Arteli Select

Details

Summary

Designed and shipped a working prototype for Arteli Select. Built for retail leads and category managers. It helped them move quicker, with better clarity on store planning and assortment calls.
Getting alignment wasn’t always easy. Fast feedback and visible progress kept us on track. Regular prototypes made the work real.
Final handoff included a live prototype, reusable UI patterns, and a solid design system the team could scale.

What is Arteli Select?

Arteli Select is an AI tool for retail teams. It answers key questions for category managers: what products to sell, where to sell them, and what changes will drive the most value.

Business Problem
Retail teams were stuck juggling huge data sets in old-school tools. They needed something that worked like they do. The goal: prove AI could help without creating extra work or noise. without adding more noise.

Design Process

Research Actions

We moved fast. Got a live demo in front of people early. That sparked real conversations. But some held back. The more helpful the AI was, the more it felt like a threat. So we focused on what they did. Clicks, skips, returns. What they used told us what mattered.

Process Overview

Started with interviews and audits. Found gaps fast. Sketched flows and tested early. Added UI patterns and a broader color palette. Built a small system to keep things moving. The demo pulled it all together and made the work feel real.

Move Fast & Show Work

We agreed on a few core principles early. They helped with tradeoffs later. Then we moved. Built fast. Shared often. Real feedback came quick. We kept updating flows, labels, and layouts. Each pass made things easier across product, data, and design.

Arteli Experience Design Principles

It’s science but it feels like magic.
We set the scene--we produce extraordinary results; we explain bits of the science; but our solutions feel like magic, as if you’re using AI for your business.

Right not rushed.
Some things take time. We take the time to get it right; but we’re speedy on everything simple.

Serious about business.
The work day often has stressful moments, we get out of the way and don’t draw attention to ourselves as the customer uses our tools to transform their business.

Crafted as only artists can.
Pixels interstitials they all matter.

The Work That Made It Real

The demo hit. The team asked to scale it to 100 stores. I rebuilt the store picker with grouped accordions and search to speed things up. We cleaned up how impact showed up. No vague numbers. Tooltips helped explain trends.

Recommendations Tab
Grouped AI suggestions by type. Each showed margin, sales, and store fit.

Action Set Summary
Tracked store actions in real time. Visual cues flagged things like locked inventory or low margin.

Business Monitor & Rules View
Side panel with all the controls. Clear thresholds. Easy to adjust. No digging.

Dashboard view by store and category

Biweekly category recommendations

Category-specific recommendation set

Side sheet for rules and alerts

Build, review, and send actions

Documenting Research

Persona
Olivia is a Retail Assortment Manager. She’s responsible for the product mix across digital and physical stores. She makes the call on what to stock, but her decisions are reviewed by leadership. They expect clear, data-backed reasoning. She needs tools that support speed and accuracy, not more busywork.

Arteli Demo

Our first demo was built to spark discussion. We wanted users and their leadership to picture themselves using it in their daily work. It helped us gauge what felt useful, what caused hesitation, and what needed to change. Their reactions gave us just enough to confirm the direction and keep improving the details.

Just enter your email and go.

See what recommendations or search for a product fast.

Click a row to open the side panel.

Select your view of stores and categories.

Provide feedback and access technical support.

Learnings

We didn’t align early on terms like “action set” which led to confusion. The demo helped fill the gaps. It made the work real and gave the team something clear to respond to. Walking through the live product brought out more useful client feedback than any slide deck.

Reflections

What worked well.

Iterative prototypes helped the team stay focused
Regular feedback from stakeholders kept the team on-track
The demo helped the client see how the product could work in their world

What didn't work.

Product and dev leads had different priorities. I filled the gaps where I could
Product and dev leads weren’t always aligned. I kept things moving with validated solutions
Team shifts slowed progress. I designed clear patterns, documentation, and flows so the team didn't lose velocity

Results

I delivered a series of iterative prototypes that helped the team collaboratively shape an early direction of Arteli Select.

The demo made abstract ideas real. It gave the team a clear view of how retail teams could use AI to support product decisions across stores. It helped align business, design, and engineering around what mattered.

The design work surfaced gaps in the data model, clarified key flows, and gave the team a solid starting point for future development. The patterns, layouts, and feedback from real demos helped carry the work forward.

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