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Redesigning how hotels manage guest experiences at scale

INTELITY · GEMS 2.0 · HOSPITALITY SAAS · 2025

Lead product designer, sole designer on the platform. Research through developer handoff, with Intelity's product and engineering teams. Via Tangerine.

Problem

Staff worked around GEMS instead of with it. WhatsApp instead of the messaging module, paper lists instead of automation. A trust problem, not a feature gap.

What I did

Audited all eight modules, ran a cross-team problem mapping session, built the design system first, then rebuilt module by module in order of operational impact.

Result

Daily active usage up 34%, around 46 FTE hours recovered every week, eight modules shipping from one system.

The call

Nexus AI could have been a flashy visual flow editor. I built a structured rules table instead. Demos reward novelty, daily use rewards familiarity.

Intelity GEMS 2.0 messaging module after the redesign
+34%daily active usage after rollout
46hweekly FTE hours recovered through automation
8core modules shipped on one design system

CONTEXT

A platform that had to think at hotel scale.

GEMS 2.0 is Intelity's operations platform, used daily by hotels around the world. Housekeeping, front desk, food and beverage and concierge all live in it: reservations, messaging, workflows, content and guest requests.

The product had accumulated complexity for years. Every new module had arrived with its own vocabulary and its own patterns. I joined through Tangerine as lead product designer, responsible for the core modules from research and wireframes through to high fidelity and handoff.

PROBLEM

Staff were working around the software, not with it.

Hotel operations do not stop. Staff need to act fast, often with a guest standing in front of them. The existing interface mixed too many concepts per screen, had no visual hierarchy, and no consistent component logic.

The result was workarounds. WhatsApp instead of the messaging module. Paper lists instead of the automation. That is not a missing feature. It is a trust problem, and you do not fix trust by shipping more surface.

So the brief I wrote for myself was not "add features". It was "make what already exists feel reliable enough that people actually use it".

INITIAL FINDINGS

I audited all eight modules before touching a single screen.

Mixed tasks per screenScreens combined monitoring, configuration and action, so staff had to read everything to do anything.

Inconsistent componentsThe same concept looked and behaved differently across modules, so learning one taught you nothing about the next.

No language for stateRequest states had no shared visual system, and staff compensated with phone calls and paper.

Database-shaped tablesLists mirrored the database instead of operational urgency, hiding whatever needed action right now.

Cross-team problem mapping board
Artifact. I facilitated a problem mapping session with engineering, product and design, and put every pain on one board. Grouping the notes by origin made the pattern obvious: three teams were describing the same problem from different angles. That board became the priority list for the whole redesign.

DESIGN PROCESS

System first, then module by module.

I started with the design system: tokens, input states, table patterns, status chips and modal flows. Defining the shared language first made every module after it faster and more consistent, and it is the reason eight modules could ship without drifting apart.

Then I moved through the modules in order of operational impact, from messaging and workflows to reservations, content, departments and integrations. Each one followed the same loop: wireframes against the audit findings, review with Intelity's product team, iteration, and a handoff doc with states and edge cases spelled out.

Two-quarter design and build roadmap
Artifact. To move eight modules without chaos I planned the work as quarterly themes, each design phase running ahead of a build phase with explicit buffers. Every block linked to its Figma file and its tickets, which kept design in front of engineering instead of blocking it.
Smart Dining before the redesign
BeforeEvery concept on one screen, no hierarchy, status buried inside rows.
Smart Dining after the redesign
AfterOrders grouped by state, status chips readable at a glance, one clear next action.

SMART DINING SHOWS THE APPROACH BEST: THE SAME DATA, RESTRUCTURED AROUND WHAT STAFF NEED FIRST

The staff platform is half of it. Guests see the other half.

GEMS runs the back of house, but the same content feeds what a guest touches in the room: the in room dining menu, housekeeping requests, the concierge. If the menu is a mess for staff, it is a mess for the guest thirty seconds later.

So I designed the guest surfaces against the same system. Same components, same state language, same ordering logic, sized for a tablet in the room and a phone in a pocket.

In Room Dining menu shown on a room tablet and on a guest phone, with dish cards and an order button on each

THE SAME MENU DATA, RENDERED FOR THE ROOM TABLET, THE GUEST PHONE AND THE STAFF QUEUE

THE DECISION

Two ways to build Nexus AI. Try both.

Hotel managers automate operations with rules: when something happens, and a condition is true, then do this. Nexus AI is where they write them.

We had two directions. A visual flow editor with cards, which demoed beautifully to investors and buyers. Or a structured rules table with conditions in rows, which mapped to how managers already write procedures on paper.

I could not settle it from a mockup, so I built both and put them in front of the team. Edit a rule. Toggle one off. Switch views. Then ask which one you would rather use fifty times a day.

I shipped the table, and kept the card view as a secondary review layer. Demos reward novelty. Daily use rewards familiarity.

NEXUS AI · AUTOMATION BUILDER
When Condition Then Active

LIVE COMPONENT · EVERY CONTROL WORKS

The shipped ticket assignment workflow builder, with an initial trigger followed by two actions and a configuration panel on the right
Shipped. The ticket assignment builder that came out of that decision. The rule reads top to bottom like a written procedure, the connectors between steps are spelled out, and configuration lives in a side panel instead of on the canvas. Nexus AI sits one pill away for anyone who would rather describe the rule than build it.

OUTCOME

Staff came back to the platform.

After the redesign rolled out, daily active usage rose 34% and the automation recovered roughly 46 FTE hours a week that staff had been spending on manual coordination. Eight modules now ship from a single design system, which cut design and build time for everything that came after.

The number I care about most is the first one. It means people stopped reaching for WhatsApp.

Go where the work happensI would push for a hotel floor observation session in week one. Seeing the pace, the noise and the handoffs would have sharpened every decision about information density earlier than spec documents did.

Generate state variants fasterEight modules meant hundreds of screens per state, and I built them by hand in Figma. Today I would generate the variant sets from a state matrix and spend the time saved on hierarchy and edge cases.

Stress test with real dataI would run long hotel names, oversold dates and extreme queue volumes through every layout before handoff, instead of discovering the breaks in staging.

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