consulting Dataviz & Design Data only creates value when it makes sense to those who decide. Our Dataviz & Design consulting combines design, UX and analytical thinking to create data experiences that are clear, accessible and action oriented. Our specialties How it works Dataviz & Design Design of analytical experiences that people understand and use We do not design pretty dashboards. We design for the user who will sit in front of that screen every Monday morning, with narrative, information hierarchy and interactions that help the decision maker understand what is happening, why it is happening and what to do next. Every project starts by mapping who will use it, how they will use it and in what context the decision will be made. There is no template here, there is a specific data reading problem, with a specific persona on the other side, and that is what defines every choice of visualization, interaction and flow. Specialties in Dataviz & Design Areas of Expertise Depending on where the reading problem lies, in the data structure, in the narrative, in the interaction or on the screen itself, the work takes different shapes. These are the specialties that Cluster deploys, alone or combined, according to what each project requires. Prototyping & Interaction DesignPrototyping of interactions, filters, drilldowns and flows to validate the experience with real users before writing a single line of implementation. See what we deliver Custom Data VisualizationCustom visualizations for complex data that does not fit a standard chart, with precision, readability and analytical intent. See what we deliver Data StorytellingBuilding visual narratives that connect data, context and meaning for those who need to communicate a result, not just explore a number. See what we deliver Dashboard UX/UI DesignRedesign of dashboards and analytical interfaces focused on clarity, hierarchy and decision making, not just aesthetics. See what we deliver AI with Dataviz Dataviz in conversational interfaces The AI layer changed where data appears, but it did not change what makes a visualization useful. Today it is technically simple to connect a language agent to a database or a BI tool. The problem is that most of these agents deliver a poor answer: a chart that does not fit the question, a number without enough context for any sensible decision, or unjustified confidence in data that no one audited. The result is smoke that vanishes by the second prompt. Cluster brings into chats, agents and MCPs the same dataviz rigor it has always applied to dashboards: choosing the visualization that fits the question, information hierarchy, curating what to show and what to omit, and governance over what the agent can or cannot state. That is what separates an AI interface that generates decisions from one that generates doubt.