Applications based on large language models (LLMs) are becoming increasingly important in the B2B sector. They offer companies the opportunity to offer innovative solutions that use natural language as an interface and thus significantly increase user-friendliness. But how can such a model be successfully integrated into an application? In this article, we provide an overview of the most important steps, techniques and potentials of LLM integration.
Briefly explained: Large language models (LLMs)
Large language models (LLMs) like ChatGPT enable the translation of natural language into automated processes.. These models can be integrated into applications to simplify complex tasks, whether by automating workflows or providing expertise in understandable language.
A key aspect of integrating such applications is prompt engineering – the art of formulating precise input commands for LLMs in order to obtain optimal responses. In addition, the Fine-tuning play a crucial role in adapting the model to specific tasks. These two techniques are essential in order to develop a customized solution that is perfectly tailored to the company’s requirements.
The range of LLM applications extends from simple chatbots to complex applications that convert natural language into multi-stage processes.
Here are some examples:
A survey on the application of AI in business processes showed that in 2023, Robotic Process Automation (RPA), Natural Language Understanding and Virtual Agents were among the most widely used AI applications in companies worldwide and across industries.
About 30 percent of companies reported using RPA, compared to 26 percent in the technology and telecommunications sector. AI gained particularly importance in product and service development: 26 percent of companies used it, and in the tech, media, and telecommunications sector, 44 percent. Germans are mostly still cautious about use large language models: according to the study results, 17 percent of companies planned to use AI like ChatGPT, while 29 percent rejected it, and a quarter were still undecided.
Two examples, however, illustrate the potential of LLM application integration and the use of generative AI in the industry:
The integration of large language models into an application, such as a 3D product configurator, requires careful planning and continuous experimentation.
Here are some recommendations:
During the development of our Gen AI showcase, we realized how fast-moving the field of generative AI is. New technologies came onto the market in a matter of weeks, forcing us to constantly rethink our approaches.
One important finding was that even complex problems can often be solved if they are broken down into smaller subtasks. The flexibility of LLMs makes it possible to tackle even challenging tasks step by step.
The integration of large language models in B2B applications offers enormous potential, both for companies and their customers. LLMs not only enable a significant simplification of complex processes, but also create completely new interaction possibilities.
Our advice: Companies should not view this technology as a future trend, but should evaluate today how it can transform their own products and services. The rapid development and adaptability of LLMs makes them an indispensable part of any future-oriented digital strategy.
SIMON GIOVANNI ENGEL
software developer
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