プロダクト
AI Applications
Give Product Data the Power of Thought.
Lazuli's AI automatically analyzes and converts text, images, and unstructured data into data that can be immediately used in PIM, DAM, and external operations.
Products
AI Applications
Give Product Data the Power of Thought.
Lazuli's AI automatically analyzes and converts text, images, and unstructured data into data that can be immediately used in PIM, DAM, and external operations.
Products
AI Applications
Give Product Data the Power of Thought.
Lazuli's AI automatically analyzes and converts text, images, and unstructured data into data that can be immediately used in PIM, DAM, and external operations.
AI Tools That Turn PIM and DAM into Strategic Assets
AI Tools That Turn PIM and DAM into Strategic Assets
AI Tools That Turn PIM and DAM into Strategic Assets
AI applications go beyond simple storage systems—they give data meaning and purpose. Lazuli’s AI interprets product information stored in PIM or DAM, transforming it into actionable knowledge through tagging, classification, and content generation. From marketing and analytics to product development and sales enablement, every business process moves faster with Lazuli AI.
AI applications go beyond simple storage systems—they give data meaning and purpose. Lazuli’s AI interprets product information stored in PIM or DAM, transforming it into actionable knowledge through tagging, classification, and content generation. From marketing and analytics to product development and sales enablement, every business process moves faster with Lazuli AI.
AI applications go beyond simple storage systems—they give data meaning and purpose. Lazuli’s AI interprets product information stored in PIM or DAM, transforming it into actionable knowledge through tagging, classification, and content generation. From marketing and analytics to product development and sales enablement, every business process moves faster with Lazuli AI.
Data Generation
Reconstruct the Way it's Communicated,into Product Information that Maximizes value.
AI automatically collects product information published on the internet from multiple sources. Data in different formats such as Excel, PDF, and HTML is normalized to a common schema and converted into centrally managed structured data.
This automates competitive research and information gathering tasks that previously required manual effort and time.
Product Information Feature Tags
Automatically generates tags such as "Usage" and "Features" to enhance searchability and appeal.
Image Text Tags
Reads characters on packages and labels using OCR and converts them into structured data, such as brand, material, and capacity.
Image Feature Tags
Automatically assigns tags that extract product characteristics from photos and can be used for search and recommendations.
Product Description Generation
Generates natural sentences aligned with the brand and automatically checks for AI-specific exaggerated expressions.
Data Enrichment
Incomplete Information,Turned into "Usable Data".
AI automatically collects product information published on the internet from various sources in the market. In addition to data in different formats such as Excel, PDF, and HTML, it can also ingest information from standard specifications like GS1 and complex external services.
AI normalizes it to a common schema and further assigns attributes from Lazuli DB, converting it into centrally managed structured data.
This automates competitive research and information gathering, which previously required a vast amount of manual work, and allows immediate utilization of valuable product data.
Automatic completion of missing information (product name, category, etc.)
AI automatically complements blanks and unclear elements within product information. It eliminates the need for manual processing due to variations in notation or omissions, ensuring consistent master data.
Automatic expansion from JAN to GS1 and collected data
Based on the JAN code, it matches and retrieves product data collected by GS1 and Lazuli, automatically expanding the master data.
Feature Labeling
Based on product information, it can also automatically determine if it meets predefined criteria or conditions and assign it as a new attribute column.
Data Estimation
Derive Clear "Classifications" From Ambiguous Expressions.
AI automatically estimates and structures information embedded in product images and descriptions (such as category, color, material). It also complements variations in product names and missing tags, redefining them as structured data. This builds a foundation that can be utilized for more advanced data applications like segment analysis and recommendations.
Automatic Estimation of Product Category
AI automatically identifies the category to which a product belongs based on its name, description, image, etc.
Estimation of Attributes such as Product Color and Material
Based on image analysis and descriptive information, AI automatically classifies and extracts attributes such as color, material, and size. It also learns subjective expressions, enabling classification closer to the user's perspective.
Feature Estimation
Based on the features included in the product information, AI automatically estimates whether it matches predefined conditions such as "Food for Specified Health Uses" or "Gluten-Free" and assigns labels.
