Get co-occurring entity counts per graph entity over a bounded window

Distinct counts of the entities that share a transaction with each requested entity inside the window — cards, fingerprints, emails, phones, IP addresses, customers, merchants — plus the transaction count and black-list membership. Renders the RELATIONS list of the investigation screen, so the whole batch is answered by one ClickHouse pass plus one indexed Postgres lookup: asking for the full rail costs the same scan as asking for one entity. Counts are exact (uniqExact), so they always match the number of members the list endpoint returns. A same-type relation is omitted: one transaction row carries one value per type, so linking two values of the same type is a two-hop question for graph-links/get. The window is required and its span is capped server-side

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Body Params
entityList
array of objects
required
length between 1 and 50

Source entities to resolve relation counts for, max 50. Duplicates are collapsed server-side. The whole batch is answered by one ClickHouse pass, so asking for the entire rail costs the same scan as asking for one entity

entityList*
string
enum
required

Source entity type to resolve relations for

Allowed:
string
required
length between 1 and 512

Source entity value. For CUSTOMER and MERCHANT it is the entity UUID; it is lower-cased server-side because ClickHouse renders UUIDs in canonical lower case

date-time
required

Window start (inclusive)

date-time
required

Window end (inclusive). The span must not exceed 90 days

Headers
string
string
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