Work About

Crafting intuitive, scalable experiences ✨ through AI‑native workflows driving efficiency and outcome‑oriented design.

A User Experience Designer with 15+ years of experience across SaaS, enterprise, and AI-driven products working across research, strategy, and design to solve complex problems in a simple, human way. I also bring AI into my UX workflows using tools like Figma Make, ChatGPT, Claude, and Gemini to speed up ideation, streamline processes, and make better design decisions.

Recent Works

ZZAZZ - Content Economy, Redesigned

ZZAZZ - Content Economy, Redesigned

Designing a dynamic pricing ecosystem for the open content economy - Terminal, Publish, and Signal powered by LPM.

UX ResearchProduct DesignDesign SystemPrototyping
SalesX - Voice-First CRM

SalesX - Voice-First CRM

Designing a simplified AI/ML-based CRM that eliminates data entry friction for modern sales teams.

UX ResearchVisual DesignDesign SystemPrototyping
Airbus - Aircraft Ground Operations

Airbus - Aircraft Ground Operations

Mission-critical interface design for A350 and A380 aircraft maintenance and authorisation systems.

UX/UIInteraction DesignInformation ArchitecturePrototyping
Waybeo - AI Insights & Call Analytics

Waybeo - AI Insights & Call Analytics

Transforming raw call data into actionable insights for sales and marketing teams.

UX/UIInformation ArchitecturePrototypingUser Testing
Onne App - Super App

Onne App - Super App

Designing a unified super app for SMBs on Android.

UI/UXInformation ArchitectureAndroid
Tring Partner - Mobile Sales

Tring Partner - Mobile Sales

Building a mobile-first sales call management app for small and medium businesses.

UXMobileMaterial Design
Back to work

ZZAZZ - Content Economy, Redesigned.

Building a three-part ecosystem that gives creators real pricing power and readers frictionless access - through Terminal, Publish, and Signal.

1 - Terminal: Landing page 2 - Terminal: Search results 3 - Terminal: Article 4 - Publish: Overview 5 - Publish: Reports 6 - Publish: Compare articles 7 - Signal: Views and Timepay
Client ZZAZZ
Duration 15 months · 2025–2026
Role Product Designer
Scope UX Research, User-flow Definition, UX Strategy, Information Architecture, Design System, Usability Testing

ZZAZZ is building the infrastructure layer for the content economy - a system that replaces today’s broken creator monetisation model with one that’s dynamic, fair, and friction-free on both sides. Three products form the ecosystem: Terminal (consumer discovery and access), Publish (creator publishing and analytics), and Signal (a lightweight embeddable widget). Powering all three is LPM - a Large Pricing Model that sets real-time access prices based on demand, engagement, and context.

My role was to translate this ambitious technical vision into product experiences that felt natural to use, from the first search query to the first payout.

01 Context & Challenge

Team & Tools

Team
3
Product Managers
5
Product Designers
Including me, across all three products.
Gemini
3 days
Compressed a 2-week research phase via competitor teardowns and paywall UX sweeps.
Claude + MCP
<4 hours
PRD drafts, user stories, and API specs - plus Jira and Confluence auto-populated each sprint.
Figma Make
15 min
Signal widget variants per iteration round - down from ~2 hrs of manual design.
Full Cycle
4 weeks
Scoped as 10 weeks. No cuts to quality.

The Problem

Creators are locked into subscription-or-free binaries that leave money on the table, while readers drown in recurring bills just to follow the writers they like. Neither side wins - the market needed a new pricing primitive.

Where the system breaks - creators can't price their work fairly, and readers won't pay through friction-heavy subscription walls.

Creator side

  • All-or-nothing monetisation
  • Poor trial-to-paid conversion
  • No visibility into what drives willingness to pay
  • Platform dependency and algorithm risk

Consumer side

  • Subscription fatigue from recurring charges
  • No way to pay for a single article
  • Inconsistent access across publishers
  • No unified reading identity or history

The ZZAZZ Approach

ZZAZZ introduces the Large Pricing Model (LPM) - a dynamic pricing layer that replaces the binary free/paid choice with a full pricing spectrum set in real time, based on content demand, reader engagement history, and context signals. Readers pay only for what they actually want to read; creators get a tuned, automated monetisation layer without configuration overhead. Three interconnected products make this work in practice:

Product 01
Terminal

Consumer-facing search and discovery. Readers find content across all ZZAZZ publishers, see real-time pricing, and pay per piece - no subscription required.