Data Collection
From "Collecting" to "Usable" Data.
AI automatically collects product information published on the internet from multiple sources. Data in different formats such as Excel, PDF, and HTML is normalized to a common schema and can be immediately utilized as centrally managed structured data. This automates competitive research and information gathering, which traditionally required a vast amount of manual work, and provides a data foundation directly linked to business in a copyright-free manner.
Automatic Collection from Multi-Data Sources
Collects product information from e-commerce sites, manufacturer sites, catalogs, etc.
Schema Unification and Normalization
Formats structures and notation variations from each data source into a unified format.
Real-time Updates
Constantly reflects the latest market information and automatically processes update differences.
Data Generation
Reconstruct the Way it's Communicated,into Product Information that Maximizes value.
AI automatically collects product information published on the internet from multiple sources. Data in different formats such as Excel, PDF, and HTML is normalized to a common schema and converted into centrally managed structured data.
This automates competitive research and information gathering tasks that previously required manual effort and time.
Product Information Feature Tags
Automatically generates tags such as "Usage" and "Features" to enhance searchability and appeal.
Image Text Tags
Reads characters on packages and labels using OCR and converts them into structured data, such as brand, material, and capacity.
Image Feature Tags
Automatically assigns tags that extract product characteristics from photos and can be used for search and recommendations.
Product Description Generation
Generates natural sentences aligned with the brand and automatically checks for AI-specific exaggerated expressions.
Data Enrichment
Incomplete Information,Turned into "Usable Data".
AI automatically collects product information published on the internet from various sources in the market. In addition to data in different formats such as Excel, PDF, and HTML, it can also ingest information from standard specifications like GS1 and complex external services.
AI normalizes it to a common schema and further assigns attributes from Lazuli DB, converting it into centrally managed structured data.
This automates competitive research and information gathering, which previously required a vast amount of manual work, and allows immediate utilization of valuable product data.
Automatic completion of missing information (product name, category, etc.)
AI automatically complements blanks and unclear elements within product information. It eliminates the need for manual processing due to variations in notation or omissions, ensuring consistent master data.
Automatic expansion from JAN to GS1 and collected data
Based on the JAN code, it matches and retrieves product data collected by GS1 and Lazuli, automatically expanding the master data.
Feature Labeling
Based on product information, it can also automatically determine if it meets predefined criteria or conditions and assign it as a new attribute column.
Data Estimation
Derive Clear "Classifications" From Ambiguous Expressions.
AI automatically estimates and structures information embedded in product images and descriptions (such as category, color, material). It also complements variations in product names and missing tags, redefining them as structured data. This builds a foundation that can be utilized for more advanced data applications like segment analysis and recommendations.
Automatic Estimation of Product Category
AI automatically identifies the category to which a product belongs based on its name, description, image, etc.
Estimation of Attributes such as Product Color and Material
Based on image analysis and descriptive information, AI automatically classifies and extracts attributes such as color, material, and size. It also learns subjective expressions, enabling classification closer to the user's perspective.
Feature Estimation
Based on the features included in the product information, AI automatically estimates whether it matches predefined conditions such as "Food for Specified Health Uses" or "Gluten-Free" and assigns labels.
Data Collection
From "Collecting" to "Usable" Data.
AI automatically collects product information published on the internet from multiple sources. Data in different formats such as Excel, PDF, and HTML is normalized to a common schema and can be immediately utilized as centrally managed structured data. This automates competitive research and information gathering, which traditionally required a vast amount of manual work, and provides a data foundation directly linked to business in a copyright-free manner.
Automatic Collection from Multi-Data Sources
Collects product information from e-commerce sites, manufacturer sites, catalogs, etc.
Schema Unification and Normalization
Formats structures and notation variations from each data source into a unified format.
Real-time Updates
Constantly reflects the latest market information and automatically processes update differences.
Data Generation
Reconstruct the Way it's Communicated,into Product Information that Maximizes value.
AI automatically collects product information published on the internet from multiple sources. Data in different formats such as Excel, PDF, and HTML is normalized to a common schema and converted into centrally managed structured data.
