WholeSum helps teams make sense of large volumes of text data with results they can stand behind.

Organisations increasingly rely on surveys, comments, reviews, posts, and other free-text data sources. But existing approaches force a trade-off: slow manual analysis, or quick AI summaries that are hard to defend.

WholeSum removes that trade-off. We combine language models with statistical methods to produce interpretations that preserve evidence, uncertainty, and structure. So results remain auditable, comparable, and defensible under scrutiny, ready to build on over time. 

Our story: 
For too long, organisations have relied on tools that flatten human experiences into tick boxes, numbers and Likert scales. Losing valuable light and shade in the process. When decisions depend on really understanding people, that kind of simplification comes at a cost.

WholeSum exists to change that. Our mission is to find the signals that matter most, no matter how complex the data. We believe organisations should collect the data they actually need, not what’s easiest to analyse. 

Our founders bring more than 20 years' combined experience across audience insights and research, with world-leading expertise in data science, mathematics and statistical inference.

With WholeSum we turn complex human responses into clear, defensible insight by analysing how answers relate to one another across your entire dataset. This means results are not only fast and accurate, but nuanced. Revealing subtle emerging signals, meaningful patterns and risks that other tools - and even humans - typically miss. 

This approach helps our partners surface hidden drivers and early signals of opportunity — from purchase intent to adoption barriers — early enough to act on them. The result is high-trust intelligence built to stand up to scrutiny, giving decision makers confidence they’re seeing the whole picture.

WholeSum

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WholeSum

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