GenAI Embed at NRF’26: How PaletteAI Is Elevating Retail Innovation

Retail is going through a major shift.

Shoppers are no longer satisfied with generic product grids and one-size-fits-all recommendations. Whether they are buying fashion, home, beauty, electronics, or lifestyle products, they expect retail experiences that are:

• Easy to navigate

• Relevant to their needs and context

• Consistent across web, app, and store

• Helpful without feeling overwhelming

Across the industry, the strongest trends are clear:

• More personalization and intent-aware discovery

• Stronger focus on curation and guidance instead of endless choice

• Faster launch cycles for campaigns and collections

• Smarter use of AI to support real business outcomes, not just experiments

At NRF 2026: Retail’s Big Show in New York, GenAI Embed is attending to showcase PaletteAI – a collection-led merchandising engine that responds directly to these trends. PaletteAI helps retailers turn large, complex catalogs into clear, guided shopping experiences that work across categories and channels.

We are demonstrating five high-value PaletteAI use cases that show how collections can improve the retail journey from discovery and engagement to purchase and post-purchase satisfaction.

If you lead ecommerce, merchandising, digital, or customer experience, PaletteAI is designed to help your teams move faster while giving shoppers a more intuitive way to explore and buy from your brand.

What Is PaletteAI and Why Does It Matter Now?

PaletteAI helps retailers move from SKU-first merchandising to story-first and context-first merchandising.

Instead of only listing products in long grids, PaletteAI helps you organize your catalog into meaningful collections that reflect how people actually shop across retail:

• Solutions for a specific need

• Ideas for a lifestyle or use case

• Curated sets for a mission or project

For example, a retailer can create collections such as:

• Back to work essentials

• Small space home upgrades

• Everyday self care

• Weekend outdoor plans

• Starter kits for new hobbies

These are not limited to a single vertical. The same engine can group apparel, accessories, home goods, electronics, beauty, and more, depending on your assortment.

This approach makes it easier for shoppers to:

• Understand what is relevant to them in the moment

• See products in context rather than in isolation

• Move from browsing to decision with less friction

At NRF 2026, we are focusing on five practical PaletteAI use cases that reflect what many retailers are prioritizing for 2026.

1. Narrative Buying and Curated Collections

Across retail, buyers are thinking less in terms of single products and more in terms of missions and stories:

• Getting ready for a new job

• Refreshing a living space

• Preparing for a trip

• Setting up a home office

• Improving a daily routine

Many ecommerce and omnichannel journeys still start with flat category pages that show items, but not outcomes.

PaletteAI helps retailers turn these journeys into narrative-led collections.

Teams can quickly create collections such as:

• New role, new workday setup

• Warm and welcoming living space

• Simple daily wellness kit

• On the go convenience essentials

Each collection is anchored in a clear purpose. Instead of making shoppers work through hundreds of SKUs, you present ready-to-shop combinations that feel clear, relevant, and helpful.

The impact:

• Shoppers move through guided experiences instead of random lists

• Retailers see stronger engagement and better use of their full catalog

• Digital channels look more like curated experiences and less like inventory dumps

2. Intelligent Clienteling and Customer Engagement

Clienteling and engagement are critical across retail formats – from fashion and home to specialty, beauty, and electronics.

Associates, digital stylists, and online support teams are constantly answering questions like:

• “What else would you recommend with this?”

• “Can you help me finish this setup?”

• “Is there a bundle or set that makes this easier?”

Without structured collections, answers depend on individual knowledge and manual searching.

PaletteAI gives clienteling and engagement teams instant access to curated collections that can be used in real time.

Teams can:

• Pull relevant collections while speaking with a shopper in-store or via chat

• Share collection links via email, SMS, or messaging as tailored suggestions

• Use PaletteAI sets as a starting point for one-to-one recommendations

This improves:

• Response speed and quality

• Consistency of recommendations across channels

• The perceived value of human and digital assistance

Customers experience guidance that feels prepared, not improvised.

