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Identity & relationship data
Why one person turns into five records across messaging apps, and what a system has to get right before any of it is trustworthy.
What is Identity Resolution?
Identity resolution is the process of deciding whether two or more records refer to the same real person, then joining them into one view. Inside a single system this is trivial — there is a primary key. Across systems that were never designed to interoperate, there is no shared key at all, and the job becomes an inference problem with asymmetric costs: a missed match leaves a duplicate, but a wrong match silently blends two people into one.
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Cross-Channel Contact Deduplication
Cross-channel contact deduplication is collapsing the several records that different channels created for one person into a single contact — without collapsing two different people by accident. The naive version ("merge on exact match") fails in two directions: the fields that match exactly are often the unreliable ones, and merges chain, so a single bad join does not produce one bad record. It produces many.
Read →What is Relationship Memory?
Relationship memory is the layer that holds context about a person — who they are, how you know them, what you have agreed to, what is still outstanding — as opposed to merely storing the messages you exchanged. A message store answers "where did we discuss this?". Memory answers "what is true about this relationship right now?". The second question is not a search problem, and it depends entirely on the identity layer underneath being correct.
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