiple sources, with no material contradiction observed.
Partially Supported
Consistent with at least one source, but corroboration is incomplete.
Unverified
Recorded as observed, but no independent corroborating source has been located.
Conflicting
Sources disagree, and the conflict is documented rather than resolved by assumption.
Insufficient Evidence
Available material does not support a finding in either direction.

Limitations of This Service

Findings are bounded by the material that is lawfully available at the time of the engagement. Digital Asset Claims does not access private accounts, credentials or systems, does not perform any unauthorised or intrusive technical activity, and does not guarantee that a given question can be answered. Where the evidence does not support a conclusion, the report says so rather than inferring one. A documented relationship between elements does not by itself establish legal ownership, control or responsibility; each edge in the map is graded by the strength of its supporting evidence.

Questions

Does a connection on the map prove common ownership?

No. Each connection is graded by the evidence behind it. Some edges reflect direct transactional evidence; others reflect weaker, circumstantial association, and the map distinguishes between them.

Can this service work from a blank starting point?

It is most effective once at least some underlying evidence exists — from a transaction reconstruction, OSINT research or infrastructure analysis — for the map to be built on.

Is the map delivered as an image or a data file?

Both: a readable visual map and an underlying reference index so every connection can be checked against its source.

Holding a pile of findings that do not yet form a picture?

Send what you have collected. We will map what the evidence connects, and say plainly what it does not.

Request An Entity Mapping