Product 02
Publish

Creator-facing publishing dashboard. Writers manage their catalogue, configure pricing ranges, monitor earnings, and view audience analytics in one place.

Product 03
Signal

An embeddable website widget that publishers drop onto existing sites. Signal surfaces real-time pricing and enables one-click access without redirecting readers away.

My design scope

Across all three products, my primary responsibility was the reader-facing experience: Terminal's discovery, pricing transparency, and first-payment flow. I co-designed Publish's creator workspace and owned the Signal widget interaction pattern end-to-end.

What I was asked to solve

The founding team had a strong technical thesis (LPM as a pricing primitive), but no answer to the design question: how do you make dynamic pricing feel fair rather than arbitrary to someone who has never encountered it before? That was the brief I started with.

02 Research

Research Plan

01 Stakeholder Interviews Business goals, constraints, and LPM value proposition with founders and product leads.
02 User Interviews Depth sessions with independent writers and frequent readers on paywalls and payment friction.
03 Competitive Analysis Audit of Substack, Medium, Patreon, YouTube, and news paywalls to map the monetisation landscape.
04 Survey 142 responses validating attitudes toward micropayments, subscription fatigue, and pricing transparency.
The Gap

No major platform combines creator pricing control with flexible per-access reading. Substack, Medium, Patreon - all binary: free or subscription.

The Opportunity

High creator control + flexible reader access is entirely unoccupied. That quadrant is ZZAZZ’s core positioning.

The Differentiator

Dynamic pricing (LPM) + embeddable widget (Signal) + cross-publisher reader identity - none of the five competitors offer all three.

Survey - 142 responses across creators and readers, validating qualitative findings at scale.

142
respondents
76%
hold 3+ subs, actively read fewer than 2
83%
abandoned a paywall in the past two weeks
61%
of creators earn under ₹10k/month despite 15+ hrs/week
54%
would pay ₹5–20/article with no sign-up, under 10s
71%
open to AI pricing if they keep a floor price override
89%
want to see why a price was set, not just what it is

Four research tracks converged on the same gap: no platform gave creators pricing control and readers a frictionless way to pay per article simultaneously. That gap wasn't a feature request, it was the entire product opportunity. Everything that followed was designed to close it.

The most important pattern - Identity & Continuity - wasn't in my original screener at all. It changed the scope.

03 Analysis & Convergence

Key Insights

01

Subscription fatigue is about commitment, not cost.

02

Creators don’t want more configuration - they want better defaults.

03

Dynamic pricing is only trustworthy if readers can see why the price was set.

04

Signal must feel native to the publisher, not ZZAZZ.

05

Cross-publisher reading history - the feature readers didn’t know they wanted.

Design Direction

Decision 01
Transparency before features

89% of readers wanted to know why a price was set. Pricing legibility became a structural requirement across all three surfaces from day one.

Decision 02
Terminal as the north star

The reader’s first-payment moment was the stress-test for every systemic decision. Publish and Signal were designed in parallel, but Terminal came first.

Decision 03
Friction reduction over configuration

83% of paywall abandonment was due to steps, not price. Any feature adding overhead before a first payment or payout was deprioritised.

04 Synthesis & Divergence

Personas

Three distinct users, one shared constraint: trust.

AS
Arjun Sharma
Independent Writer · Publish
Goal

Sustainable income from writing. Needs a middle ground between free and hard paywall.

Pain

Platform fees eat 16% before payout. No pricing flexibility between free and paid.

₹2,400 avg. monthly - 64% below viability
DC
Divya Chinnappa
Product Manager · Terminal
Goal

Quality content on demand. Support the writers she values without another monthly commitment.

Pain

Pays for 4 subscriptions, actively reads 1. Every article hits a paywall anyway.

73% of paid subs go unread each month
RP
Rajesh Pillai
Digital Editor · Signal + Publish
Goal

Loyal readership beyond algorithmic reach. Flexible monetisation without hard paywalls.

Pain

AI answers queries before readers reach the site. Hard paywalls kill discovery.

−41% organic search traffic in 18 months

Journey Maps

Following Arjun across six stages - from discovery to the loyalty flywheel.

