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Go Exceed2023 · 6 months

Go Exceed — Solve(X) Mobility Platform

Took a cluttered enterprise tool and turned it into an intelligent product — new modules, simplified workflows, and AI woven into every decision point.

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Avg Cost Savings

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Less Manual Work

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Redesign to Shipped

Product RedesignEnterprise UXAI IntegrationInformation ArchitectureDesign System
Go Exceed — Solve(X) Mobility Platform — product screen

Client

Go Exceed

Year

2023

Role

Product Strategy & Design Lead

Duration

6 months

The Brief

01

The Story Behind It

The Situation

Go Exceed had a Solve(X) platform that worked — technically. But enterprise customers needed training to use it, still built their own spreadsheets, and barely touched the AI.

What We Did

Over 6 months I evolved Solve(X) from a data-heavy internal tool into a coherent enterprise product — auditing what was overbuilt, designing entirely new modules, and integrating AI at the moment of decision.

What Changed

35% average cost reduction. 60% less manual effort. Full device visibility for the first time. Enterprise customers adopted it without a single training session.

CapabilitiesProduct RedesignEnterprise UXAI IntegrationInformation ArchitectureDesign System

What Drove It

02

Research & Design Bets

What the research showed, and the bets we made in response.

What We Found

Savings don’t land unless they’re legible

The AI engine was already finding 30-40% savings — but the old interface buried results in CSV exports. The redesign needed to make every saving traceable and actionable — current cost, optimised cost, and exactly what changed — right inside the product.

Duplicate plans were the hidden cost killer

Across every enterprise account, duplicate and unrecognised rate plans silently inflated spend. The product needed a dedicated surface to detect, compare, and resolve these before optimisation could even begin.

Asset management is a trust problem, not a tracking problem

Mobility managers didn’t distrust their inventory count — they distrusted the status. Is this device deployed? Returned? In repair? The product needed real-time status as a first-class surface, not a column in a table.

The Bets We Made

Optimizer as the hero surface, not a report

Situation

The AI engine ran in the background, but optimisation results were dumped as raw data exports — mobility managers rebuilt comparisons in Excel and presented findings manually.

The Bet

Design the Optimizer as a live, interactive surface — table-driven with inline saving analysis, comparison flyouts, and direct action paths — not a static report.

The Payoff

Mobility managers acted on optimisation recommendations in the same session — replacing a multi-day manual workflow with a single-surface triage process.

Duplicate and unmapped plans as a pre-optimisation gate

Situation

The platform had no way to handle dirty data — duplicates and unmapped plans silently degraded AI accuracy. Users didn’t know the problem existed until results made no sense.

The Bet

Surface duplicate plans, unmapped plans, and unrecognised codes as explicit pre-optimisation steps with dedicated resolution flows — not hidden warnings.

The Payoff

Customers resolved data hygiene issues in the first session instead of discovering them weeks later when savings didn’t materialise.

Asset status as a first-class surface, not a table column

Situation

The old platform’s asset tracking was a flat, overloaded table — status was just another column buried among dozens of others.

The Bet

Elevate asset status to a filterable, first-class surface with inventory count by status at the page level, bulk status changes, and a structured details flow for every device.

The Payoff

Device recovery time dropped from an average of 45 days to under 30 days post-offboarding.

The Structure

03

Architecture & Core Primitives

Architecture defined before a single screen was drawn — structure shapes behaviour.

Information Architecture

Core Primitives

The Work

04

Screens That Shaped the Product

Every screen below was driven by a research insight — here's the decision chain from problem to pixel.

AI Rate Plan Optimizer

Screen 01 / 04

AI Rate Plan Optimizer

AI savings were buried in CSV exports — mobility managers rebuilt comparisons in Excel and presented findings manually.

The Design Decision

The core intelligence surface — ingests carrier data, runs AI optimisation per account, surfaces savings with full cost comparison and one-click action paths.

Mobility managers acted on recommendations in the same session, replacing a multi-day manual workflow.

Duplicate & Unmapped Plan Resolution

Screen 02 / 04

Duplicate & Unmapped Plan Resolution

Dirty data silently degraded AI accuracy — duplicates and unmapped plans caused savings projections to be unreliable.

The Design Decision

Dedicated pre-optimisation flows for detecting and resolving duplicate rate plans and unrecognised codes before the AI engine runs.

Customers resolved data hygiene issues in the first session instead of discovering them weeks later.

Smart Asset Management

Screen 03 / 04

Smart Asset Management

Device tracking was a flat, overloaded table — coordinators couldn’t get a read on what was deployed, returned, or missing.

The Design Decision

Unified device inventory with real-time status, IMEI/serial tracking, manufacturer filtering, and a structured details flow for every device in the fleet.

Device recovery time dropped from 45 days to under 30 days post-offboarding.

Enterprise Account Hierarchy

Screen 04 / 04

Enterprise Account Hierarchy

Organisation hierarchy was flat — every account at the same level, no inheritance, no bulk operations that scaled.

The Design Decision

Organisation → Account → User structure with cascading defaults, role-based access, and bulk operations that scale from 500-line SMBs to 50,000-line enterprises.

Enterprise customers adopted the platform without a single training session after account hierarchy was introduced.

The Outcome

Results That Proved the Thesis

01 / 04

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Wireless Cost Reduction

Average cost savings across enterprise accounts

02 / 04

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Manual Effort

Reduction in manual optimisation and tracking work

03 / 04

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Asset Visibility

Full device lifecycle visibility from procurement to retirement

04 / 04

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Time to Insight

Average time from deployment to first optimisation savings

Rahul didn’t just hand us screens — he spent weeks understanding telecom expense management inside-out, and it showed. He pushed back on our own assumptions about workflows we’d lived with for years, and every time he was right. Working with him felt less like hiring a designer and more like adding a product co-founder. The platform he shaped is the first tool our enterprise clients actually adopt without a single training session.

VP of Product

Go Exceed

Before We Go

06

What This Project Taught Us

Key Learnings

  • Redesigning an existing product is harder than building from scratch — you’re fighting ingrained patterns, existing user habits, and the temptation to just reskin what’s there. The real work was deciding what to kill, what to simplify, and what to build new.

  • Integrating AI into a product isn’t about adding a ‘smart’ feature — it’s about making intelligence visible at the exact moment a user needs to make a decision. The AI engine was already powerful; my job was to surface that power in context, not behind a button.

  • Enterprise products need hierarchy as a first-class design surface. The old platform treated every account as flat. The moment I introduced org-level defaults with cascading inheritance, onboarding time collapsed and the product finally scaled.

Let’s Collaborate

Enterprise tool that nobody actually uses?

We audit what’s overbuilt, redesign the core workflows, and integrate AI at the moment of decision — turning a platform people tolerate into one they adopt.

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