UK-based qualitative analytics startup WholeSum has raised £730,000, combining grant funding from Women TechEU with a pre-seed round led by Twin Path Ventures. The round also included participation from SFC and strategic angel investors via Ventures Together, including founders and operators from JustPark, Episode 1, ClearScore, and Prolific.
A significant share of organisational data is unstructured, yet many teams lack consistent methods for analysing large volumes of text. Key information is often found in transcripts, open-ended survey responses, online discussions, and customer feedback, while analysis frequently relies on time-intensive manual processes or automated summaries that are difficult to verify or reproduce.
WholeSum provides an AI-based analytics layer for qualitative data, converting large amounts of free text into statistically supported, auditable outputs. Founded by Emily Kucharski and Dr Adam Kucharski, the company combines experience in commercial and public sector insights with expertise in statistical inference and machine learning.
The platform is designed for direct API integration and produces quantified, reproducible insights that can be incorporated into existing analytics workflows. Tasks that would typically take weeks of manual analysis can be completed more quickly and then examined further using statistical tools to support decision-making.
Through collaborations with organisations including Imperial College London and Female Founders Rise in partnership with Barclays, WholeSum has found that high-value insights are often contained within unstructured data rather than simplified survey metrics. However, identifying these insights consistently and at scale has historically been difficult.
John Spindler, Partner at Twin Path Ventures, said that qualitative analysis has long depended on manual processes and inconsistent approaches. He noted that WholeSum introduces a more systematic and automated framework and described the platform as an important foundation for how qualitative evidence may be produced and relied upon in the future.
The platform is primarily aimed at sectors such as research, healthcare, and financial services, where reliable qualitative evidence plays an important role in decision-making and outcomes. According to internal evaluations, WholeSum demonstrates improved performance compared with several established reasoning models on certain datasets, offering faster processing and lower theme attribution error while maintaining reproducible results.
The company plans to use the new funding to advance product development, expand its science and engineering teams, and scale early enterprise deployments.
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