Wholesum

DISCOVER NEW SIGNALS
FOR BETTER OUTCOMES

Use untapped text data to continually uncover the drivers that matter
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Barclays
Cambridge University
Imperia
Maternal Mental Health Alliance
Link Consumer

How data science, insights and strategy leaders use Wholesum

1

Earlier intelligence from operational data

The problem

Emerging threats and opportunities show up in text data like field team notes, internal feedback and call transcripts long before lagged quantitative metrics, organisations struggle to interpret narrative data consistently at scale.

Our solution

Wholesum spots emerging issues early, before they affect outcomes.

Who we deliver this for

Pharma Customer Engagement, Retail Data Science, Global People Insights

2

Improve the predictive power of models

The problem

Organisations focused on understanding audience intent and behaviour are still largely dependent on quanitative and structured data.

Our solution

Wholesum turns text into new signals and feeds into existing systems.

Who we deliver this for

AdTech and Media Platforms

3

Track geopolitical and market shifts

The problem

In high-stakes industries, narrative data sources hold valuable signals for decision-making. But these are hard to interpret carefully at scale, meaning teams fall back on ad-hoc human interpretation.

Our solution

Wholesum analyses external text at scale and triangulates with internal data.

Who we deliver this for

National Security, Investment Management, Private Equity

A new kind of analysis engine

Traditional classification tools are fine-tuned to a narrow, static range of topics or sentiment.

Modern large language model performance is inconsistent and difficult to operationalise reliably across large, evolving datasets.

Wholesum is different. We use comparative statistical inference across entire datasets, which solves dozens of common failure modes in AI and human interpretation, making large-scale analysis stable and repeatable.

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Why are enterprise teams choosing Wholesum?

Full contextual analysis

Analyses every entry comparatively in the context of the wider dataset, removing anchoring and interpretation bias.

Stable signal detection

Discovers both widespread and niche patterns — and quantifies how strong, how prevalent, and how certain each signal is.

Reproducible outputs

Consistent, reproducible outputs across analysis runs, stable across time periods, and traceable to its source data.

Built for scale

Scale from thousands to millions of entries while maintaining stable, reproducible analysis.

Meet the founders

Wholesum was built to bring statistical rigour to narrative text data at scale.

Our founders have experience across audience insights and behavioural research, along with world-leading expertise in data science and statistical inference.

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.

About us

Turn text data into defensible intelligence

Book a 30-minute call to discuss how Wholesum can help your team extract reproducible, auditable insights from unstructured text at enterprise scale.

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Wholesum — Turn complex text into reliable signals at scale