Bonrix AI/ML Business Solution: Transforming Shopping Through Intelligent Search

Bonrix AI/ML Business Solution: Transforming Shopping Through Intelligent Search

Bonrix AI/ML Business Solution: Transforming Shopping Through Intelligent Search

At Bonrix Software Systems, Ahmedabad, Gujarat (India), we focus on building applied Artificial Intelligence solutions that solve real-world business challenges. Our mission is to identify areas where AI provides more accurate, efficient, and scalable solutions than traditional programming approaches.

Under our Business AI/ML Application Initiative, we are proud to introduce our latest innovation:
Image-to-Image Catalog Search and AI-Driven Product Discovery for E-Commerce and Retail.
This solution transforms how customers and sales teams search, discover, and interact with products in both online e-commerce platforms and offline retail environments.

1. Image-to-Image Catalog Search
Customers can take a photo with their mobile camera or upload any image, and our AI system will instantly search the catalog for visually similar products.
• For jewelry stores: helps match patterns, metals (gold, silver, rose gold), and design variants.
• For fashion retailers: finds clothes by design, fabric, or color variations.
• For offline store staff: enables quick product recommendations by comparing customer preferences with in-store inventory.
This delivers a seamless and intuitive shopping experience that goes beyond traditional keyword search.

2. Text-Based Search
Shoppers can also search by description or keywords.
• Typing “modern diamond necklace in rose gold” will instantly bring up visually and semantically relevant catalog items.
• AI interprets natural language queries to match visual styles, product categories, and attributes.
This is equally valuable for online marketplaces, fashion studios, and jewelry galleries, making product discovery smarter and faster.

3. Hybrid Search (Image + Text)
Our platform allows combined search — a reference image with additional text.
• Example: A customer uploads a photo of a ring and types “show me similar designs but in silver with emerald stones.”
• The hybrid search filters results using both visual similarity and textual context, ensuring refined and precise recommendations.

4. Advanced Textual Prompt Search (Positive + Negative Filters)
Customers can search using positive and negative prompts:
• “I want a vintage-style necklace with diamonds but without pearls.”
• The AI intelligently excludes items that match the negative attributes while prioritizing positive characteristics.
This gives customers greater control over their shopping experience and helps them find exactly what they want.

5. Keyword & Attribute Identification
Our AI can automatically analyze an uploaded image and identify its attributes in keyword form:
• Jewelry: gold, rose gold, ring, necklace, diamond, vintage, modern.
• Fashion: casual, formal, silk, denim, floral pattern.
• Furniture: wooden, leather, modern, minimal, sofa, chair.
We maintain industry-specific keyword taxonomies to ensure precision.
Customers can also modify attributes (e.g., change gold to rose gold) and ask AI to generate new variations or designs, opening doors to customized product creation.

6. AI-Assisted Design from Sketches
Customers and designers can start with a rough sketch or existing product image and let AI generate professional, real-world designs.
• Furniture: Sketch a sofa layout and transform it into realistic images with chosen fabric, color, or style.
• Jewelry: Upload a ring sketch and convert it into photo-realistic renders with different materials or gemstones.
• Fashion: Modify existing clothing styles with new cuts, colors, or fabrics.
This feature supports custom orders and enables rapid design prototyping for retailers and manufacturers.

7. Virtual Try-On & Model Application
We integrate AI-based try-on experiences:
• Fashion retailers: Apply outfits on a customer’s photo or a digital model.
• Jewelry stores: Place rings, necklaces, or earrings on a customer image to preview fit and look.
• Furniture retailers: Place a sofa or chair inside a photo of the customer’s living room to preview design and space fit.
This feature reduces return rates, builds customer confidence, and generates professional marketing imagery for online stores.

8. AI-Generated Galleries & Showcases
Our platform also curates AI-generated galleries:
• Showcase how outfits, jewelry, or furniture look when tried by different customers or placed in different environments.
• Collect creative AI-generated variations to inspire customers with new design ideas.
• Enable visual storytelling for brands by showing how products integrate into real lifestyles.
This creates an engaging catalog experience that goes beyond traditional static product listings.

Business Impact
• For Customers: A smarter, faster, and more personalized way to shop.
• For Retailers: Improved customer engagement, reduced decision fatigue, and higher conversion rates.
• For Designers: AI-driven customization and rapid prototyping open new opportunities for bespoke products.
• For E-Commerce Platforms: A competitive edge through advanced AI/ML search and discovery features.

✅ With Bonrix Software Systems’ Image-to-Image Catalog Search, we are shaping the future of applied AI in retail, fashion, jewelry, and furniture industries — where every customer finds exactly what they imagine.

