About
ViSearch, developed by ViSenze, is a cutting-edge AI commerce search and discovery platform purpose-built for retailers and ecommerce brands. At its core is Multi-Search, which allows shoppers to find products using natural language, keywords, images, or any combination in a single query — removing the limitations of traditional keyword-only search and reducing lost sales from poor discovery. The platform's AI Recommendation Engine surfaces contextually relevant products at the right moment in the shopping journey, with support for visually similar suggestions, pairing recommendations, and 'Shop the Look' features. An intuitive AI Shopping Assistant enables customers to describe what they want conversationally and receive tailored product suggestions. ViSearch also features GenAI Smart Tagging, which automatically applies accurate, AI-generated tags to products at scale — enriching catalog data and improving searchability without manual effort. The Experience Studio gives merchandising teams the ability to customize search and discovery layouts, trigger image-based searches, and connect recommendations from lookbooks, UGC, and social media. Built-in Analytics provides actionable insights into customer journeys, demand signals, conversion funnels, and trending styles, helping teams continuously optimize performance. With over a decade of AI training on hundreds of millions of commerce products and integrated support for the latest LLMs, ViSearch is ideal for enterprise retailers seeking smarter, scalable search solutions.
Key Features
- Multi-Search: Allows shoppers to search using natural language, keywords, images, or any combination in a single query, enabling smarter and more intuitive product discovery.
- AI Recommendations Engine: Surfaces personalized product suggestions including visually similar items, pairing recommendations, and 'Shop the Look' collections based on individual shopper preferences.
- GenAI Smart Tagging: Automatically applies AI-generated, contextually accurate tags to products at scale, enriching catalog data and improving searchability without manual effort.
- Experience Studio: A no-code customization tool for building tailored search and discovery experiences, including lens-based search, conversational shopping assistants, and social commerce integrations.
- Commerce Analytics: Provides actionable data on customer behavior, emerging trends, conversion funnels, and demand signals to continuously optimize the online shopping experience.
Use Cases
- Fashion and apparel retailers enabling customers to search by uploading outfit photos or screenshots to find visually similar products.
- Large ecommerce platforms automatically enriching product catalogs with AI-generated tags to reduce manual data entry and improve search accuracy.
- Online stores delivering hyper-personalized product recommendations based on browsing history, visual preferences, and real-time shopper queries.
- Retailers making their social media content shoppable by allowing customers to click on posts and discover matching products instantly.
- Merchandising teams using the Experience Studio to customize search experiences, including conversational AI shopping assistants and lookbook-based discovery.
Pros
- True Multimodal Search: Combines text, image, and visual inputs in a single query, significantly improving product discoverability compared to keyword-only solutions.
- Decade of AI Training: The AI engine has been trained on hundreds of millions of commerce products over 10+ years, delivering highly accurate and relevant results out of the box.
- End-to-End Platform: Covers search, recommendations, tagging, and analytics in one unified platform, reducing the need for multiple point solutions.
- Enterprise Scalability: Designed to handle large, multi-catalog deployments with peak traffic performance and 24/7 global support.
Cons
- Enterprise-Only Pricing: The platform is geared toward large retailers and requires a sales demo to get started, making it inaccessible for small businesses or startups.
- No Self-Serve Onboarding: There is no free trial or instant sign-up; all onboarding goes through a demo request and a sales process, which may slow adoption.
- Implementation Complexity: Full deployment and customization may require dedicated technical resources, especially for integrating across large or complex catalog infrastructures.
Frequently Asked Questions
What is ViSearch and who is it for?
ViSearch is an AI-powered commerce search and discovery platform by ViSenze, designed for mid-to-large ecommerce retailers and brands that want to improve product findability, personalization, and conversion rates.
What types of search does ViSearch support?
ViSearch supports keyword-based text search, natural language search, visual image search, similar product search, and social search — all combinable in a single 'Multi-Search' query.
How does GenAI Smart Tagging work?
ViSearch's GenAI Smart Tagging uses advanced AI and machine learning to automatically generate and apply relevant product tags at scale. This enriches catalog data, improves searchability, and ensures products are surfaced based on shopper intent and trending styles.
Can ViSearch integrate with social media and UGC content?
Yes. ViSearch supports social search, making social media posts shoppable in one click. The Experience Studio also enables recommendations from lookbooks, user-generated content (UGC), and social media feeds.
How does the analytics feature help retailers?
ViSearch's analytics module tracks customer activity across the shopping funnel, identifies demand trends, highlights catalog gaps, and provides attribution insights — enabling continuous improvement of the search and discovery experience.
