What we do
We create really good conversations between humans and machines throughout the entire design and implementation process.
In all phases, we work in a user-centered and data-driven manner. And right from the start, we think about how we can improve the application step by step.
Design & project briefing
What is it actually about? We find that out at the start of every new project. Only when we really understand what the purpose of the application is, can we think of it. We collect information and decide where to go into depth interviews about ideation, users and stakeholders. As early as this first step, we consider the technical options and evaluate various implementations in order to find the ideal fit for the project.
This applies not only to the selection of the channel, but also to possible integrations of generative AI to further individualize and automate parts of communication.
UX Research & UX Testing
When UX research and UX testing? Always! In every phase of conception, we look at what users want and whether the conversation is flowing. In doing so, we use qualitative and quantitative methods and work with all data that we have available. Even at a very early stage, we try to obtain as many insights as possible, and above all real data.
In doing so, we too relied on the power of generative AI to optimize our processes and testing.
Concept & design
Do conversations always follow certain patterns? Yes but no. In our design process, we give the systems character, appearance and voice. For this purpose, we have developed tools that make it easier for us to process and communicate with stakeholders and bring the bots to life even before the first prototype. We also use the same methods for our Generative AI Branding — so that even dialogs adopted by LLMs (Large Language Models) have an unmistakable language.
Based on this, we define the individual interaction steps. In order to be able to design coherent conversations, we keep an eye on users as well as on the technical limits and possibilities.
Implementation & optimization
Which framework is the right one? There is no universal answer to this question. For each project, we decide which platforms and technologies are the best fit. This starts with choosing the right framework for bot logic and extends to building various prompt chaining and RAG (Retrieval Automated Generation) pipelines to seamlessly integrate ChatGPT or other LLMs (Large Language Models).
We ensure that both automated and non-automated testing methods are connected and that the success of the application can be measured for KPIs and OKRs through proper monitoring.
Architecture & hosting
NLU pipeline, bot logic, TTS integration, backend, and API integration? That's right. We need them so that Conversational Interfaces become more than FAQ pages in another format. The whole thing becomes even more demanding when we want to connect various LLMs (Large Language Models) and other options for Generative AI.
We work both locally and across various cloud services to meet all project and data protection requirements.
Want to talk about a project?