The Modern Analytics
Life sciences and healthcare

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

Validated systems reach analytics before anyone says the word AI

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.

Content and claims carry a review trail

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.

Consent and provenance travel with the record

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.

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