This automates competitive research and information gathering tasks that previously required manual effort and time.
Product Information Feature Tags
Automatically generates tags such as "Usage" and "Features" to enhance searchability and appeal.
Image Text Tags
Reads characters on packages and labels using OCR and converts them into structured data, such as brand, material, and capacity.
Image Feature Tags
Automatically assigns tags that extract product characteristics from photos and can be used for search and recommendations.
Product Description Generation
Generates natural sentences aligned with the brand and automatically checks for AI-specific exaggerated expressions.
Data Enrichment
Incomplete Information,Turned into "Usable Data".
AI automatically collects product information published on the internet from various sources in the market. In addition to data in different formats such as Excel, PDF, and HTML, it can also ingest information from standard specifications like GS1 and complex external services.
AI normalizes it to a common schema and further assigns attributes from Lazuli DB, converting it into centrally managed structured data.
This automates competitive research and information gathering, which previously required a vast amount of manual work, and allows immediate utilization of valuable product data.
Automatic completion of missing information (product name, category, etc.)
AI automatically complements blanks and unclear elements within product information. It eliminates the need for manual processing due to variations in notation or omissions, ensuring consistent master data.
Automatic expansion from JAN to GS1 and collected data
Based on the JAN code, it matches and retrieves product data collected by GS1 and Lazuli, automatically expanding the master data.
Feature Labeling
Based on product information, it can also automatically determine if it meets predefined criteria or conditions and assign it as a new attribute column.
Data Estimation
Derive Clear "Classifications" From Ambiguous Expressions.
AI automatically estimates and structures information embedded in product images and descriptions (such as category, color, material). It also complements variations in product names and missing tags, redefining them as structured data. This builds a foundation that can be utilized for more advanced data applications like segment analysis and recommendations.
Automatic Estimation of Product Category
AI automatically identifies the category to which a product belongs based on its name, description, image, etc.
Estimation of Attributes such as Product Color and Material
Based on image analysis and descriptive information, AI automatically classifies and extracts attributes such as color, material, and size. It also learns subjective expressions, enabling classification closer to the user's perspective.
Feature Estimation
Based on the features included in the product information, AI automatically estimates whether it matches predefined conditions such as "Food for Specified Health Uses" or "Gluten-Free" and assigns labels.
Data Collection
From "Collecting" to "Usable" Data.
AI automatically collects product information published on the internet from multiple sources. Data in different formats such as Excel, PDF, and HTML is normalized to a common schema and can be immediately utilized as centrally managed structured data. This automates competitive research and information gathering, which traditionally required a vast amount of manual work, and provides a data foundation directly linked to business in a copyright-free manner.
Automatic Collection from Multi-Data Sources
Collects product information from e-commerce sites, manufacturer sites, catalogs, etc.
Schema Unification and Normalization
Formats structures and notation variations from each data source into a unified format.
Real-time Updates
Constantly reflects the latest market information and automatically processes update differences.
Data Generation
Reconstruct the Way it's Communicated,into Product Information that Maximizes value.
AI automatically collects product information published on the internet from multiple sources. Data in different formats such as Excel, PDF, and HTML is normalized to a common schema and converted into centrally managed structured data.
This automates competitive research and information gathering tasks that previously required manual effort and time.
Product Information Feature Tags
Automatically generates tags such as "Usage" and "Features" to enhance searchability and appeal.
Image Text Tags
Reads characters on packages and labels using OCR and converts them into structured data, such as brand, material, and capacity.
Image Feature Tags
Automatically assigns tags that extract product characteristics from photos and can be used for search and recommendations.
Product Description Generation
Generates natural sentences aligned with the brand and automatically checks for AI-specific exaggerated expressions.
Data Enrichment
Incomplete Information,Turned into "Usable Data".
AI automatically collects product information published on the internet from various sources in the market. In addition to data in different formats such as Excel, PDF, and HTML, it can also ingest information from standard specifications like GS1 and complex external services.
AI normalizes it to a common schema and further assigns attributes from Lazuli DB, converting it into centrally managed structured data.
This automates competitive research and information gathering, which previously required a vast amount of manual work, and allows immediate utilization of valuable product data.
