LeapSpace™ Bring clarity to R&D decisions with AI built on trusted scientific content

AI is increasingly embedded in R&D workflows—but confidence hasn’t kept pace. While 84% of researchers use AI, just 22% feel confident applying it.¹

For AI to support scientific environments effectively, it should be grounded in trusted scientific content, provide transparency in how responses are generated, and be designed to enable human oversight and critical evaluation.

This session shows what that looks like in practice.

We’ll walk through real workflows used in high-stakes R&D environments, showing how teams:

• Move from broad questions to focused insights faster
• Connect evidence across sources without losing context
• Maintain visibility into how conclusions are supported

Built for R&D Requirements
LeapSpace is designed for the rigor and accountability of scientific work:

• Grounded in trusted scientific content
• Transparent, evidence-based outputs
• Designed to support human review and validation

Security & Privacy
Your work stays yours:

• YourPrivate, encrypted environment
• Secure user sessions on enterprise-grade cloud infrastructure
• Your data is never used to train large language models

Agenda

• What research‑grade AI really means for high‑stakes R&D decisions
• How LeapSpace enables evidence‑based R&D decisions
• How responsible AI is built into LeapSpace—transparency, human oversight, and enterprise‑grade privacy & security
  
  1 Confidence in Research: Researcher of the Future Report 2025, Elsevier.