Global Innovators Accelerate Scientific Discovery with AI-Driven Agents
Microsoft Discovery is a new enterprise AI agent platform designed to transform research and development (R&D) across sectors. By orchestrating specialized AI agents with a sophisticated graph-based knowledge engine, researchers and scientists can reason contextually through complex data, simulate experiments, and iterate research plans faster than ever before. Built on Azure High Performance Computing (HPC) and Azure AI Foundry, it emphasizes trust, compliance, and extensibility. Real-world impact is demonstrated by Microsoft researchers rapidly developing a sustainable immersion datacenter coolant, a process that normally takes years, in just 200 hours. GSK aims to accelerate medicinal chemistry, while The Estée Lauder Companies focuses on faster product innovation. The platform integrates partner technology from NVIDIA, Synopsys, and PhysicsX to enable advances in pharma, materials, semiconductor design, and industrial engineering. Strategic alliances with Accenture and Capgemini are helping scale deployments. Microsoft Discovery is positioned as a future-proof system for solving the most challenging R&D problems using AI agents and Microsoft’s secure cloud foundation.
- Organization
- GSK
- Industry
- Pharma
- Location
- United States
- Published
- May 2025
Reported outcomes
200 hours
timeTime & speed
Strategic outcomes
Primary read
Use case focus
Showing 3 of 4
- 1AI research agent
- 2materials simulation
- 3knowledge graph
- R&D processes in science and engineering are slow, complex, and highly iterative.
- Scientific knowledge is distributed, nuanced, and siloed across domains.
- Simulating and validating new materials (such as sustainable datacenter coolants) can take years with traditional methods.
- Connecting data, tools, and knowledge across domains is difficult for research teams lacking deep computational expertise.
- Compliance and trust in AI systems is required for enterprise-scale adoption.
- Microsoft Discovery orchestrates domain-specialized AI agents (e.g., for simulation, literature review) using a graph-based knowledge engine.
- Built on Azure HPC, Azure AI Foundry, and Microsoft Copilot for trusted and compliant infrastructure.
- Researchers can build and define custom agents to fit specific R&D workflows.
- Partnerships extend the platform with NVIDIA (AI/GPUs), Synopsys (semiconductor design), and PhysicsX (physics models).
- Consulting partners Accenture and Capgemini scale adoption and co-innovation.
- Reduced the time to discover a sustainable, non-PFAS datacenter coolant from years to about 200 hours (plus under 4 months for lab prototype synthesis).
- Enabled faster development cycles at GSK for medicinal chemistry and at The Estée Lauder Companies for product innovation.
- Brings capabilities for rapid parallel prediction, testing, and workflow automation to R&D teams.
- Accelerates semiconductor and material science breakthroughs through third-party integrations.
Architecture
Microsoft Discovery is built on Azure HPC and Azure AI Foundry, using a graph-based knowledge engine to orchestrate teams of domain-specific AI agents. Copilot acts as a scientific assistant, overseeing workflow orchestration and integrating customer/partner models and datasets. Extensibility is achieved via modular integration with open-source, partner, and custom solutions, with enterprise governance controls. Integrations with NVIDIA ALCHEMI and BioNeMo NIM, Synopsys, and PhysicsX expand the ecosystem for specialized scientific and engineering domains.
Sources & evidence2
The same organization appears in newer AI deployment evidence.
- Same organization re-documented as recently as 2026.
- Cited source last checked Jun 12, 2026 — ok (0/2 broken).
Measures whether this deployment's public evidence persists — not whether the system is still in production.
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