We're excited to share that Wholesum has closed an additional round of pre-seed funding, bringing our total raised to $1.3 million. The round adds new investment from Love Ventures, Beamline, and strategic angels, building on our initial $965k raise led by Twin Path Ventures earlier this year.
Why now
Enterprises in high-trust sectors are hitting a wall with AI. Most organisational data is unstructured text, and teams know there's valuable signal buried in it. But when they turn to large language models to analyse it at scale, they run into hallucinations, inconsistent outputs, and results they can't reproduce or defend. That's a serious problem in regulated environments like healthcare, financial services, and defence, where every insight needs to hold up to scrutiny.
We built Wholesum to close that gap. Our platform combines AI with statistical inference to turn free-text data into insight that's uncertainty-aware, reproducible, and auditable. It's designed as an API-first infrastructure layer, so it drops into existing analytics workflows and lets teams extract nuanced signals and underlying drivers from text with the same rigour they'd expect from numerical data.
What we've learned so far
Since our first raise, we've worked with universities, financial institutions, and pharmaceutical companies. A consistent pattern has emerged: the most valuable early signals often live in unstructured text, not in lagged quantitative metrics. Organisations that can reliably tap into that text get a real head start.
This new funding goes toward R&D, growing our scientific and engineering teams, and scaling enterprise deployments in the sectors where methodological rigour matters most.
Where it started
Wholesum was founded by Emily Kucharski and Dr Adam Kucharski. Adam's award-winning statistical research has informed national and international health policy; Emily has led audience insight and strategy work for global brands. The idea for Wholesum came out of our own frustration with existing AI tools while analysing large-scale qualitative datasets in a previous venture. That experience made one thing clear: organisations want to extract meaningful insight from qualitative data, but they lack tools that are both scalable and scientifically defensible.
“From talking to dozens of large organisations making high-stakes decisions, we've seen a clear pattern: teams are experimenting with AI for text analysis, but quickly hit a wall when outputs can't be trusted or reproduced,” said Emily Kucharski, Cofounder & CEO of Wholesum. “This funding allows us to move faster in building infrastructure for robust analysis at scale.”
“Generic LLMs can't deliver the consistent, reliable signals that high-trust industries need from unstructured data,” said Bill Corfield, Principal at Love Ventures. “Emily and Adam are uniquely positioned to solve this, and we're delighted to be backing them as they scale across Pharmaceuticals, Financial Services and beyond.”
“Glad to join Wholesum's round — a strong example of deep analytics that can outperform big generic models when trust, accuracy, and explainability are non-negotiable,” added Jana Budkovskaja, Investment Partner at Beamline.
What's next
We're now rolling out pilots and enterprise integrations for increasingly complex, large-scale datasets. If you're working with unstructured text data in a high-trust sector and want to see what rigorous, reproducible analysis looks like, get in touch.