AI in Healthcare
Integrating artificial intelligence into healthcare organizations, from strategy to operational deployment.
AI projects delivered
innovation projects overall
Who is it for? Pharmaceutical companies, medtechs and health institutions that want to move from AI experiments to concrete, compliant and adopted deployments.
The Challenge
AI is transforming the pharmaceutical value chain — from R&D to market access. It accelerates therapeutic target identification, optimizes clinical trial recruitment, enriches health-economic models, and opens new channels in the relationship with healthcare professionals. Yet the majority of AI projects in healthcare never reach production: data quality issues, organizational resistance, and regulatory requirements that were not anticipated early enough.
Organizations that fail to integrate these technologies — or do so without a structured approach — risk falling irreversibly behind competitors who are already industrializing their AI capabilities.
Our Approach
We combine deep domain expertise with mastery of AI technologies to move from strategy to operational deployment. Our method is built around three phases:
Diagnosis and scoping. We assess the organization's data maturity, identify high-impact use cases (enhanced pharmacovigilance, prescriber targeting, real-world evidence generation) and define a realistic roadmap that is compliant with regulatory requirements and data protection obligations.
Prototyping and validation. We work in short cycles with business teams to build proof-of-concepts, test models on real data, and evaluate acceptance by end users — physicians, MSL teams, market access managers.
Deployment and adoption. We support scaling: technical architecture, change management, team training, and performance monitoring. The goal is not to deliver a tool, but to build lasting internal capability.
Our Results
Across more than 40 AI projects, successful deployments consistently share three traits: strong business sponsorship, data that is structured from the outset, and clear AI governance. These projects are part of a broader portfolio of 150+ innovation initiatives delivered across the healthcare ecosystem.
Our clients — pharmaceutical companies, medtechs, and institutions — are now using AI to concretely improve patient care, with an estimated impact across more than 80,000 patients reached by the solutions deployed.
Frequently asked questions
When should you start an AI project in healthcare?
As soon as you've identified a friction point or an optimisation lever in your pathways, processes or data. The French government published a 2025 review of AI in healthcare: the question is no longer when, but how. We help identify pilot projects.
Do you need in-house AI skills?
Not necessarily. We bring expert resources at the right moment while upskilling your teams on AI in healthcare.
How long does an AI project typically take?
Depending on scope, between 3 and 12 months for structured scoping and experimentation.
