About us
Our mission is to help teams build a deeper, continually improving understanding of what drives the outcomes that matter. We believe organisations should be able to learn from all the evidence available, not just what is easiest to analyse.
Wholesum uses comparative statistical inference across entire datasets to identify stable signals, then applies tailored causal frameworks to understand which drivers matter and where the weight of evidence lies. That means signals that are easy to miss — in large internal datasets, or spread across many external sources — are surfaced and put in context.
This helps our partners identify levers for change early enough to act on them — from employee and customer outcomes to emerging shifts in markets and geopolitics. The result is understanding that compounds with each cycle, built to stand up to scrutiny.
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Meet the team
Emily Kucharski
Cofounder and CEOEmily understands the commercial importance of audience insights. She held senior roles at global marketing agencies and worked with major brands across a variety of sectors (healthcare, financial services, FMCG). She's also built two data-driven parenting apps that attracted thousands of users.
In 2025 she won a competitive deep tech grant - Women TechEU - to help bring her vision for Wholesum to life.
Dr. Adam Kucharski
Cofounder and CTOAdam's academic research has been used to advise governments and design widely used open-source software. He's in the top 0.1% of cited researchers worldwide for his work on generative modelling, statistical inference and machine learning.
He's previously led data and research projects with top organisations, including BBC, SpaceX and Meta. As an award winning science writer and bestselling author, he's also passionate about communication of data-driven insights.
Guy Torbet
Founding EngineerGuy has developed large-scale infrastructure used by millions, with a focus on performance, reliability and clean implementation.
He began his career at HackerNoon, leading full-stack migrations and most recently led backend and systems development at Malted AI. He has a first-class degree in AI & Computer Science from the University of Edinburgh and won the SkyScanner Award for systems design.
Dr. Joel Hellewell
Applied ScientistAn expert in making sense of complex, messy data in high-stakes environments, Joel has identified markers of antibiotic resistance in huge datasets of bacterial genomes at the European Bioinformatics Institute; found signals of what medical interventions work in the chaotic humanitarian environments that Médecins sans Frontières operate in; and his research fed directly into UK government scientific advice during COVID-19.
He did his PhD in mathematical and statistical modelling at Imperial College London.
Steve Ortiz
Software EngineerSteve brings extensive experience architecting software that turns complex data into something people can act on across fintech, R&D, energy and travel tech sectors. He has designed and built everything from data-analytics platforms to portfolio investment systems and public-facing applications.
He has a degree in Software Engineering from the Technical University of Madrid.
Our expertise
Our founders bring more than 20 years' combined experience across audience insights and behavioural research, with world-leading expertise in statistical and causal inference and complex systems.
Statistical Inference
Advanced statistical modeling and inference techniques for reliable data analysis.
Machine Learning
Cutting-edge machine learning and language modeling approaches for nuanced text interpretation.
Commercial Insights
Deep understanding of audience behaviour and enterprise insight needs.
Our story
Wholesum’s founders encountered the same problem from very different worlds — corporate and academic. Emily and Adam both saw the limits of quantitative data when it came to understanding the ’why’ behind human behaviour, and they felt the frustration of trying to extract reliable understanding from narrative evidence at scale.
"We saw organisations struggling with the same challenge over and over: rich evidence about what was really driving outcomes, sitting unused because analysis was too slow, unreliable, or expensive."
Emily, CEO
This challenge shows up everywhere. In how companies listen to customers, patients and employees; in how analysts assess markets; and in how governments and researchers seek to understand behaviour.
What we’re building with Wholesum is a foundational capability. And the urgency has never been greater. AI adoption is accelerating, the demand for deeper insight continues to grow, yet many teams are frustrated by shallow, error-prone tools. Even the most advanced models struggle to build a consistent, reliable picture of what is happening and why across large, evolving evidence.
Imagine if the strengths of quantitative data — trust, transparency and reproducibility — could be applied to all the evidence available, and extended to understanding cause and effect. That’s the transformation we’re working toward: decision-making that captures nuance, weighs the evidence, and compounds with every cycle.