From experiment design to actionable insight, Luma orchestrates the flow of scientific planning, experimentation, and analysis across the connected digital lab, without the manual hand-offs.
After the experiment runs, the outputs land in files. But the files don't carry the question that shaped the experiment, the protocol decisions, or its relationship to everything that came before. That thread breaks every time data crosses a system boundary, and the friction compounds as labs scale.
AI can summarize what's in front of it. What it can't do is guide a research program without knowing where it's been, what was tried, what was learned, why this experiment was designed the way it was.
The vision most labs have for AI, intelligent guidance on next steps, closed-loop experimentation, analysis that spans entire research programs, depends entirely on data that's grounded in its scientific context. Orchestration is how you build that foundation.
True lab orchestration operates across three domains at once, and the weakest link in most labs today is the connection between the physical and the digital.
Most labs have the first. Luma closes the gap between all three.
Most labs generate more data than they can use, and most of it loses context the moment an experiment ends. This guide walks through the three layers every connected lab needs, how to spot where your own lab sits on the maturity curve, and a practical, staged path toward orchestration.
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A global pharmaceutical company set out to orchestrate data from more than 5,000 standalone instruments across its research and development labs. Here's how the rollout unfolded, based on our conversation with their orchestration lead.
Thousands of standalone instruments across discovery, research, and development, each one isolated. Results and metadata landed in local storage, vendor-specific CDS systems, and scattered directories, siloed, fragmented, and effectively trapped.
The team started with their LCMS fleet, roughly 1,000 instruments across five manufacturer types including Waters, Agilent, Thermo, and SCIEX, plus vendor-specific CDS systems like Empower, Agilent OpenLab, and Thermo Chromeleon.
Multimode readers, liquid handlers, and flow cytometers came online alongside the LCMS fleet, proving out a phased, instrument-agnostic path to onboarding across different labs and business areas.
Harmonized data now feeds Luma Agent and flows out to systems like ELNs and LIMS, surfacing purity trends, instrument utilization, and service history to guide smarter capital and purchasing decisions, on a clear path toward every instrument on campus.