Our Target audience involves 1. Industrial Innovation Labs 2 Academic Institutions with research groups and finally 3. large scale consortia labs which involves the collaborations between geographically distributes partners.
When a scientist leaves a lab, even though she leaves all her notebooks, her harddrives, all the data she ever collected a know-how gets loss.
In scientific labs, scientists make experiments and measurements and collect a lot of data. But this data comes in all sizes and formats. This variation in data causes a lot of inefficiencies.
DigitalLabBook -is a cloud based data sharing platform for scientist to be able to collect , store data and knowledge transfer securely.
This platform will enable standardized data collection with the generation of database collaboration between distributed constortia of partners or within a lab. This allows the facilitation to share data and use of data efficiently
Comes from different sources and electron microscope or a wet chemistry experiment in different formats. Sometimes scientists log this in their paper notebooks, sometimes there is an Excel Table (manual entry) or the instrument has specific software that dumps the data into a CSV file or they store the images (Gigs of data) on the hard-drive.
We know that we need to understand the scientists and wear their shoes to be able to develop an engaging platform. So we have a Materials Science team. In our team we have multiple scientists who are academicians. We work with them and their labs to build templates. We have our Operations team for building this software and data platform. We also know that the core reason dor data inefficiency is relying under CX and UX so we have a team working on engagement as well.
The market size of Scientific Research and Innovation is huge. Only in the US, in 2020, $171 Bn were spent for research! After the pandemic, in 2021 we know that this number will at least double.
We have been conducting Design Sessions in Labs and interviewing scientists on how they collect data, how they store, share. We know that there are many steps missing/not recorded so we are aiming to collect those steps in between processes. We are currently working on our MVP. We have two clients (one academic and one industrial Lab) that we work with.
We have three main expertise that we focus on. Materials Science, Database Architecture and CX/UX.
We believe we are following a blue ocean strategy and developing a new market. There are existing point solutions in the market. They vary in abilities, purposes and cost.
We believe that what makes us special is that: we have found a gap in the market and we believe that we can only fill this gap by wearing a scientist’s shoes. We are better because we are developing our product with real labs and our target customers. This will allow huge improvements in data standardization and collection which will yield to great success.