An innovative startup transforming the drug market launch process through generative AI.
1000+ 400-page documents analyzed
95% response accuracy
30s average response time
MaxAI, founded by Virginie Simon (MBA '24J), won the Grand Prize at the 48th INSEAD Venture Competition, along with €25,000 in funding. The startup, based at Station F, aims to reduce costs and facilitate drug market launch by leveraging the potential of generative AI.
Managing and analyzing over 1000 pharmaceutical documents of 400 pages each presented a major challenge. The complexity lay in the need to understand and extract relevant information from dense technical documentation while ensuring absolute accuracy, critical in the pharmaceutical field.
The complex medical terminology required a sophisticated approach, combining technical expertise and professional validation. The system needed to not only understand specialized language but also provide quick and accurate responses.
Our technical solution relies on three essential components:
Technical architecture
AI Model: Gemini for analysis and generation
Database: MongoDB Atlas for vector storage
RAG System: Optimized chunking for medical documents
This architecture enables intelligent document processing and efficient contextualized search, ensuring accurate responses in 30 seconds on average.
The project was completed in one month by a tight team consisting of an AI engineer and a developer, with expert validation from Virginie Simon. The iterative approach allowed continuous refinement of system accuracy through embedding benchmarks and expert validations.
The platform now achieves 95% accuracy in its analyses, enabling a significant reduction in file processing time. The system efficiently processes 400-page documents, extracting and analyzing relevant information automatically.
The solution is deployed on a cloud infrastructure, ensuring scalability and performance. The chosen architecture allows for smooth scaling while maintaining stable response times.
MaxAI continues to innovate in applying AI to the pharmaceutical sector. The success of this first phase paves the way for new developments, with the constant goal of improving and accelerating the drug market launch process.