Also known as: Glisten
Glisten AI automatically categorizes and tags e-commerce product data using computer vision and natural language processing.
E-commerce retailers struggle to manage large product catalogs with consistent, accurate, and searchable product data. Manual tagging and data entry processes are time-consuming and error-prone, preventing effective product search, filtering, and discovery.
E-commerce retailers struggle to manage large product catalogs with consistent, accurate, and searchable product data. Manual tagging and data entry processes are time-consuming and error-prone, preventing effective product search, filtering, and discovery.
Glisten AI uses computer vision and natural language processing to automatically extract, classify, and standardize product attributes from images and descriptions, enabling retailers to taxonomize millions of products efficiently.
Glisten AI uses computer vision and natural language processing to automatically extract, classify, and standardize product attributes from images and descriptions, enabling retailers to taxonomize millions of products efficiently.
Company status marked as inactive on Y Combinator as of available records.
Company status marked as inactive on Y Combinator as of available records.
Glisten AI is an artificial intelligence platform designed to transform unstructured product information into standardized, machine-readable data for e-commerce and retail businesses. Founded in 2019 and based in San Francisco, California, the company specializes in automating the process of product data enrichment, cleaning, and standardization across large product catalogs.
E-commerce retailers and marketplaces face significant challenges managing product data at scale. Product information is often inconsistent, incomplete, or poorly structured across different sources and platforms. Manual data entry and tagging processes are time-consuming and error-prone, requiring teams to spend countless hours copying and pasting product attributes into standardized fields. This inefficiency becomes exponentially worse for retailers managing thousands of products, each with multiple images and descriptions, especially when new inventory arrives regularly. Poor product data directly impacts search functionality, filtering capabilities, and customer discovery, ultimately affecting sales and user experience.
Glisten AI is an artificial intelligence platform designed to transform unstructured product information into standardized, machine-readable data for e-commerce and retail businesses. Founded in 2019 and based in San Francisco, California, the company specializes in automating the process of product data enrichment, cleaning, and standardization across large product catalogs.
E-commerce retailers and marketplaces face significant challenges managing product data at scale. Product information is often inconsistent, incomplete, or poorly structured across different sources and platforms. Manual data entry and tagging processes are time-consuming and error-prone, requiring teams to spend countless hours copying and pasting product attributes into standardized fields. This inefficiency becomes exponentially worse for retailers managing thousands of products, each with multiple images and descriptions, especially when new inventory arrives regularly. Poor product data directly impacts search functionality, filtering capabilities, and customer discovery, ultimately affecting sales and user experience.
Total Raised: $150,000
Last Round: Seed round of $150,000 raised approximately 5 years ago
Total Raised: $150,000
Last Round: Seed round of $150,000 raised approximately 5 years ago
Business-to-business software as a service for e-commerce retailers and marketplaces
Business-to-business software as a service for e-commerce retailers and marketplaces
E-commerce retailers, online marketplaces, and brands managing large product catalogs
E-commerce retailers, online marketplaces, and brands managing large product catalogs
Company marked inactive on Y Combinator; no recent activity signals available.
Hiring: unknown
Company marked inactive on Y Combinator; no recent activity signals available.
Hiring: unknown
Glisten AI addresses this challenge through an automated approach combining computer vision and natural language processing technologies. The platform analyzes product images and descriptions to automatically extract and classify relevant product attributes. Rather than relying on generic computer vision algorithms, Glisten's system is context-aware and trained on a growing library of approximately 11 million product images paired with corresponding descriptions. The platform uses natural language processing to parse descriptions and understand which attributes correspond to which product characteristics.
Glisten AI addresses this challenge through an automated approach combining computer vision and natural language processing technologies. The platform analyzes product images and descriptions to automatically extract and classify relevant product attributes. Rather than relying on generic computer vision algorithms, Glisten's system is context-aware and trained on a growing library of approximately 11 million product images paired with corresponding descriptions. The platform uses natural language processing to parse descriptions and understand which attributes correspond to which product characteristics.
The system learns from how people naturally label products, creating models based on aggregate human labeling patterns. For fashion and apparel, the platform identifies attributes such as sleeve length, neckline style, and occasion suitability. For other product categories like beauty or automotive, the same underlying algorithms adapt to identify category-specific characteristics. For example, a shampoo product might be classified by volume, hair type, and ingredient information like paraben content. This flexibility allows the platform to serve multiple retail verticals beyond its initial fashion focus.
The system learns from how people naturally label products, creating models based on aggregate human labeling patterns. For fashion and apparel, the platform identifies attributes such as sleeve length, neckline style, and occasion suitability. For other product categories like beauty or automotive, the same underlying algorithms adapt to identify category-specific characteristics. For example, a shampoo product might be classified by volume, hair type, and ingredient information like paraben content. This flexibility allows the platform to serve multiple retail verticals beyond its initial fashion focus.
Glisten AI's primary customers are e-commerce retailers, marketplaces, and brands that need to manage large product catalogs with consistent, searchable data. The company discovered that its ideal customers are those who directly experience the pain of maintaining messy and unreliable product data. Use cases include enabling better product search and discovery, powering accurate filtering and faceted navigation, improving product recommendations through structured attributes, and providing reliable data for analytics and business intelligence.
Glisten AI's primary customers are e-commerce retailers, marketplaces, and brands that need to manage large product catalogs with consistent, searchable data. The company discovered that its ideal customers are those who directly experience the pain of maintaining messy and unreliable product data. Use cases include enabling better product search and discovery, powering accurate filtering and faceted navigation, improving product recommendations through structured attributes, and providing reliable data for analytics and business intelligence.
The company operates on a business-to-business model, selling to retailers and marketplace operators rather than directly to consumers. Early traction showed five figures of monthly recurring revenue through direct outreach sales efforts. Glisten AI competes against internal manual tagging teams and general-purpose computer vision solutions, but differentiates through its ability to produce structured, standardized data specifically optimized for e-commerce applications.
The company operates on a business-to-business model, selling to retailers and marketplace operators rather than directly to consumers. Early traction showed five figures of monthly recurring revenue through direct outreach sales efforts. Glisten AI competes against internal manual tagging teams and general-purpose computer vision solutions, but differentiates through its ability to produce structured, standardized data specifically optimized for e-commerce applications.
The platform leverages advances in artificial intelligence, specifically computer vision and natural language processing, to automate what would otherwise require significant human effort. By training on real-world product data and descriptions, the system captures how people actually describe and categorize products, resulting in more accurate and useful attribute extraction than generic algorithms.
The platform leverages advances in artificial intelligence, specifically computer vision and natural language processing, to automate what would otherwise require significant human effort. By training on real-world product data and descriptions, the system captures how people actually describe and categorize products, resulting in more accurate and useful attribute extraction than generic algorithms.
