Vivrelle Debuts Ella AI Stylist Across Revolve and FWRD

Vivrelle announced Ella, a new AI personal-styling tool that recommends outfits across Vivrelle, Revolve, and FWRD, letting members rent, buy, or mix and match items with a single checkout on Vivrelle.

Built in about a year, Ella accepts natural-language prompts like “a bachelorette weekend outfit” or “what to pack for a trip,” searches inventories across all three retailers, and returns coordinated looks that can be rented, bought new, or picked pre-owned.

This launch follows an earlier joint tool, Complete the Look, and marks one of the first examples where three retailers integrated to offer a single personalized AI experience that spans rental, resale, and retail.

Why Ella matters

Ella is more than a chatbot-style stylist. It attempts to remove friction across three commerce models and address longstanding fashion problems: decision fatigue, fragmented inventory, and the friction of combining rentals or resale with retail shopping.

• Faster outfit discovery—users get curated looks instead of searching multiple sites.
• Unified commerce—rent, buy new, or shop pre-owned with one cart and clearer purchase decisions.
• Personalization that improves—Ella learns from interactions to refine recommendations over time.

Practical challenges behind the scenes

Delivering a smooth omnichannel AI stylist requires more than a strong model. Teams must tackle product-taxonomy alignment, real-time inventory syncing, unified pricing and return policies, and privacy-conscious user data handling. Handing off a recommendation from an AI to a functioning cart across three platforms is an integration and UX problem as much as an AI one.

• Inventory normalization—matching SKUs and attributes across retail, resale, and rental catalogs.
• Evaluation and metrics—A/B tests measuring conversion lift, rental uptake, and member retention.
• Privacy and consent—personalization that respects membership data and regulatory requirements.

How organizations should think about this

If you run a brand, marketplace, or membership program, Ella is a useful case study in bridging multiple commerce models with AI. Start by scoping the product experience, not just the model: which user intents will you support, how will you measure success, and where must inventory and checkout systems align?

• Define priority intents—packing lists, event looks, and last-minute add-ons are high-value, high-clarity prompts.
• Align catalogs and attributes so recommendations map cleanly to checkout actions.
• Instrument experiments that track conversion lift, rental vs. buy decisions, and changes in member lifetime value.

Ella shows where AI in fashion can go: from a novelty stylist to a true commerce layer that reduces friction and connects multiple supply models. Expect more partnerships that blur the lines between renting, buying new, and reselling as companies chase higher value per customer with smarter recommendations.

For product and tech leaders, the lesson is clear: personalization needs operational muscle behind it. Ella is a reminder that the competitive edge comes from coupling strong AI with tight integrations, clear metrics, and a membership-first product mindset.