Contributions
Hypothesis & Roadmap
Personas & User Journeys
UI/UX
Team
Product Design (Myself)
Founder/Lead Engineer (Dimitry Parayushkin)
Graph visualisation (Alberto Harres)
Graph visualisation (Antonio Hofmeister R)
InfraNodus is a sensemaking tool for researchers, academics or anybody who wants to dig deep into a body of information. It uses AI and ML to create interactive visual graphs which reveal the concepts and relationships contained in the text.
Groundwork – contextualising the user and making a roadmap.
We defined user personas, journeys and a set of hypotheses to lay the foundation of our work ahead. Using existing data from analytics and an internal understanding of the userbase, since done is better than perfect.01
Enabling navigation of dense content
Infranodus uses Ai generated summaries to label clusters of topics. We used these labels as tags that could help you quickly navigate a discourse.
02
Giving the user quick control over node interactions
Nodes are the building blocks of the graph. By emphasizing their selection states, interactivity and accessibility, we can speed up workflows and give use granular control over their content.03
Controling the overview of all content
One of the most challenging parts of the redesign was to understand how users shift their gaze or linger between the three panels. We explored various approaches to discuss their respective impact.
Iteration 1
A new tagging system, updated text panel and simplified analytics panel led to this iteration in the redesign.Visual/UI updates
We incorporated a new graph visualisation along with UI updates to make the interface feel fast and breezy.
Leveraging the graph’s potential to enable powerful new features.
We explored ways to integrate analytic features directly into the graph. Thereby reducing the burden on the analytics panel, decreasing the ui footprint to make the content shine through.