Linkurious

iObeya - Application of whiteboarding & lean/agile management

Linkurious - Case Study for the Alert Creation Flow

Linkurious - Case Study for the Alert Creation Flow

The perfect management
tool for Agile/Lean

Context

Context

| Current screen for the "Alert Creation"

Linkurious - Case Study for the Alert Creation Flow

Context

Linkurious is a JavaScript librairy and an App designed to be use by technicals users and data scientists. Today, Linkurious use a feature for their app called 'Alert' for technical users and data scientists. Alert help to automatise when a pattern is detected.
Here the flow :
- User Creates an Alert with some detection rules, then, the alert creates cases.
- The cases are managed by investigators or Analysts.
-While functional, user feedback indicates that creating an Alert can be cumbersome with frequent support requests.

Linkurious is a JavaScript librairy and an App designed to be use by technicals users and data scientists. Today, Linkurious use a feature for their app called 'Alert' for technical users and data scientists. Alert help to automatise when a pattern is detected.

Here the flow :
-User Creates an Alert with some detection rules, then, the alert creates cases.
- The cases are managed by investigators or Analysts.
-While functional, user feedback indicates that creating an Alert can be cumbersome with frequent support requests.

| The tasks that i've been given :

No

No

final

final

design

design

How

How

would you approch the problem ?

would you approch the problem ?

Thought process

Thought process

for balancing improvements with constraints.

for balancing improvements with constraints.

Who are the users ?

One of the most important element to not fall into is : survivor bias. The risk : disturb too much the user-flow for users that doesn't have a problem with the current Alert feature.
It's important to, first, understand why some people are able to use it.
- Maybe the interaction isn't common ?
- If others users manage to use it, what types of applications are they also using ?
- What kind of support do they use ?
- What is the goal of their usage ? Is it aligned with how the feature was originally intended to be used ?

| Tools

Figma

Figma

Figma

Figma

Figjam

Figjam

Figjam

Figjam

Illustrator

Illustrator

Illustrator

Illustrator

| A Figjam of the current userflow for the Alert feature

Empowering Visual
Collaboration - My Journey
in Redefining UX at iObeya

Who are the users ?

Who are the users ?

| No data was given to work with, so i've given examples to help understand my logic.

| No data was given to work with, so i've given examples
to help understand my logic.

Data & technical constraint

The use of data…

For this type of case the use of data is very important to understand where problems lies. What kind of data are we looking for ?
Mainly feedbacks but also fail alert creation. This kinds of data will help us to avoid survivor bias. However it is important to keep in mind that context is important for the understanding.
The risk : At this point, asking directly to a user can lead to be blindsided by the needs. Which can lead to improvement that disturb currents users.

HIGLIGHTS

Data & technical constraint

Data & technical constraint

SQCDP Cards : Core
of the management tools

The use of data…

The use of data…

HIGLIGHTS

Data & technical constraint

Data & technical constraint

Empowering Teams :
The iObeya Resource Center

Working with
technical constraint…

Working with technical constraint…

Data & technical constraint

Working with
technical constraint…

One of the most important element is to limit dev works.

This will help reduce the amount of time spent on this modification.

- Prioritize "Quick-fix quick-win"
- What are the technical limitations for this case ? What type of librairy might be impacted ?
- Does this project has a deadline ? How should we prioritize it ?

But we will need to beware of technical debt !

Defining the solution

The start of the conception

The idea is now to start searching where is the problem mainly be. Here from the data we got we can understand that the mains problems come from. Here we can see that two of the mains problems are :

- Information priorisation

- Query calculating inputs

- Data preprocessing.

HIGLIGHTS

Defining the solution

Defining the solution

Multi-Selection :
A Lesson in Failure and Growth

The start of the conception

The start of the conception

HIGLIGHTS

Wireframes

Wireframes

Empowering Teams :
The iObeya Resource Center

Version 1 -
Quick-fix / Quick-win

Version 1 -
Quick-fix /
Quick-win

Wireframes

Version 1 -
Quick-fix / Quick-win

This version mainly focus on the idea of a low effort modification, So the mains changes are to more easily prioritize the way information is given to the user.

However it was made in mind that this version, can also help to ease a transition from the original version to the version 2. Which is a more complete and definitive.

Keep in mind this is a basic wireframe not a definitive version of the solution.

HIGLIGHTS

Wireframes

Wireframes

Empowering Teams :
The iObeya Resource Center

Version 2 - "Fil-Bleu"

Version 2 - "Fil Bleu"

Wireframes

Version 2 -"Fil Bleu"

This version is a big upgrade from the usual use of the current page. Here the main problem from the priorization of the information is that it needs all the inputs from the user in a single page. So i've decided to change this to page comparable of the interface of Youtube when uploading a video. This mean every information are gradually showned by clicking on next. The differents information to put are displayed by a stepper.

Figma File :

HIGLIGHTS

Multi-Selection :
A Lesson in Failure and Growth

Final presentation :

Final presentation

Conclusions

Looking Ahead ✨

This use case was a valuable learning experience that deepened my understanding of how crucial data is to the UX design process. It highlighted how, without real user data or feedback, designers can easily fall into the trap of survivorship bias, making assumptions based on limited or misleading information. This can ultimately lead to design decisions that miss the real needs of users and fail to solve the right problems.

Although I wasn’t selected by Linkurious following this exercise, I’m grateful they gave me the opportunity to work on a real-world problem and allowed me to showcase this case study in my portfolio.

Next Steps 👣

Building on this experience, I plan to deepen my skills in data-informed design and explore more complex problem spaces. I aim to collaborate closely with users and developers to design solutions grounded in real needs. This project reinforced my commitment to thoughtful, user-centered design in every step of the process.

© 2025 Antoine AURAIX All Rights Reserved.

Made with Framer / Spline / ThreeJS

© 2025 Antoine AURAIX All Rights Reserved.

Made with Framer / Spline / ThreeJS

© 2025 Antoine AURAIX All Rights Reserved.

Made with Framer / Spline / ThreeJS

© 2025 Antoine AURAIX All Rights Reserved.

Made with Framer / Spline / ThreeJS