The quality of product development is of strategic importance for many companies because problems can lead to delays, costly recalls or even personal injury. Increasing complexity and stricter compliance requirements are exacerbating the situation. Traditional approaches are reaching their limits and jeopardizing economic success. What to do?
The use of AI solutions in product development is already showing promising results. And one or the other reader has certainly followed my activities in the field of AI. I have been working on a virtual quality assistant under the name Semiant for about a year. I have been following the activities of the Qualicen company for a while. Now we have decided to continue on this path together.
Under the name Holmes , Qualicen is working on a platform that uses artificial intelligence to relieve teams in product development. Holmes also uses Natural Language Processing (NLP) to process human-written content. What both solutions have in common is that they can be used to automate many important but monotonous and error-prone tasks for which employees are often overqualified. For product development, this means more efficient work, fewer risks and a lot of time saved.
For Semiant customers and those of Qualicen, not much will change at first. Together, however, we can act faster with the enlarged team. In the medium term, we want to develop a product with Holmes that can be used immediately without much adjustment and delivers measurable results. Which use cases we’ll tackle first isn’t clear yet, but we have a lot of ideas.
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