5 reasons why you should rely on ready-made AI solutions
In a world dominated by technology and automation, artificial intelligence (AI) has become an indispensable part of everyday business. Businesses of all sizes and in all industries are realising the benefits of using it to speed up processes, reduce costs and make better decisions. In this short article, we explore 5 reasons why it makes sense to rely on existing AI solutions rather than focusing on developing your own.
In the meantime, there are numerous providers of tools on the market that solve sub-areas or specific tasks – but often not your individual problem, so you should focus on the combination of the right, “perfect” tools for you. Do not limit your research & development team to internal solutions or own developments.
5 reasons for ready-made AI solutions
- Time saving:
With solutions already available, you can save time by not having to research, test and develop yourself.
In most cases, ready-made solutions have already been tested, optimised and established. This guarantees higher efficiency, better performance and an individual solution – tailored to your problem.
- Cost saving:
In many cases, it can be more expensive to solve a problem yourself, especially if you need specialised knowledge or resources. At the beginning of a development, one is often busy for a long time solving bugs that have often already been solved by providers.
- Specialised skills:
Some problems require specialised knowledge or skills that not everyone has. In these cases, it makes sense to use solutions that are already available, rather than committing expertise in the form of staff for the long term, as it is often only needed initially.
With self-developed solutions, there is a risk that errors will occur that require time and resources to fix. In addition, such software projects also tie up internal capacity for maintenance and operation, which should not be underestimated.
In general, it is important to make a balanced decision based on the specific needs and requirements of the problem, as well as the available resources and skills.
We also say openly and honestly that semantha is not “the solution” for everything. Combined with other software solutions such as UiPath, Snowflake, Streamlit or Google Colab-Notebook, however, value-adding tools can be created very quickly that suddenly become an individual solution for you and your company.
In one of our next blog articles you will learn how you can build a document analysis app in just a few minutes with very few lines of code and our semantha SDK for Python!