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 was designed to empower people who do deep topical research. Powered by AI and machine learning, it analyses text to create interactive visual graphs. We designed a versatile and powerful experience that adapts to your particular research needs.
Creating a tool that works for academics as well as market researchers.
To create a versatile product, we first had to prioritise our hypotheses. By identifying use cases shared across different user types, we set the foundation to later optimise for specific needs without letting other users down.We ensured long term success by making core improvements to the foundational UX.
01
Navigation
Ai generated topic clusters and labels were used to create an index for content that was fed in. Being able to traverse any body of text was foundational to the experience.02
Quick controls
Nodes are the building blocks of the graph. By emphasizing their selection states, interactivity and accessibility, we accelerate task completion and provide granular control over the content.03
Text & Graph relationship
One of the more challenging parts of the redesign was to understand how users shift their gaze or linger between the three panels.
Our 1st Milestone with an improved mental model.
Navigation tags, improved text and node interactions, and simplified analytics panel were foundational to the first iteration of this redesign.As our goal was to help researchers get to their insights fast, we surfaced the underlying concepts of the content while receding everything else. We emphasised topic relationships and the graph itself, while keeping everything else minimal and breezy.
By using colour intentionally we visually re-inforced the connection between topic tags and the nodes on the graph. An improved graph with clearner design and a minimal UI could contain support dense graphs with lots of text.
By bringing to surface deeply hidden graph analytics features, we made it easier for users to find those nuggets of insights that would require hours of research.
We explored ways to bring up powerful analytic features directly from the graph. Instead of being tucked inside the analytics panel, we made the unique capabilities of the tool shine through and decreased the UI footprint even more.