WholeSum, a UK-based qualitative analytics startup, has raised £730k, combining grant funding from Women TechEU with a pre-seed round led by Twin Path Ventures, with participation from SFC and strategic angels via Ventures Together, including founders and operators from JustPark, Episode 1, ClearScore and Prolific.
Most organisational data is unstructured, but teams still lack reliable ways to analyse large volumes of text. Critical nuance and signals remain buried in transcripts, open-ended surveys, online conversations and customer feedback. Organisations instead rely on slow manual coding or brittle LLM summaries that can’t be audited or reproduced.
WholeSum offers a hybrid-AI analytics layer for qualitative data, converting large volumes of free text into statistically robust, auditable insights. Designed to integrate directly via API, the platform outputs quantified, reproducible insight that can be dropped straight into existing analytics workflows. A dataset of 10,000 responses – typically weeks of work for a trained analyst – can be processed in seconds, then passed to a deeper statistical analysis toolkit to inform decision-making.
WholeSum’s work with Imperial College London, Female Founders Rise in collaboration with Barclays, and others is revealing that the most valuable signals are often buried in unstructured audience data rather than in crude tickbox metrics. Until now, though, it has not been feasible to uncover those signals reliably and at scale.
A priority target is high-trust sectors such as research, healthcare and financial services where dependable qualitative evidence is crucial for better decisions and outcomes.
WholeSum outperforms leading reasoning models, including GPT-5 and Gemini 3 Pro. On datasets with clear thematic structure, it can deliver up to 100× faster processing with 100× lower theme attribution error, while ensuring reproducible outputs.
Founded by Emily Kucharski and Dr Adam Kucharski, the company combines deep expertise in commercial and public sector insights as well as statistical inference and machine learning. Adam’s award winning research has informed international health policy (SAGE, WHO) and his open-source tools are used globally; Emily brings extensive experience translating audience data into strategy for major consumer brands at top advertising agencies.
The married pair began developing WholeSum after encountering LLM hallucinations and numerical inconsistencies while analysing thousands of user experiences in a previous venture. The issues revealed a broader market problem: organisations want richer insight from qualitative data but lack tools that are both scalable and scientifically defensible.
The new funding will be used to accelerate product development, expand the science and engineering teams, and scale early enterprise deployments. WholeSum is now opening API pilot partnerships.
