Mentexa.ai

(name changed due to NDA)

Designing a Central Operations Dashboard to Drive Clarity, Efficiency, and Trust in GenAI-Powered Software Testing

Mentexa.ai is an internal GenAI-powered testing tool for an enterprise QA company. It automates test creation, aiming to reduce QA timelines and increase accuracy. The tool was built and deployed when I joined, but no one could tell if it was working.

I joined the team midway through the project to lead UX for the next phase, designing a central dashboard that would give decision-makers the clarity and control they lacked.

Type

Enterprise SaaS
Central Operations Dashboard
Generative AI

Team

Co-Founder
Design Manager
Senior UX Designer
Product Managers - 2
Developers - 2
UX Designer - me

Contribution

User Research
Information Architecture
UX and UI Design

The unseen challenge - proving AI's value

From
A GenAI-powered tool that automated testing and promised efficiency, without a clear way to prove it was working.
No visibility. No data. No trust.

To
A strategic product expansion that made AI performance visible through real-time dashboards, turning adoption hesitation into data-backed confidence.

"We’ve built this powerful AI tool, but how do we show that it’s saving time and making teams more efficient?"

- A recurring concern from PMs and Engineers

The Mentexa.ai dashboard gave enterprise leaders the visibility they needed to trust, scale, and measure the true impact of GenAI-powered testing.

A dashboard that empowers overseeing organisations.

Real time insights about users, teams, projects and organisations

Tracking impact and effieciency in testing by Mentexa.ai

Impact Metrics

40%

reduction in manual tracking efforts for Super Admins

50%

faster decision-making with centralized, real-time data

45%

cutting down testing time for Mentexa.ai users per project

Jumping into a Project Midway

Week 1

Week 2

Week 6

Week 4

Note: The process involved daily Scrum calls, with feedback and design critiques being essential milestones.

Week 3

Week 5

This wasn't just a design task; it was about creating a measurable foundation for an advanced AI product.

Translating Ambiguity into Actionable Clarity

Make GenAI testing measurable, trusted, and scalable.

Transform qualitative concerns into quantifiable insights.

Empower leaders with the clarity and control they lacked to truly understand, optimize, and scale the AI's impact.

My Goals for the project

Help leadership see what’s working and where the AI is saving time

Uncover the real operational pain points by talking to people beyond just product stakeholders

Bring structure to a complex, multi-org system

Design something actionable, scannable, and future-proof

There were no clear requirements for what the dashboard needed to do. So I created them.

Interviewing the support team, who were handling confused calls from users and admins

Synthesizing needs across PMs, engineers, and client stakeholders

Mapping pain points and digging into system architecture

Doing a quick competitive scan of platforms like Salesforce and Asana to benchmark visibility features

This helped frame the actual opportunity

A real-time dashboard that helps Super Admins track AI impact, manage teams, and optimize testing performance.

What I designed

I designed a modular Central Operations Dashboard that provides Enterprise Leaders with a comprehensive overview.

01. Organizational Overview

KPI cards to show usage, time saved, and token activity
Gamified leaderboard to boost adoption across teams
Visual insights (bar/pie charts) that support quick decisions

02. User & Role Management

Clear role-based access controls
Active/Inactive user tracking
Inner role editing and smart filters

03. Project Performance

Real-time view into the project testing status
A nested team structure to show contribution
Quick actions to reassign users to catch delays early on

We worked lean

I designed wireframes, iterated fast, and got real-time feedback
Used Salesforce Lightning Design principles for visual clarity
Built high-fidelity UI in Figma and collaborated with developers for handoff

Lean UX in Agile Setting

Retrospective

I joined this project in ambiguity, and turned that into structure.
By speaking with those closest to the chaos, I helped the team identify what truly needed to be addressed. Working at the intersection of engineering, product, and support taught me how to lead design with clarity, even when nothing was clearly defined.
This wasn’t just about design, it was about helping the business measure the success of their core product.