From NLP to AutoML – what we are working on
When we founded Veracell, we mostly worked on projects in the healthcare and wellbeing domain, before gradually evolving into other business areas. Lately we’ve been active on many fronts covering many aspects of software and business development. Here's a quick summary of what we are working on.
Veracell in Healthcare
So let’s get started with our work in healthcare and wellbeing. Here, Veracell is playing an important role in predictive analytics: We work on discovering the presence of rare diseases through processing (free text) patient journals with the help of Natural Language Processing (NLP). Predictive analytics is also used in hematology to explore the possibility of finding potential matches for drug trials.
Even Finnish, which can definitely be seen as a niche language, is seeing dramatic improvement in NLP-based text understanding due to transfer learning.
And projects that involve NLP deserve a special mention, because they’re growing in importance. Even Finnish, which can definitely be seen as a niche language, is seeing dramatic improvement in NLP-based text understanding due to transfer learning.
For this same client, we also take care of the surrounding infrastructure such as data engineering and integrations, dataops, and service/product design from user studies to data visualization, UI design and development. In addition, we provide the lead design for the product suite.
For a multinational biopharmaceutical company we’re consulting on the creation of a roadmap that will provide a more systematic and streamlined utilization of data, particularly in Real World Data (RWD) projects. These projects are complex as they combine data from many highly regulated sources to quantify the effectiveness of a particular drug while it’s in use. Getting it right will lead to big efficiency gains for both for the company and drug development as a whole.
Then we’re also (co-)developing tools for the healthcare industry. These projects leverage our unique expertise of combining medical data and AI. The work includes roadmaps, development, and data engineering for Enterprise Resource Planning (ERP) and the use of AI for a real-time remote sensing and alerting system.
Work beyond healthcare
The first non-healthcare case on our list is an interesting one as the company is looking to utilize AI to further improve on hypothesis-driven concept testing. Right now, we’re working on establishing the future roadmap for their market research automation tool.
Then it gets real technical as we’re working on AutoML framework development for the next generation of grid computing. For this high performance computing (HPC) solution, we collaborate on product UI design, co-creation, and branding.
Whenever AI moves something physical it becomes 10x cooler.
The final project is one that we’re super-excited about as it involves autonomous vehicles, and whenever AI moves something physical it becomes 10x cooler. Hopefully, we can do a case about this later but for now we can only share that we’re working on data integration, automated machine learning (ML) development, deployment and monitoring, and MLOps.
Why all these companies are working with us
In the end, many of these data-related projects are groundbreaking and require both research capabilities and practical experience.
We tried to find a way to make this sound less boastful, but we also pride ourselves on being transparent and truthful. In the end, many of these data-related projects are groundbreaking and require both research capabilities and practical experience. To complete these projects successfully you need to work with people who understand the business as well as the code infrastructure that makes it work. And to top it off, you need a player that’s willing to be transparent and share these often massive projects.
Do you want to find out how to harness data to grow your business? If so, we would love to have a chat.
Veracell was founded to help companies create value from their vast pool of data. Our forte is to straighten out tangled data and solve challenging problems with the help of strategically planned artificial intelligence.