Lab Workflows Reimagined: Automation for AI-Driven R&D

As AI becomes an increasingly foundational tool in life sciences R&D and lab workflows, the pressure to produce clean, high-quality and context-rich scientific data has never been higher. AI models are only as effective as the data they’re trained on, yet many labs today still grapple with fragmented instrumentation, manual workflows, disconnected analysis tools and inconsistent metadata capture. These challenges not only hinder scientific productivity but also significantly limit the reliability and impact of AI/ML applications across the R&D pipeline.

In this webinar, the featured speakers (@nari.kang and ​@nick.floeck) will explore how scientific organizations are addressing these gaps by modernizing and automating their lab and analytics workflows. Attendees will hear how automation can streamline the capture, processing and structuring of experimental data — creating AI-ready data assets that are reliable, reproducible and traceable. The speakers will also examine the role of rich metadata, standardized context and structured workflows in elevating both the scientific and operational rigor of experiments.

Through real-world examples and best practices, this webinar will highlight how integrated automation and analytics platforms are empowering R&D teams to spend less time wrangling data and more time accelerating discoveries.

Whether dealing with high-throughput assays, managing complex instrumentation or preparing for AI initiatives, this session will provide practical steps to align data strategy with scientific ambitions.