AI streamlines data extraction from incoming invoices, whether received via email or uploaded in various formats, including duplicate detection.
Eliminates manual paper-based invoice handling and data entry, efficiently managing hundreds of invoices as a cohesive document set.
Converts invoices with extensive line items into a structured data format.
AI models for table recognition accurately identify and categorize rows and cells, organizing each line item into logical groups.
Features
Performs in-depth fashion data analysis and produces detailed trend reports.
Detects potential fashion trends using predefined criteria and analytical rules.
Forecasts future fashion movements by processing both historical and real-time data on market trends.
2. Design & Product Development Application
AI technology is increasingly integrated into the fashion design and development process.
It provides design recommendations, optimizes patterns to maximize fabric efficiency, and creates virtual prototypes of clothing items.
This allows designers to explore various fabrics, styles, and colors, visualize the final product, and streamline the design process, potentially reducing the number of revisions needed.
Features
Optimizes patterns to minimize fabric waste, contributing to more sustainable production practices.
Enhances material use, which helps lower production costs.
Develops virtual models of clothing items to preview designs and assess fits before physical production.
Enables real-time adjustments and provides instant feedback on design modifications.
Generates a range of design ideas based on trends, designer preferences, and historical data.
Offers tailored suggestions that match brand aesthetics and target audience preferences.
Supports experimentation with various fabric, style, and color combinations to find the optimal match.
Analyzes current trends to recommend popular fabric types, styles, and colors.
3. Merchandising and Analysis application
Effective merchandising is crucial for optimizing sales and enhancing customer satisfaction. AI aids this process by improving inventory management and assortment planning.
AI systems analyze comprehensive data, including sales figures, historical trends, and customer preferences, to determine the best product mix, quantities, and store placements.
This datadriven strategy helps minimize excess inventory, reduce stockouts, and ultimately improve profitability for fashion businesses.
Features
Gathers and evaluates data from multiple sources to provide a complete view of inventory.
Uses trend analysis and historical data to forecast demand, ensuring timely production of in-demand items and preventing overstocking.
Delivers real-time insights into stock levels and product performance to enable informed decision-making.
Segments customers based on predefined criteria through data analysis.
Identifies potential opportunities for cross-selling and upselling based on customer segments.
