Ninety days to implementation vs. 12 to 18 months with traditional systems: That’s not just an incremental improvement—it’s a complete reimagining of what’s possible in life sciences quality management.

AI has amazing capabilities, and it’s one of the best technologies for the future. It’s helping to change the world and bringing productivity enhancements across industries with its exceptional use cases. Quality assurance isn’t left out, either.

Many organizations have decided to automate their quality management system (QMS) or upgrade their currently automated QMS.

The case for in-office work has never been stronger. This may seem surprising, given that many businesses have operated remotely or in hybrid models for more than five years.

When an issue arises, it’s important to take quick action. Whether that means launching a software patch, pulling a batch, or halting the use of a reagent, it’s critical to tackle the immediate problem.

My first day as a consultant coincided with the annual women’s summit, and so the other female new hires and I were invited to join the event.

Many organizations list continuous improvement (CI) as a priority, but it often fails to take root in day-to-day work. It appears as a workshop or a one-off initiative, then fades without lasting change.

You’ve probably had the experience of visiting a contemporary factory floor and being amazed by all the incredible robots, sensors, and machines working like a finely choreographed dance. It’s quite remarkable—until there’s a malfunction.

Sharon, a corporate HR leader, spends her days managing her team and helping shape a culture that supports innovation and creative thinking. But when fall rolls around, her evenings are spent with foam wreath forms, mesh ribbon, and a glue gun.

Capturing real-time data in all areas of the business is vital for maintaining long-term success. When manufacturers conduct business with separate systems, data end up in silos, and information can’t flow in an efficient manner.