Health & Life Science use cases are plenty with Gen AI and agents and you have heard them all. You have co-pilots, state of the art LLMs, domain specific agents, vector databases and you have built a RAG based chatbot- do you need more?
Whats missing?
It’s not the lack of LLMs. It’s the leap from promising demos to production-ready systems—especially when the data is unstructured and multi-modal, the use case is critical and highly regulated. Customers seek to optimize, precision, cost and performance and there is no one size fits all solution to do this.
Join us for a candid panel with life sciences and healthcare leaders & tech leaders who’ve built—and scaled—AI applications in the field. We bring together the diverse panel to exchange and educate across both technology and business practitioners.
Not only will you learn the challenges from the field, but also new concepts that matter for AI like ranking, search and tensors. You’ll also hear how other industries—like e-commerce and companies like Yahoo and Perplexity—are solving similar challenges at scale with speed and precision. This is not a product pitch—it’s a learning opportunity for anyone serious about building GenAI that lasts for a complex vertical like Healthcare and lifesciences. This panel will seek to dive into:
- Real-world use cases across pharma, biotech, providers, and health tech—and why precision and relevance matter?
- The rise of health techs: what key differentiators they may be overlooking in their rush to build cohort builders?
- Cross-industry insights: what health & lifesciences can learn from how tech giants build scalable AI systems?
- The future of modeling: why concepts like tensors and vision-language models (VLMs) matter for unlocking value in scientific data across discovery, commercial and hospital care.