We're very happy to share the news that we've closed a £730k pre-seed round, with Twin Path Ventures as lead investor. Beyond capital, they've already given us key GTM insights, deep AI expertise, and a brilliant network of founders building ambitious tech.
The problem
80-90% of organisational data is unstructured: this includes audience data like transcripts, surveys, feedback, and conversations. Yet teams still lack reliable ways to analyse it at scale.
Manual coding is slow and expensive. LLM summaries are brittle, non-auditable, and non-reproducible. The valuable signals needed to shape decisions stay buried.
WholeSum's solution
WholeSum is a hybrid-AI analysis layer for complex text data. We turn large volumes of free text into statistically robust, auditable, reproducible insights—designed to slot straight into existing analytics workflows.
What takes weeks of manual processing can be processed in seconds, then pushed into deeper statistical analysis for real decision-making.
Our work with Imperial College London, Female Founders Rise (with Barclays), and others shows the richest insights often sit in unstructured data, not in tick boxes. Until now, extracting these signals reliably just hasn't been feasible.
We're initially focused on high-trust sectors like research, healthcare and financial services, where evidence that can be scrutinised and built upon really matters.
The opportunity
At its core, this is about unlocking human experience. For too long, this has been trapped in messy text, flattened summaries, or soul-destroying 'somewhat agree/somewhat disagree' scales.
Curious?
We're rolling out 4-week proof-of-concepts with organisations who want to give their valuable qual data the analysis it deserves. Our API launches next month.