DISCOVER ONBOARD CREATE AWAIT CONVERT LOYALTY EMOTION EXPERIENCE TOUCHPOINT OPPORTUNITY Happy Neutral Unhappy 🙂 😟 😊 😐 🤩 😄 • Finds ZZAZZ via Twitter • Reads about Publish features • Compares payout vs. Substack “Payout terms look better here” • Creates account, sets up tiers • Attempts CSV list import • Hits friction with 3-step import “Why 3 separate CSV exports?” • Writes piece, adds paywall break • Previews on mobile • Hits Publish with confidence “Free vs. paid - on my terms” • Shares on Twitter & LinkedIn • Checks analytics every hour • Open rate 34%, no read-depth “Did they read the whole piece?” • Gets paid subscriber alert • Reviews payout dashboard • First ₹299 earned “Someone paid. This piece landed.” • Reader shares via Signal • New readers discover creator • Organic distribution begins “I just need to write.” Marketing site Publish · Setup Publish · Editor Analytics · Terminal Publish · Payout Signal · Publish OPPORTUNITY Clearer comparison vs. Substack OPPORTUNITY 1-click list migration OPPORTUNITY Web ↔ email preview parity OPPORTUNITY Read-depth beyond open rate OPPORTUNITY Link conversion to trigger piece FLYWHEEL ✦ Creator-reader loop begins

How Might We

HMW 01

Make dynamic pricing feel fair to readers who’ve never encountered it before?

HMW 02

Let creators benefit from LPM without adding configuration to their workload?

HMW 03

Design Signal to feel native to the publisher’s brand, not an overlay?

HMW 04

Build a cross-publisher reading identity that feels like a benefit, not tracking?

HMW 05

Make the first payment fast enough that readers don’t abandon at the decision point?

Three personas, three surfaces, but one shared constraint: trust. The priority matrix forced a clear order. First-payment flow and pricing legibility ranked above every configuration feature. Anything that added steps before a reader paid or before a creator understood their earnings was deprioritised, regardless of how requested it was.

05 Design & Iteration

Design Principles

Principle 01
Legible pricing

Every price must carry enough context to explain itself - no hunting required.

89% of readers wanted to know why a price was set. 6/8 missed it entirely when unstyled.
Principle 02
Zero friction at payment

Auth and payment front-loaded on first use. Every access after that is one tap.

83% abandoned a paywall recently. The barrier wasn’t price - it was the number of steps.
Principle 03
Creator confidence, no config overhead

LPM runs in the background. Creators set a floor and ceiling - that’s it.

4/5 creators weren’t opposed to AI pricing - they just needed an override. Guardrails, not a panel.
Design Decision: QAP Chart

A 72-hour price history chart - like a stock sparkline - shown at the paywall. Readers could see if the price was rising, falling, or stable. Context made dynamic pricing feel fair rather than arbitrary.

What it changed

In V1, 5/8 readers called dynamic pricing “random.” After the QAP chart in V2, that dropped to 1. It didn’t add trust - it made the existing trust logic visible.

The pushback

“Readers aren’t traders.” My counter: you don’t need financial literacy to understand a falling line means the price is dropping. Familiarity is the mechanism.

Design System

Designing across three products simultaneously made one thing clear: a shared system wasn't optional. Every component had to carry meaning in three different contexts: discovery, publishing, and embedding. The design language that emerged wasn't a style guide; it was the connective tissue that made Terminal, Publish, and Signal feel like one ecosystem rather than three separate tools.

06 Testing & Validation

Usability Testing

Method

Moderated remote

Think-aloud · Loom · Google Meet

Participants · n=8

4 Independent creators
4 Paid newsletter readers

Task Flows · 3

T1 Find & buy a paywalled article
T2 Set paywall break in Publish
T3 Subscribe via Signal mid-article

Success Metrics

Completion rate≥80%
SUS score≥75
Time on taskvs. baseline
Error frequencyper path

87%

Avg. task completion

78

SUS score (Good)

−34%

Time on task vs. V1

3

Critical issues found

T1 · Price Discovery Critical

Finding · Root cause

6/8 missed the price tag - price badge was small grey text inside meta row, same weight as author name.

Fix applied

Promoted to coloured pill badge on article card. Completion rate 50% → 87%.