Automatic completion of missing information (product name, category, etc.)
AI automatically complements blanks and unclear elements within product information. It eliminates the need for manual processing due to variations in notation or omissions, ensuring consistent master data.
Automatic expansion from JAN to GS1 and collected data
Based on the JAN code, it matches and retrieves product data collected by GS1 and Lazuli, automatically expanding the master data.
Feature Labeling
Based on product information, it can also automatically determine if it meets predefined criteria or conditions and assign it as a new attribute column.
Data Estimation
Derive Clear "Classifications" From Ambiguous Expressions.
AI automatically estimates and structures information embedded in product images and descriptions (such as category, color, material). It also complements variations in product names and missing tags, redefining them as structured data. This builds a foundation that can be utilized for more advanced data applications like segment analysis and recommendations.
Automatic Estimation of Product Category
AI automatically identifies the category to which a product belongs based on its name, description, image, etc.
Estimation of Attributes such as Product Color and Material
Based on image analysis and descriptive information, AI automatically classifies and extracts attributes such as color, material, and size. It also learns subjective expressions, enabling classification closer to the user's perspective.
Feature Estimation
Based on the features included in the product information, AI automatically estimates whether it matches predefined conditions such as "Food for Specified Health Uses" or "Gluten-Free" and assigns labels.
Data Collection
From "Collecting" to "Usable" Data.
AI automatically collects product information published on the internet from multiple sources. Data in different formats such as Excel, PDF, and HTML is normalized to a common schema and can be immediately utilized as centrally managed structured data. This automates competitive research and information gathering, which traditionally required a vast amount of manual work, and provides a data foundation directly linked to business in a copyright-free manner.
Automatic Collection from Multi-Data Sources
Collects product information from e-commerce sites, manufacturer sites, catalogs, etc.
Schema Unification and Normalization
Formats structures and notation variations from each data source into a unified format.
Real-time Updates
Constantly reflects the latest market information and automatically processes update differences.
Please Feel Free to Ask Any Questions or Consult with Us.
Have challenges managing your product data? We’re here to help you unlock its full potential.
Please Feel Free to Ask Any Questions or Consult with Us.
Have challenges managing your product data? We’re here to help you unlock its full potential.
Please Feel Free to Ask Any Questions or Consult with Us.
Have challenges managing your product data? We’re here to help you unlock its full potential.
Frequently Asked Questions
Q
What is Lazuli's AI application?
Q
Is the automatic generation of product descriptions and tags accurate?
Q
How do you prevent hallucinations?
Q
What kind of business operations can AI applications be utilized for?
Q
What kind of results can be expected after implementation?
The True Value of Lazuli PDP is Unlocked When Combined
The True Value of Lazuli PDP is Unlocked When Combined
The True Value of Lazuli PDP is Unlocked When Combined
By integrating each feature, we achieve a level of data utilization that cannot be reached through standalone use.
By integrating each feature, we achieve a level of data utilization that cannot be reached through standalone use.
By integrating each feature, we achieve a level of data utilization that cannot be reached through standalone use.
SOLUTIONS
Solve Your Business Challenges with AI Built for Product Information
SOLUTIONS
Solve Your Business Challenges with AI Built for Product Information
SOLUTIONS
Solve Your Business Challenges with AI Built for Product Information
Please Feel Free to Ask Any Questions or Consult with Us.
Have challenges managing your product data? We’re here to help you unlock its full potential.
Products
Solutions
Case Studies
Company Information
Recruitment
News
Please Feel Free to Ask Any Questions or Consult with Us.
Have challenges managing your product data? We’re here to help you unlock its full potential.
Products
Solutions
Case Studies
Company Information
Recruitment
News
Please Feel Free to Ask Any Questions or Consult with Us.
Have challenges managing your product data? We’re here to help you unlock its full potential.
Products
Solutions
Case Studies
Company Information
Recruitment
News
Please Feel Free to Ask Any Questions or Consult with Us.
Have challenges managing your product data? We’re here to help you unlock its full potential.
Products
Solutions
Case Studies
Company Information
Recruitment
News