WholeSum Secures £730K To Develop Qualitative Data Analysis Platform

The round also saw participation from SFC and strategic angel investors through Ventures Together, including founders and operators from JustPark, Episode 1, ClearScore, and Prolific.

Although a large proportion of organisational data is unstructured, many teams still lack reliable ways to analyse text at scale. Valuable insights are often buried in interview transcripts, open-ended survey responses, online forums and customer feedback, yet analysis typically depends on slow manual work or automated summaries that are hard to validate or replicate.

WholeSum tackles this problem by offering an analytics layer for qualitative data that turns free text responses into statistically robust auditable outputs. Founded by Emily Kucharski and Dr Adam Kucharski the company combines experience in commercial and public sector research with strong expertise in statistical inference and machine learning.

Read Also - Pixel Flow Raises Seed Funding Just Three Months After Launch

Designed for direct API integration, the platform generates quantified, reproducible insights that slot into existing analytics workflows. Work that would normally take weeks of manual analysis can be completed far more quickly and then explored further using statistical methods to support robust decision-making.

Through collaborations with organisations such as Imperial College London and Female Founders Rise in partnership with Barclays, WholeSum has shown that some of the most valuable insights are found in unstructured data rather than simplified survey metrics. Historically, extracting these insights consistently and at scale has been a major challenge.

John Spindler, Partner at Twin Path Ventures, said qualitative analysis has long relied on manual, inconsistent methods. He added that WholeSum offers a more systematic and automated approach, positioning it as a key building block for how qualitative evidence could be generated and trusted in the future.

WholeSum is initially focused on sectors such as research, healthcare, and financial services where reliable qualitative evidence is essential. Internal evaluations show that on certain datasets the platform performs better than several established reasoning models with quicker analysis, fewer errors in theme attribution and consistent, reproducible results.

The company will use the new funding to accelerate product development, grow its science and engineering teams, and scale early enterprise deployments.

About WholeSum

WholeSum enables teams to analyse large volumes of text data with confidence. As organisations rely more on surveys, feedback, and other free-text sources, WholeSum provides statistically robust, auditable analysis at scale, avoiding the trade-off between slow manual work and hard-to-verify automated summaries.