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 researchers working with dense content. Powered by AI and machine learning, it analyses text to create interactive visual graphs that help you find insights and connections hidden in the text.
Creating a tool that works for academics as well as market researchers.
To create a versatile product, we identified different usecases by speaking to users and looking at usage metrics across the product.
Creating a tool that works for academics as well as market researchers.
By identifying high and low usage features, we prioritised the ones shared across user types, and set a strong foundation to later optimise for specific needs.
Making core improvements to foundational UX ensured long term success.
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.
1st Milestone – an improved mental model.
Navigation header, improved text and node interactions, and simplified analytics panel gave us a robust foundation to design upon.Visual design improvements that helped the content shine while making the UI recede to the back.
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 support dense content with lots of text.
An improved graph library that immerses you in the content.
We integrated analytic features directly into the graph to help researchers find their insights faster.
Instead of being tucked inside the analytics panel, we highlighted the unique capabilities of the tool. Nesting analytic features in a bottom bar, gave quick access with a lower UI footprint
Outcomes
The project is still being developed and a roadmap for implementation of the features has been created. Due to the limitations of the team and implementation, these features are being slowly released through a browser plugin as a way to validate their value.