Clear.bio, a Netherlands-based health-tech startup that offers a 12-week digital nutritional intervention to help people reverse Type 2 Diabetes, boosted its high-value healthcare partner conversion rate by 30 percent after automating the manual process its sales team used to identify and target clinical partners with Google AI.
"The collaborative effort, involving engineering, product, scientific, marketing, and partner management teams, transformed a manual process into an automated, AI-powered system that streamlines how we find and prioritize the right practices. It saves our team time, reduces guesswork, and helps us reach out to the most promising practices more efficiently," said Parul Vats, CTO of Clear.bio.
Clear.bio founded in 2019 grew across the Netherlands and expanded into Germany and France, at which point its core challenge shifted from product validation to distribution. Sales staff had to manually research thousands of healthcare practices, assessing technology adoption, patient demographics, and treatment patterns to figure out which general practices and healthcare organizations were most likely to refer patients to its program. That manual workflow was time-consuming and could not scale with geographic expansion, slowing growth.
To replace it, Clear.bio ran an AI Sprint with Google for Startups. The company used Gemini to analyze practice profiles and assess factors such as technology adoption, patient demographics, and treatment patterns, then trained and deployed an AutoML machine learning model on the Gemini Enterprise Agent Platform to produce a 'Best_Class' predictive score for each potential practice. BigQuery served as the data warehouse, loading, extracting, and preprocessing the data used to train the model, while Google Cloud Functions automated the pipeline, triggering the scoring process whenever new CSV files were uploaded and managing the end-to-end data flow.
Within the first few months of deployment, Clear.bio achieved a 30 percent increase in the conversion rate of high-value healthcare groups interested in partnerships. The added precision let the sales team concentrate on the top 20 percent of practices most likely to generate referrals, cutting outreach time by roughly 20 percent and enabling more efficient expansion in the Netherlands and internationally. The predictive model proved highly reliable, delivering 92-94 percent prediction accuracy.
Beyond business operations, the same AI infrastructure supports the startup's clinical mission: Clear.bio uses AI to translate continuous glucose data into personalized nutritional insights, and 69 percent of patients in its program saw a clinically meaningful drop in HbA1c. "Using the AI tool enables me to deliver highly personalised and relevant information to potential new clients. This consistently boosts engagement and significantly increases my chances of closing new contracts," said Gijs van der Spek, Account Manager, Regional Healthcare Organisations.
Clear.bio plans to keep scaling by extending the successful predictive model to more teams, attracting new clients, and expanding into additional countries. "Our main plans are to scale the successful predictive model to more teams, get more clients, and expand to new countries," said Madelon Bracke, Co-founder and Head of Bioscience at Clear.bio. The company said the model has already shown strong results over its first six months and is helping it pursue its mission of helping millions reverse Type 2 Diabetes through personalized nutrition.