Labs of the Future: How to Choose a LIMS
A practical buyer's guide to evaluating laboratory information management systems, what a modern LIMS should do, what to ask vendors, and how AI is changing the lab
Most companies spend millions on R&D labs and equipment, but treat the data those labs produce as an afterthought. Experiment results end up scattered across spreadsheets, shared drives, and one scientist's memory; and when that scientist leaves, so does the knowledge.
This guide walks you through what a laboratory information management system (LIMS) actually is, what separates a modern platform from a legacy one, and the questions to ask any vendor before you sign a contract.
What's inside
- What a LIMS is, and why the old definition of "task and data tracker" doesn't cut it anymore
- The shift from outdated, manual R&D tools to a connected digital lab
- Six questions to ask every LIMS vendor before you buy
- How AI and machine learning are changing what "modern" LIMS means
- What it actually takes to implement a new LIMS and get your team to adopt it
Why your lab's data deserves the same investment as your lab's equipment
Materials breakthroughs, from 3D-printed medical devices to renewable bioplastics, are happening faster than ever, and researchers are expected to innovate at the same pace. That speed is in direct conflict with how most labs still collect and share data: locked in disconnected spreadsheets, siloed by team, rarely reused for the next experiment.
A laboratory information management system is software that helps you collect, organize, and share data from lab experiments, giving every scientist visibility and accountability at each step of the testing process, and giving the company a record that outlasts any one person's tenure.
The rise of AI-enabled LIMS
The best modern platforms don't just replace your spreadsheets; they combine the core functionality of a LIMS and an electronic lab notebook (ELN) with machine learning that gets smarter with every experiment you run. That means faster search, tailored predictions, and models that improve as your team generates more data, all in one system, instead of stitched together across several.
Proof it works
"With the Uncountable platform, analysis and reporting that used to take hours or days now takes minutes." Mike Recchio, President and CEO, Zeon Chemicals LP
R&D and materials teams at companies including Clariant, Repsol, Mitra Chem, and SCG Chemicals run on Uncountable's LIMS platform, with SCG Chemicals reporting a 10–20% acceleration in R&D cycle time.
Ready to future-proof your lab?
Download the full guide to get the complete framework for choosing a LIMS, including the six vendor questions, the shift to AI-enabled platforms, and what successful implementation looks like in practice.
FAQs
Traditional LIMS were built mainly to track lab tasks and samples. Modern LIMS platforms also capture what happens earlier in the process, support advanced statistical analysis, and increasingly build in AI to turn past experiments into predictions for future ones.
At minimum: how the system handles real-time and historical search, whether you can customize attributes and workflows, how permissions and data-sharing work, what time savings to expect, and what support looks like after you sign.
No. While regulated industries (pharma, chemicals) rely on LIMS for compliance and auditability, any R&D team producing experimental data, materials science, consumer products, industrial chemicals, benefits from a structured, searchable system of record.
No. The AI and machine learning capabilities in a modern LIMS are built into the platform itself, so scientists get predictions and insights without needing to build or maintain their own models.
See the Platform Behind the Guide
