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 fulfill its function optimally. The following applies:
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.
What is RAG?
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.
Why is that valuable?
Setting up and constantly updating the databases usually involves a lot of effort. But the advantages are enormous:
- Control over the data accessed by the AI assistant
- Targeted answers to business-relevant questions
- High quality and relevance of the results
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 from Meta AI 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
- 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
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
One of the key challenges in development: the data.
In order to provide the chatbot with relevant information, our developers had to obtain, clean and structure large amounts of data in a meaningful way.
We have configured our own AI-supported data pipeline for this purpose, which automatically transfers all information into the appropriate format – efficiently and scalably.
The AI model itself was also intensively tested and fine-tuned.
We optimized the model with real users until the response quality reached the desired level.
And last but not least: seamless integration into the app.
The chatbot’s UX was designed to be intuitive and smooth for users – a central goal of the entire project.
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.
We are still at the beginning - but the way is paved for a multitude of new, AI-supported possibilities.
With the further development of the underlying technologies such as LLMs or machine learning algorithms, they should be suitable 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.