T2 · Paywall Break Moderate

Finding · Root cause

3/4 creators couldn't find the paywall break control - buried 2 levels deep in "Monetise" dropdown, icon-only.

Fix applied

Inline block-level insertion via + between paragraphs. Discovery time 94s → 18s.

T3 · Signal Trust Moderate

Finding · Root cause

2/4 readers described the widget as "an ad" - generic "Subscribe" CTA with no creator context in the collapsed pill.

Fix applied

Added creator avatar + name. Widget reads "Follow Arjun Sharma". Trust hesitation 50% → 12%.

Three critical issues. All three fixed before handoff. The clearest signal from testing: pricing transparency wasn't a trust-builder, it was a prerequisite. Without it, readers stalled before they even reached a payment decision. Small copy and hierarchy changes moved completion rates by margins that no visual redesign alone would have achieved.

07 Impact & Learnings

Final Designs

Outcomes

Across 15 months and three shipped products, the design work moved three numbers that mattered, and surfaced one that I hadn't anticipated.

87%
Task completion
Across all three usability test flows. Up from 51% average in V1, driven almost entirely by the price badge redesign and paywall break discovery fix.
−34%
Time on task vs. V1
The paywall break control went from 94s to 18s discovery time after I moved it inline. No feature change, just a placement decision.
78
SUS score (Good)
Industry average for SaaS is 68. At 78, Terminal and Publish cleared "Good" territory on first round of testing, before further iteration.
3
Pilot publishers
Signal was adopted by three pilot publishers within the first month after the trust redesign. Adding the creator name to the collapsed widget pill was the fix that unblocked them.

The number I didn't anticipate: of the three critical issues found in testing, all three were copy and hierarchy changes, not component rebuilds, not new flows. The biggest usability gains came from making existing information more visible, not from adding new information. That shaped how I approach every audit I run now.

What I'd Do Differently

Learning 01
Explain novelty inline, not upfront.

Onboarding screens had the worst recall - only 2/8 remembered the pricing explanation 15 mins later. Inline copy at the moment of encounter had 4× better recall.

Learning 02
Same tokens, different affordances per product.

Identical article cards across Terminal and Publish confused readers - the card read as “your content,” not “content to discover.” Shared tokens, distinct interaction patterns per surface.

Learning 03
Design the entry point last, not first.

Signal was designed last but was the first touchpoint for most readers. 3/4 who hit it first described ZZAZZ as “a widget thing.” Sequence effort by user-facing impact, not engineering complexity.

Back to work

SalesX - Voice-First CRM.

Redesigning CRM from the ground up - powered by NLP (Natural Language Processing) to eliminate manual data entry through voice-first interaction so sales teams can focus on what they actually do best.

Salesx 01 Salesx 02 Salesx 03 Salesx 04 Salesx 05 Salesx 06
Client SalesX (salesx.io)
Duration 2 years · 2017–2019
Role Lead UX Designer
Scope UX Research, Wireframing, Prototyping, UI Design, Design System
Technology NLP (Natural Language Processing)

SalesX is reinventing the CRM experience through NLP-powered voice interaction - allowing sales teams to capture, log, and manage data entirely by voice, and focus purely on selling. Traditional CRMs have evolved into systems that demand excessive manual data entry, often shifting the focus of relationship managers from client engagement to administrative tasks.

The goal: create a self-driving CRM that captures, organises, and analyses sales activities automatically, making manual data entry obsolete.

Zero Data Entry & Automated Organisation
Intelligent Meeting Summaries & Smart Follow-ups
Effortless Pipeline Management
01

Understanding the user

User research · Personas · Problem statements

User Research

What we learned in the field.

Our user research revealed that sales professionals struggle with excessive manual data entry, context switching across multiple tools, and inefficient follow-up management. SalesX addresses these pain points by automating data capture, organising interactions intelligently, and providing AI-driven insights to streamline the sales workflow.

8 In-depth interviews with sales professionals across different industries
3 Companies observed during a 1-week sales team shadowing study
50+ Sales professionals surveyed about their daily workflow challenges
1 Deep analysis of existing CRM usage patterns and failure modes
Pain Points

Three critical breakdowns in how CRMs are used today.

01

Manual Data Entry Overload

Sales professionals spend excessive time logging interactions, with 82% missing crucial details and 67% delaying note entry, leading to irretrievable information loss.

