Sciar wants to bring better documentation to the laboratories through modern tech tools

In laboratories around the world, there is the same problem: as research is being conducted, the documentation of the research findings is frequently compromised in some manner. Science requires accurate, detailed information – but extracting that raw data from the labs is surprisingly difficult.

Kristian Alaviuhkola, Co-Founder of Sciar Company Ltd, says that the challenge here has to do with old-school tools: relying on paper and pen, for instance, to get the results down and onwards to a database.

“With digitalization, you can build processes which bring automatic documentation tools to the laboratory environment,” he says.

Sciar has created a Quality Management software which utilizes automated documentation, as well as an Augmented Reality workflow tool, to rectify the problem.

“Once the data is correct, you’re able to repeat the same experiment and get the same results – which is not always the case today.”

As errors are recognized and minimized, repeatability improves – thus boosting the quality of the research itself. “Our goal is to enhance the quality of the researcher’s work as well as the quality of the data.”

Our goal is to enhance the quality of the researcher’s work as well as the quality of the data.

Plan & execute

The Sciar product is two-fold: there is the Sciar cloud-based software and then the Sciar mobile application.

“The software plans the processes in the lab beforehand and manages them. The software is both interactive and intuitive in providing the lab worker with instructions on what to do from a documentation viewpoint.”

The Sciar app completes the picture, making sure the lab worker moves from one work phase to another one in a correct manner. The app is presently being developed and it’s coming soon to Android smart phones and pads.

“Right now, we’re still using AR glasses to achieve the same documentation effect, but we’re expecting the mobile app to be even more helpful for our customers.”

According to Alaviuhkola, as long as you automate the workflow and dataflow, the emerging information will be solid through-and-through. “When you report the findings correctly in each case, that makes the scientists’ lives so much easier.”