3. Predictive Merchandising and Demand Foresight

Retailers today need to react faster to what customers are showing interest in, whether that signal comes from:

• Search behavior on the website

• Category and campaign performance

• Social trends and creator content

• Seasonal and regional patterns

Static merchandising structures often lag behind these signals.

PaletteAI helps keep collections aligned with what people are paying attention to right now.

Teams can:

• Refresh collections around themes that are trending in search and campaigns

• Create new collections that respond to rising interests

• Adjust product mixes within collections based on inventory and performance

Examples include:

• Highlighting comfort and value during economic pressure

• Prioritizing sustainable or low-impact products when that demand grows

• Tailoring collections for key cities or regions based on local behavior

PaletteAI gives retailers a practical way to connect merchandising strategy with live demand signals without rebuilding pages from scratch every time.

4. AI-Driven Storytelling and Content Creation

Content and marketing teams are under pressure to:

• Launch more campaigns

• Maintain brand consistency

• Personalize experiences by audience and region

• Avoid burning out creative and merchandising teams

Building every layout, story, and landing page from the ground up is slow and expensive.

PaletteAI gives content and marketing teams a structured foundation for channel-ready storytelling.

With PaletteAI, teams can:

• Start from curated collections that already make sense as a story

• Turn collections into homepage features, landing pages, and campaign modules

• Keep product, visuals, and copy aligned across web, email, and paid media

Instead of asking “What should we feature?”, teams start with “Which collections best support this campaign or audience?”

This reduces:

• Time from idea to live experience

• Repetition and manual page building

• Risk of disconnected or off-brand experiences

5. Post-Purchase Clarity and Return Reduction

Returns are a major topic across all retail categories. Many of them happen because expectations were not fully set:

• The product did not fit the shopper’s need or situation

• The item did not work as part of the setup they had in mind

• They missed a component or accessory that would have made it useful

PaletteAI helps customers understand context and use before they buy.

By showing products as part of clear collections and scenarios, retailers can:

• Set better expectations about how an item will be used

• Surface complementary products that prevent incomplete purchases

• Explain how a group of products works together to solve a specific need

This leads to:

• Better match between what customers expect and what they receive

• Lower rate of avoidable returns

• Stronger post-purchase satisfaction and trust

How PaletteAI Brings It All Together

Across these five use cases, PaletteAI acts as a shared engine for curated, story-led retail experiences.

It helps retailers:

• Build curated collections in minutes, not hours

• Create consistent product stories across site, app, email, and store

• Communicate seasonal and category direction clearly to teams and partners

• Give customers immediate clarity on what is relevant to them

• Reduce manual work for merchandising, clienteling, and content teams

In simple terms, PaletteAI helps transform retail from “manage the grid” to “design the journey”.

How PaletteAI Fits Into Modern Retail Tech Stacks

PaletteAI is designed to plug into your existing catalog and commerce stack, not replace it.

It can:

• Ingest your current catalog and product attributes

• Surface collection ideas aligned with inventory, strategy, and themes

• Let teams review, adjust, and approve collections in a controlled way

• Expose collections through APIs and components to power:

  • Category and landing pages

  • Collection hubs and campaign sections

  • “Shop this setup” or “Complete this journey” modules

  • Personalized experiences and outbound journeys

This makes PaletteAI a practical option for retailers running on modern platforms, headless architectures, or mixed legacy setups.

Visit GenAI Embed at NRF 2026 in New York

You can see all five PaletteAI use cases live at:

GenAI Embed at NRF 2026: Retail’s Big Show
Booth 2938, Level 1
Jacob K. Javits Center, New York City, USA
January 11 to 13, 2026

Our team will provide live walkthroughs of PaletteAI, showing how it supports:

• Merchandising and assortment presentation

• Clienteling and personalized customer guidance

• Content, campaign, and experience design for 2026 retail strategies

Bring your own categories, journeys, and challenges. We will be ready to explore how PaletteAI fits into your roadmap and stack.
Book a dedicated session with the GenAI Embed team at NRF 2026 to see PaletteAI mapped to your categories and KPIs.
Booking link:
https://outlook.office.com/book/NRF2026BoothVisitors@genaiembed.onmicrosoft.com/?ismsaljsauthenabled=true