82%miss crucial details
67%delay note entry
02

Context Switching Disruptions

Managing customer relationships requires juggling multiple tools, causing 73% to lose focus mid-task and 89% to desire automatic activity logging.

73%lose focus mid-task
89%want auto-logging
03

Inefficient Follow-up Management

Manual tracking leads to 64% missing deadlines, 91% wanting AI-driven reminders, and 78% struggling to maintain accurate customer histories.

64%miss deadlines
91%want AI reminders
Personas

Who we designed for.

Enterprise Account Executive

Sarah Chen

Age 35 · San Francisco

Sarah manages large enterprise accounts at a B2B SaaS company, handling deals worth $500K+. Tech-savvy but values efficiency over feature complexity.

Goals
  • Minimise time on administrative tasks
  • Track complex stakeholder relationships
  • Maintain detailed meeting records without manual effort
Frustrations
  • "I spend more time updating the CRM than talking to customers"
  • "Important details get lost between meetings"
  • "Can’t quickly find historical context during calls"
40%

of selling time lost to CRM admin - blocking her $1.5M monthly quota

Sales Manager

David Rodriguez

Age 42 · Chicago

David leads a team of 12 sales reps, focusing on team performance, forecasting, and process optimisation. Data accuracy is his greatest daily blocker.

Goals
  • Accurate pipeline visibility
  • Team productivity optimisation
  • Data-driven coaching for reps
Frustrations
  • "Can’t trust the data in our CRM"
  • "Reps don’t update their opportunities regularly"
  • "Difficult to identify coaching opportunities"
60%

of CRM data is outdated - forcing 15+ hrs/week on validation instead of coaching

02

Interface design principles

Invisible interface · Contextual intelligence · Minimal interaction

Design Principles

Three rules that shaped every decision.

Invisible Interface

  • System works in the background without user intervention
  • Information appears automatically when needed
  • Zero-click information capture

Contextual Intelligence

  • Smart categorisation of interactions
  • Automated relationship insights
  • Predictive next actions

Minimal Interaction Required

  • One-tap access to key functions
  • Automated data organisation
  • Smart defaults based on user behaviour
References

Products that shaped our thinking.

Superhuman Email Client

Superhuman & Apple Live Activities

Auto-prioritisation of important emails and seamless interactions. Subtle background updates without user intervention - context-aware recommendations that appear only when needed.

Notion UI

Notion AI & HubSpot

Automatic linking and categorisation of information. Smart relationship tracking and predictive actions. Predictive text and recommended next steps - reducing cognitive load at every turn.

03

Starting the design

Low-fidelity wireframes · Usability testing · High-fidelity prototype

Low Fidelity - Web

Make a call flow - six screens, one seamless journey.

Salesx Lofi 01 Salesx Lofi 02 Salesx Lofi 03 Salesx Lofi 04 Salesx Lofi 05 Salesx Lofi 06
Low Fidelity - iOS

Mobile-first wireframes for on-the-go sales management.

iOS screen 1
iOS screen 2
iOS screen 3
iOS screen 4
High Fidelity - Web

Refined after usability testing - a CRM that feels invisible.

SalesX high-fidelity web design
High Fidelity - iOS

Usability-tested iOS interface with final visual polish.

SalesX high-fidelity iOS design
04

Feature spotlight

Calls - the heart of the sales workflow

Calls Feature

Four states that define the call experience.

Calls overview View & edit notes New or existing call Live note-taking
Salesx Calls 01 Salesx Calls 02 Salesx Calls 03 Salesx Calls 04

SalesX - Working prototype

Outcome

A CRM built for humans.

Dramatically reduced data entry

Intelligent automation handles the logging, leaving reps to focus on building relationships.

Scalable design system

A unified component library supporting both web and iOS, enabling consistent shipping velocity.

Strong early adoption

Measurable improvements in deal logging speed and overall CRM engagement from day one.

Next Project

Waybeo - AI Insights & Call Analytics.

Back to work

Waybeo - AI Insights.

Designing an AI-powered analytics feature that transforms raw call data into actionable intelligence - helping sales and marketing teams make faster, better decisions.

