MadeAi Wins 2026 Fierce AI Innovation Award for Medical Affairs

MadeAi, an artificial intelligence (AI)-enabled evidence synthesis provider for the life sciences industry, has been named the winner of the 2026 Fierce AI Innovation Award for AI Innovation in Medical Affairs. The award recognizes MadeAi for its innovative approach to accelerating literature review and evidence synthesis while maintaining the transparency, scientific rigor, and traceability required for regulated life sciences workflows.

According to Gaugarin Oliver, the Founder and CEO of MadeAi, the company’s platform combines generative AI, large language models, natural language processing, retrieval-augmented generation, agentic AI workflows, and human validation across the evidence synthesis process. The platform is designed to maintain source traceability and expert review while automating labor-intensive activities such as protocol development, screening, data extraction, synthesis, summarization, and reporting.

MadeAi’s platform supports pharmaceutical, biotechnology, medical device, and contract research organization (CRO) organizations in transforming complex scientific information into trusted, evidence-based outputs. By combining AI automation with human oversight, the company helps Medical Affairs, health economics and outcomes research (HEOR), market access, and real-world evidence (RWE) teams accelerate evidence workflows while supporting scientific confidence and audit readiness.

The recognition follows Fierce’s assessment of MadeAi as an AI-enabled, human-in-charge platform that helps automate labor-intensive literature review workflows while maintaining the scientific rigor required in life sciences. The award highlights MadeAi’s commitment to innovation and its ability to address the challenges faced by medical affairs teams in the fast-paced and data-rich environment of the life sciences industry.

MadeAi’s platform is designed to support systematic literature reviews, Good Veterinary Practice (GVP) and Joint Clinical Research (JCAR) submissions, and evidence generation workflows across various life sciences organizations. From protocol development to publication-ready deliverables, the platform combines artificial intelligence with human oversight to help research teams achieve faster turnaround times and scalable evidence generation.