Where the reasoning has to survive an audit.
The longest thread in my work. A global BI platform and a drug development analytics portfolio, and now agentic workflows in regulated healthcare content.
What is different here
In most sectors the question about an automated decision is whether it was right. Here it is whether you can reconstruct, months later, why it was made, on which version of which data, reviewed by whom. That single difference changes what you have to build. Lineage stops being good practice and becomes the thing that decides whether you go live at all.
What usually needs fixing
Data integrity expectations apply to a reporting layer as much as to a laboratory system, and teams discover this at the point of go live rather than at design.
In regulated marketing the constraint is not the model. It is whether the human review, the approval and the reasoning can be produced when somebody asks.
Personal and patient adjacent data arrives from several systems with different consent bases, and joining them quietly creates a record nobody has a basis to hold.
Where I have done it
2 of the seven case studies are in this sector.
The work this usually involves
Six services, and most engagements touch three of them. Which three depends on where the chain is breaking rather than on what you came in asking for.
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