Ai 1 Ai 2 Ai 3 Ai 4 Ai 5
Client Waybeo (waybeo.com)
Duration 1 year · 2016–2017
Role UX Designer (Individual Contributor)
Scope Information Architecture, User Research, User Flows, Wireframes, Hi-Fis, Prototype

AI Insights is an AI-powered analytics feature that enhances sales and marketing by analysing customer call interactions. It provides actionable insights to improve engagement, optimise marketing efforts, and refine sales strategies - helping businesses make data-driven decisions efficiently.

The existing product lacked AI capabilities and offered only a basic analytics dashboard without deeper intelligence. The opportunity: introduce a native AI Insights tab with a customisable dashboard and recommendations that surface critical insights seamlessly.

Faster decision-making through improved data visualisation
Native AI insights - not retrofitted, built-in from day one
Actionable recommendations for sales & marketing teams
Before

The existing product - no AI, no actionable insights.

Waybeo existing product before AI Insights
01

Understanding the user

User research · Competitive analysis · Personas · Problem statements

User Research

Stakeholder discussions and competitive benchmarking.

Stakeholder and customer discussions shaped the direction - covering the right formats and visualisations for insights, how to simplify complex data, alignment with customer workflows, and the role AI should play in improving sales efficiency.

3 Competitors benchmarked - Exotel, Knowlarity, and existing Waybeo product
4 Key feature dimensions evaluated: AI insights, call tracking, real-time analytics, integration
1 Clear differentiator: native AI insights with user-friendly, actionable recommendations
5 wk End-to-end design cycle from research through to high-fidelity prototype
Competitive Analysis

Where competitors fall short - and where Waybeo can lead.

Competitive Analysis Matrix
Pain Points

Four gaps in the existing analytics landscape.

01

Scattered & Unstructured Data

Existing platforms present raw data without clear insights, making it difficult for businesses to extract meaningful information from call interactions.

02

Lack of Actionable Insights

Competitors offer basic analytics but fail to provide AI-driven recommendations that help businesses optimise their sales and marketing strategies.

03

Complex & Non-Intuitive UI

Many analytics tools require technical expertise, making it challenging for non-technical sales and marketing users to navigate and leverage insights.

04

Inefficient Decision-Making

Without a centralised AI-powered dashboard, businesses struggle to make quick, data-driven decisions that improve engagement and conversions.

Persona

Who we designed for.

Sales Lead - Auto Dealership

Rajesh Vashi

Age 34 · Mumbai

Rajesh is a sales executive lead at an auto dealership who handles a high volume of customer calls daily. He relies on call data to track leads and close deals, but the current system gives him raw numbers with no context or follow-up guidance.

Goals
  • Increase sales conversions with better customer engagement
  • Use AI insights to understand customer behaviour and improve follow-ups
  • Prioritise high-potential leads for efficient selling
Frustrations
  • "Struggles to analyse call data manually, leading to missed opportunities"
  • "Wastes time sifting through unstructured data instead of selling"
  • "Lacks actionable insights to refine sales strategies effectively"

manual analysis time wasted per week - missing high-potential leads and slowing decision-making at a critical point in the sales cycle

02

Information architecture

Four sections · Seamless navigation · AI-driven structure

Information Architecture

Structuring AI insights into four clear, navigable sections.

AI Insights structures data into four key sections: Dashboard (sales metrics overview), Potential Opportunities (lead likelihood scoring), Models (product-level insights), and Call Log (interaction-level analysis). This IA-driven approach enables seamless navigation, making AI-powered insights more accessible, actionable, and intuitive.

Information Architecture diagram
01

Dashboard

High-level sales metrics - total calls, AI-processed calls, sales intent score, potential opportunities breakdown, top dealers, top keywords.

02

Potential Opportunities

Lead likelihood cards (Likely / Neutral / Not Likely) with top reasons, top questions asked, and trend data for prioritising follow-up actions.

03

Models

Product-specific insights including transmission, fuel type, and colour preferences with variant-level details to inform inventory and marketing decisions.

04

Call Log

Interaction-level analysis with AI call summaries, keyword tags, and a detail overlay for reviewing individual call recordings and transcripts.

03

Starting the design

Wireframes · Draft UI · Stakeholder review

Wireframes

Low-fidelity layouts for all four sections.

