How Clear.bio Uses Gemini to Boost Partner Conversion by 30%

Clear.bio entered the European digital health market with a clinically validated program that uses continuous glucose monitoring data to help patients reverse Type 2 Diabetes without medication. As the company expanded from the Netherlands into Germany and France, the core business challenge shifted from product validation to distribution: how to efficiently identify and prioritize the general practices and healthcare organizations most likely to refer patients and adopt the program.

The manual approach to partner identification was a significant bottleneck. Sales staff had to individually research thousands of healthcare practices, assessing their technology adoption patterns, patient demographics, and treatment philosophies—a process that was time-consuming, inconsistent, and unable to scale alongside geographic expansion. Without a systematic way to rank prospects, the team spent equal time on low-probability and high-probability targets.

Through a Google for Startups AI Sprint program, Clear.bio cross-functional teams of engineers, product managers, scientists, and marketers designed an automated pipeline. Google Gemini analyzed healthcare practice profiles across multiple dimensions, while BigQuery served as the data warehouse for loading and preprocessing the training data. The Gemini Enterprise Agent Platform was used to train and deploy the AutoML predictive scoring model, and Cloud Run functions automated the end-to-end pipeline, triggering on new data uploads without manual intervention.

The system now assigns each practice a Best_Class score based on Gemini analysis, achieving 92–94% prediction accuracy. Sales representatives can focus their outreach on the top 20% of practices identified by the model, resulting in a 30% lift in high-value partner conversion and approximately 20% reduction in outreach time. The AI-generated insights also allow account managers to deliver highly personalized information in initial outreach, increasing engagement and contract close rates.

Beyond the partner acquisition workflow, the success of the Gemini-powered model has accelerated Clear.bio broader AI strategy. The company plans to scale the predictive model across additional teams and new geographies, using the proven six-month track record as the foundation for ongoing expansion. The same data infrastructure underpins Clear.bio patient-facing product, where personalized glucose response data guides individual nutritional recommendations—demonstrating how a unified AI platform can simultaneously optimize business operations and clinical outcomes.