Bonrix AI/ML Business Solution: Transforming Shopping Through Intelligent Search

     Screenshots For Bonrix AI/ML Business Solution

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Videos and Details For Bonrix AI/ML Business Solution

Jewelry Image Search and Background Removal Demonstration

Description: This video demonstrates how to use a "Jewelry Image Search" tool to find similar jewelry items from an uploaded image. Initially, an image of a ring on a hand is uploaded, and a processing step, labeled "Qwen," removes the background to isolate the ring. The user then adjusts search parameters like the number of results and search accuracy before initiating a search for similar images. The tool displays a grid of rings that match the uploaded item, and the user can click on any result to view more details, including an option to perform a further similar image search based on that specific result.


Jewelry Text Search and Similar Item Discovery

Description: This video showcases the text search functionality of a jewelry search tool. The user demonstrates typing "rng" into the search bar, utilizes a spell check feature to correct it to "ring", and then executes a text-based search. After browsing the initial results, the user selects a specific ring and performs a subsequent search to find more similar items, illustrating an iterative approach to discovering desired jewelry pieces.

Hybrid Search in Action: Fast, Accurate Jewelry Matching (Image + Text)

Description: This video showcases your hybrid search workflow: choose a catalog, submit a query (drop an image or type “rose-gold solitaire ring”), and watch results blend visual similarity (embeddings) with keyword/BM25 matching—re-ranked by adjustable weights. You’ll see filters (metal, stone, price) refine results in real time, confidence scores and SKUs on each match, and quick drill-downs to product details. Behind the scenes, vector hits, lexical terms, and metadata boosts (brand/collection) are fused for precise, explainable results. The demo closes with saving/exporting matches and peeking at analytics to track top queries and hit rates.


Keyword Search in Action: Fast Jewelry Lookup by Names, Tags & Filters

Description: This video focuses on keyword (lexical) search in your Jewelry app: you type terms like “rose gold solitaire ring,” use autocomplete and suggestions, and apply filters (metal, stone, price, collection) to narrow results. The grid/list updates instantly with product thumbnails, SKUs, titles, and prices, and you can sort by relevance or price, open a product to view details, and copy the SKU. It also shows exact-match vs. partial-match behavior (phrases, AND/OR terms), synonyms/stemming for common jewelry terms, and quick refinements via facets. Finally, you save or export the filtered set for merchandising or client sharing—demonstrating fast, precise text-based discovery without needing an image.

Apply Jewelry to Image: Smart Virtual Try-On for Instant Mockups

Description: This video shows the virtual try-on flow: upload a model or customer photo, then pick a ring/earring/necklace from your catalog to “apply” onto the image. The system auto-detects landmarks (ear, finger, neckline) to snap the piece into place; you can fine-tune with drag, rotate, and scale, toggle left/right ear or finger, and adjust depth, shadow, and shine so it looks realistic. Try multiple variants (metal color, stone shape/size), compare before/after, and switch backgrounds if needed. When you’re happy, save the mockup to the project/design board or export a PNG/JPG for sharing (e.g., WhatsApp) or posting—ideal for quick client approvals and merchandising previews.

AI Jewelry Design Studio: Generate & Refine Concepts from Prompts or References

Description: This video shows the AI Design flow end-to-end: enter a style prompt (e.g., “rose-gold halo ring with marquise diamond”), optionally upload a reference sketch/photo, pick presets (metal, stone shape, band style), and set variant count. The system generates multiple concepts, then you refine—swap metals/stones, tweak details with prompt edits, and use “variations” to explore alternatives. You can zoom into a design, compare side-by-side, favorite the best, and upscale for a clean mockup. Finally, it saves the result to your Designs library and lets you export images/spec sheets for sharing with clients or handing off to CAD.

Positive/Negative Search: Include & Exclude Signals for Sharper Jewelry Matches

Description: This video demonstrates refining results with positive (must-have) and negative (must-not) signals. You add positives like “rose gold,” “solitaire,” or an image crop to boost similar pieces, and apply negatives like “two-tone,” “cluster,” or “oval” to suppress mismatches. The UI shows +/− chips, quick facet filters (metal, stone, price), and a weight slider to control how strongly signals re-rank the grid. You’ll see instant updates with thumbnails, SKUs, and confidence scores; open details to verify attributes; combine text + image cues; and finally save/export the tuned query as a reusable search profile for merchandising.


Image History: Searches

Description: This page is a centralized gallery of all AI-generated images—cleanly organized for quick browsing, with simple options to search, filter, and download the visuals you need.

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