Wireframe: Dashboard and Models Dashboard & Models
Wireframe: Dashboard detail Dashboard detail
Wireframe: Potential Opportunities Potential Opportunities
Wireframe: Call Log Call Log
Draft UI

Initial designs presented to stakeholders for feedback.

Waybeo Draft Dashboard Waybeo Draft Opps Waybeo Draft Models Waybeo Draft Calllog Waybeo Draft Calllog Slider
Dashboard Potential Opportunities Models Call Log Call Log (Slider)
04

Refining the design

Usability study · Before & after · Hi-fi prototype

Usability Study

Four key findings that shaped the final design.

01

Date Range Selection

Users found the date picker controls unclear. Simplified the filter row to make time-period selection faster and more intuitive.

02

Simplified Model Overview

The Models section contained too much data density. Reorganised the layout with clearer hierarchy and tab-based navigation by model variant.

03

Cleaner Navigation Structure

The left-hand navigation lacked clear active states and section separation. Refined with stronger visual hierarchy and consistent active indicators.

04

Call Log & Slider Presentation

The call detail overlay was difficult to scan. Enhanced the slider layout with better structured call summaries, keyword tags, and recording controls.

Before & After

How each screen evolved after usability testing.

Before
Dashboard before
After
Dashboard after
Before
Potential Opportunities before
After
Potential Opportunities after
Before
Models before
After
Models after
Before
Call Log before
After
Call Log after
High-Fidelity Prototype

The refined product - AI Insights live in the Waybeo platform.

Waybeo AI Insights high-fidelity prototype
Outcome

Impact and what I learned.

Happy end users

Intuitive data accessibility, improved sales conversions, and a competitive differentiation through native AI.

Scalable AI framework

The design established a foundation for future AI feature growth across the Waybeo platform.

Room to grow

Data depth, personalised insights, and better end-user guidance were identified as the next priorities for the product.

AI Insights has completely transformed how we analyse customer interactions - it’s intuitive, actionable, and has directly boosted our sales conversions.
Tata Motors Regional Sales Head

Next Project

Verint - Workforce Management Suite.

Back to work

Airbus - Aircraft Ground Operations.

Designing mission-critical interfaces for A350 and A380 aircraft maintenance, and a secure authorisation platform for enterprise services.

A 1 A 2 A 3 A 4 A 5 A 6 A 7
Client Airbus
Year 2019 – 2023
Role UX/UI Designer
Scope UX/UI, Interaction Design, Information Architecture, Prototyping, User Testing

Interfaces for aircraft that don’t forgive mistakes.

ArGO is a specialised application for managing the maintenance and operation of commercial aircraft on the ground and in flight - primarily for Airbus A350 and A380 models. The service is provided by Airbus to airline companies worldwide.

The stakes here are extraordinarily high. Every interface decision - a label, an information hierarchy, a confirmation flow - has safety implications. Designing in this domain required extreme rigour, deep collaboration with domain experts, and continuous testing with real maintenance engineers.

Large volumes of highly sensitive data are transferred between aircraft and ground systems through ArGO, accessible only within secured Airbus networks. Security and clarity had to coexist throughout.

Deep domain immersion.

The project began with extensive field research - understanding how maintenance engineers actually work, the cognitive load they operate under, and the failure modes of existing tools. User journeys were mapped in granular detail before any interface work began.

Prototypes were tested iteratively with actual ArGO users, incorporating feedback from both technical stakeholders and end users in airline maintenance operations.

Auth 1 Auth 2 Auth 3 Auth 4 Auth 5 Auth 6 Auth 7 Auth 8

Managing access at enterprise scale.

Core Elec is the authorisation platform underpinning the broader Airbus digital ecosystem - managing access to APIs, UI surfaces, and user roles across multiple interconnected products.

Designed for a large-scale solution where multiple products work in concert, the platform required a clear, consistent model for permissions, roles, and access states that technical administrators could operate confidently.

Trusted by airlines worldwide.

The ArGO interface shipped to airline partners and has been in active use for A350 and A380 fleet management. Core Elec established a reliable access-control foundation for Airbus's growing digital product suite.

Next Project

Tring Partner - Mobile Sales Management.

Back to work

Tring Partner - Mobile Sales Management.

Building a mobile-first sales call management app for small and medium businesses using Material Design principles.

Tring 1 Tring 2 Tring 3
Client Tring Partner (tringpartner.com)
Year 2015 – 2016
Role UX Designer
Scope UX, Material Design, Development Collaboration

Sales call management in your pocket.

