From translations to software development – AI is taking over more and more standard tasks in the office. However, as soon as a task becomes more complex, conventional tools reach their limits. AI assistants are different: they are specifically programmed to use internal databases to automate tasks and offer employees personalized support. From data analysis to knowledge transfer and individual coaching.
How does an AI assistant work?
AI assistants provide employees with targeted support for clearly defined tasks. They use large language models (LLM) such as ChatGPT and natural language processing. On the one hand, they are able to understand all user commands and formulate suitable, easy-to-understand answers. On the other hand, they can easily process large amounts of data, understand correlations and recognize patterns.
This is crucial, as an AI assistant relies on extensive internal databases to perform its function optimally. The more content is available and the more carefully this content is categorized, the better.
Thanks to machine learning and self-learning algorithms, the system can also continue to develop and improve. This means that with each interaction, an AI assistant adapts its answers more precisely to the individual needs, working methods and preferences of each user and therefore performs its task better and better.
Rapid development thanks to Panter RAG framework
Large LLMs can be used specifically for your own company without having to train your own model. The key lies in linking pre-trained language models with a company’s own knowledge base.
This is where the Retrieval Augmented Generation Framework (RAG) comes into play. With the framework developed by Panter, the LLM no longer only obtains its information from the existing training data, but supplements it with predefined knowledge sources, such as an internal database or an API. Similar to a search engine such as Perplexity, this enables it to find and display the information relevant to a query in a targeted manner.
Setting up and constantly updating the databases usually involves a lot of effort. But the advantages are enormous: the company can precisely define and control which data the AI assistant uses as its knowledge base.
In summary, the competitive advantage arises from access to unique, proprietary data that is not available anywhere else and its targeted provision for AI queries.
Create added value for your company – with our AI assistants
Panter develops AI assistants for companies from A to Z. We have developed a flexible and cost-efficient chatbot framework that can be used to query specific data with the latest AI models. Whether with Google Gemini or OpenAI GPT as a service, GPT in the Azure Cloud or Llama at a Swiss hosting location – our framework can be adapted to almost all of our customers’ requirements.
Our full-stack development team with UX designers will be happy to support you from the development of a proof of concept (POC) to the final integration of the solution into your company. In addition, a dedicated DevOps team ensures that the further development and operation of the software are optimally integrated.
Possible uses of AI assistants in companies
Simple and, with increasing development, increasingly complex tasks can be performed fully automatically by artificial intelligence. This allows business processes to be optimized and valuable resources to be freed up.
The use cases for AI assistants include, among others:
- Data analysis: AI can process and summarize large volumes of data and text within a very short time and present the core content clearly. This allows companies to make well-founded and data-driven decisions.
- Chatbot for company data: Provision of product information from knowledge databases, FAQs for internal purposes and customers
- Personalized training: By accessing internal knowledge databases, AI assistants create tailor-made learning programs for employees and thus promote individual development in a targeted manner.
- Chatbots in customer service: AI-supported chatbots available around the clock enable fast and personalized responses to customer inquiries and contribute to a better customer experience.
Personalized leadership coaching with artificial intelligence – WolfPak
How do AI assistants prove their worth in the business world? Panter has developed a web & mobile app for WolfPak that specifically strengthens the leadership skills of employees in companies through data-driven, personalized coaching.
The core element is an individual learning path in the app, on which managers are accompanied by a personal AI coach and chatbot. This allows them to train precisely the skills that are currently important to them and receive sound advice for their further development directly in the app.
The AI assistant can draw on curated learning content and internal, company-specific knowledge databases to compile a personal learning path and answer specific questions.
Challenges & solutions: How we optimized the AI assistant
This gave rise to one of the major challenges that the Panter developers had to overcome: obtaining, cleansing and structuring the data required for the chatbot. An AI pipeline was also configured for these steps, which prepares the data in the format required for the application. In addition, the configuration and fine-tuning of the AI model had to be improved through intensive testing with users so that the quality of the answers reached the desired level.
And last but not least, the seamless integration and linking of the chatbot’s user experience into the app was key to making it as easy as possible for users to use the application. Want to learn more about WolfPak and the development of the AI assistant by Panter? Click here for our success story.
AI assistants create added value – for companies and employees
Applications like WolfPak show this: There are already use cases in which the use of AI assistants brings companies real added value. And this is just the beginning. As the underlying technologies such as LLMs or machine learning algorithms are developed further, they are likely to be considered for many more and significantly more complex applications in the future. However, this is only possible if data availability and quality are improved through intensive test cycles.
Panter supports companies in the development of AI assistants with extensive expertise and a full-stack development team. From initial workshops in which the project scope and the exact requirements for the tool are defined, to the creation of a POC, UX design and integration of the solution into existing processes.
