AI is the foundation of Relewise
Relewise delivers personalization and relevance at scale using advanced, real-time machine learning algorithms. Whether it’s responding to a new product launch, a shifting trend, or a changing customer journey, AI recalibrates rankings and suggestions as it learns more about your shoppers.
With this self-learning approach, you no longer need brittle if-then logic, keeping your system automatically aligned with customer expectations.

Predictive search
Relewise’s predictive search shows real-time query suggestions and autocomplete results that adapt as users type, with context-aware completions delivered in milliseconds. Results are ranked by click-through and purchase likelihood, giving shoppers faster, smarter paths to what they’re actually looking for. This feature reduces friction in product discovery, helping both B2B and B2C customers quickly find relevant items and decreasing bounce rates.

AI-powered recommendations
Relewise uses trend- and seasonality-aware algorithms to serve relevant products automatically, across every channel. Each recommendation blends real-time signals, historical behavior, and global trends without any need for rule-tweaking. Merchants can fine-tune the balance between popularity and purchase frequency without writing a single line of logic.
For B2C, this powers everything from mixed product-and-content carousels to trending picks and cross-sell accessories, driving more engagement and conversions.

Real-time predictive personalization
Relewise runs in the background, predicting what each shopper is likely to want next. It blends live behavior, historical patterns, and global trends to surface the right product before the user even starts searching. The result is timely, relevant recommendations that boost conversions and basket size without adding more work for your team.

Fully automated self-learning engine
Relewise’s AI engine refines itself continuously, learning from every click, cart addition, and purchase in real time. There’s no need for merchandisers to retrain the model or adjust rules manually. Relewise instantly adapts to emerging trends, seasonality shifts, and customer behavior changes without downtime. For you, it means achieving market-leading personalization, reducing manual overhead and operational complexity, and freeing your teams to focus on strategy and growth instead of daily optimization.

Adaptive intent recognition
Relewise instantly understands not just what your shoppers are looking for, but why they’re looking. It adapts search results and recommendations based on contextual clues like current session signals, previous purchases, category interest, and inventory availability, ensuring each result precisely matches their shopping intent. Each shopper sees the right product faster, leading to quicker decisions and fewer missed sales.

NLP-enhanced search
Relewise incorporates Natural Language Processing (NLP) to handle the messy reality of real-world search. Built-in stemming, compound-word splitting, and synonym matching ensure that even misspelled or oddly phrased queries still return accurate results. This particularly benefits brands operating across multilingual markets, enhancing customer satisfaction by delivering precise results regardless of query variations.
What are the steps involved to get Relewise on your site?
Turn the pages in the carousel below to see a simple overview of the six steps you’ll take with our team to implement Relewise on your site.
1. Getting in touch
2. Getting to know you
3. Exploring your potential
4. Planning with partners
5. Signing contracts and onboarding
6. Optimizing and ensuring efficiency
Want to get technical?
Cross-segment intelligence
Learns from both cohort-level trends and individual patterns across business and consumer verticals.
Account-based logic
Supports custom price lists, availability rules, and segmentation for B2B portals.
Session-specific personalization
Recognizes anonymous, new, or returning users and tailors output accordingly.
Behavioral ranking
Search results are re-ordered using learning-to-rank models that blend click history, preferences, and session data.
NLP & typo tolerance
Built-in stemming, synonym expansion, and typo correction enhance recall without sacrificing precision.
Unified indexing
Supports multilingual, multi-catalog, and facet-aware queries via a single API call.
20+ built-in strategies
Includes "view-to-buy", "frequently bought together", and more, all dynamically selected.
Real-time graph updating
Relevance scores adjust on-the-fly based on current user behavior and global trends.
Omnichannel output
Recommendations can be deployed via web, app, email, or in-store displays using a unified API.
Predictive scoring engine
Every ad slot is ranked based on real-time likelihood of interaction.
Cohort-aware targeting
Ads adapt to shopper type, past behavior, and seasonal trends.
Business Rules with AI
Combine promotional logic (e.g. boost margins, exclude out-of-stock) with automatic optimization.
Self-adjusting rankings
Co-view networks, popularity curves, and purchase recency update product scores in near real time.
Cold start handling
New products gain exposure quickly as they gather interaction signals.
Merchandiser control
Schedule rules, override, boost, or pin items easily using intuitive UI controls.
Put AI in charge of your personalization today.
Book an online chat with one of our experts today. You’ll tell us about your business, and together we’ll explore how AI can help you reach your personalization potential.