Tring Partner is a mobile-based application for small and medium businesses to manage sales calls within a team or across multiple teams. The product targets the growing SMB segment that needs CRM-like capabilities without the enterprise overhead.

The design challenge was building something powerful enough to be genuinely useful for sales teams while remaining simple enough for adoption across non-technical users in small businesses.

Material Design as a foundation.

The project used Material Design as the foundational design language, collaborating closely with the development team to ensure the implementation matched the intended experience.

I worked across UX flows and UI execution - designing the information architecture, interaction patterns, and visual components that made the app feel native and intuitive on Android devices.

Streamlined team sales operations.

Tring Partner shipped with a clean, consistent Material Design implementation that gave SMB sales teams a reliable tool for call logging, team coordination, and performance tracking - all from their mobile devices.

Next Project

Onne App - Super App.

Back to work

Onne App - Super App.

Designing a unified super app for small and medium businesses on Android.

Onne 1 Onne 2 Onne 3
Client Onne App (onne.world)
Year 2016 - 2017
Role UI/UX Designer
Scope UI, UX, Information Architecture, Android

One super app.

Onne App is a super app for small and medium businesses, built natively for Android. The product - Onne App and Onne Business - aimed to consolidate team communication into a single, reliable mobile experience.

For SMBs operating without dedicated IT infrastructure, a communication tool needs to be intuitive from day one, reliable under real business conditions, and simple enough that the entire team adopts it.

Structure through information architecture.

The project required careful information architecture work to organise the app's features - messaging, calls, team management, and business tools - into a hierarchy that felt natural rather than cluttered.

The design balanced the breadth of functionality with a clean, uncluttered interface, ensuring that everyday communication tasks required minimal steps and cognitive effort.

Communication that just works.

Onne App launched on Android with a structured, navigable interface that brought together the key communication needs of SMB teams. The information architecture established a clear foundation for future feature expansion across Onne Business.

Next Project

SalesX - Voice-First CRM.

Process & Philosophy.

Great design solutions don't exist in isolation - they are part of larger systems. Understanding the full context, the people, their needs, and the environment they operate in is where meaningful design begins.

Evidence-based design

Design decisions grounded in data, research, and rational insights rather than intuition alone. Every choice answers a question, informs a decision, or validates an assumption.

Calm technology

The best design fades into the background, letting people focus on what matters. Technology should be a quiet enabler - seamless, intuitive, and unobtrusive.

Systems thinking

Using user journeys and service blueprints to map the interconnectedness of different parts of the system, creating cohesive experiences across physical and digital touchpoints.

Experimentation

Design as exploration. Prototyping quickly, testing assumptions, and iterating based on what's learned - embracing uncertainty as a path to better solutions.

Collaboration

The best work happens at the intersection of disciplines. Facilitating workshops, bridging engineering and design, and building shared understanding across teams.

Leadership

Guiding teams through ambiguity, establishing design processes, and creating the conditions where great work can emerge. Design leadership is about enabling others.

Yedu Dev

Learning through building, failing, and simplifying what's complex.

I've spent that time learning how to navigate complexity, adapt quickly, and build with intent - largely focused on making systems easier to understand and use, while balancing business needs and user expectations.

Beyond product design, I've explored different paths early in my career - experimenting with building communication solutions, working on branding initiatives, and even attempting to create a community platform for filmmakers and reviewers. Not everything worked, but each experience shaped how I approach problems today - with curiosity, resilience, and a bias toward action.

I enjoy collaborating with people who challenge ideas and push for better outcomes. Whether it's mentoring designers, working closely with cross-functional teams, or refining workflows, I care about creating environments where good design can thrive.

Outside of work, travel plays a big role in how I see the world. I genuinely love exploring new places, experiencing different cultures, meeting people, and gaining fresh perspectives wherever I go. I've travelled to over a dozen countries so far, and I'm always looking for the next experience.

Get in touch

Talks & writing.

2025 Designing for trust in autonomous systems Talk
2024 Evidence-based design in complex domains Article
2023 The role of calm technology in modern interfaces Talk
2022 From research to product: bridging the gap Workshop
2021 Systems thinking for interaction designers Article
2019 Designing voice-first experiences Talk