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AI INNOVATION

AI Engineered to Power Modern Commerce

Trained on billions of data points and expert feedback, our models drive unmatched performance

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Harness AI to Accelerate Innovation, Productivity, and Scale

Powering Retail Intelligence with AI

Our AI Architecture

  • Pre-Processing & Enrichment: Clean, normalize, and refine multimodal text and image data
  • Feature Engineering and Model Building: Leverage CLIP, BERT, LLM embeddings, and Siamese networks to extract insights and map taxonomies
  • Knowledge Graph and Structured Intelligence: Build a retail-specific knowledge graph for accurate product and metadata mapping
  • Smart Storage and Retrieval: Store embeddings and insights in vector databases and graph stores for efficient access
  • Human-in-the-Loop Optimization: Continuously refine AI models with expert feedback for enhanced accuracy and greater control

DataWeave AI Stack

From AI to Actionable Outcomes

Product Matching

Achieve unmatched accuracy in product matching across industries, channels, and languages—powered by AI, multimodal intelligence, and human expertise.

Business Use Cases: Pricing Intelligence, Private Label Comparative Analysis, Assortment Gap Analysis

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Product Attribute Tagging and Normalization

AI-powered extraction, standardization, and augmentation of product attributes for consistency and accuracy.

Business Use Cases: Assortment Analytics, Product Classication

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Sentiment Analysis

AI-driven sentiment analysis to decode consumer feedback, uncover product insights, and enhance brand strategy.

Business Use Cases: Product Enhancements, Brand Health Monitoring, Customer Support Optimization

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Flyers & Promo Intelligence

AI-powered analysis of promo banners and flyers to track competitor strategies and optimize discount campaigns.

Business Use Cases: Campaign Effectiveness Evaluation, Promotional Spend Optimization, Seasonal and Sales Event Planning

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Content Optimization

Gen AI-powered content and keyword optimization to enhance discoverability, relevance, and conversions across search and PDPs.

Business Use Cases: Search Visibility Optimization, Improved Customer Engagement and Conversions

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AI Agents for Retail

AI-powered retail agents for intuitive data access, real-time insights, and faster decision-making.

Business Use Cases: Enhanced Executive Reporting, Faster Decision-Making

Frequently Asked Questions

How does DataWeave’s AI stack integrate multimodal intelligence to enhance product insights?

DataWeave’s AI stack combines text analysis, image recognition, and domain-specific heuristics to extract, standardize, and contextualize product data. This multimodal approach improves accuracy across critical areas like pricing, content optimization, and competitive benchmarking, providing a more comprehensive and reliable analysis for businesses.

What advanced techniques does DataWeave use to enhance product matching accuracy?

DataWeave utilizes a combination of deep learning, natural language processing (NLP), computer vision, and human-in-the-loop validation. These advanced techniques work together to ensure highly accurate product matching, reducing the risk of false positives and missed matches, even in complex product catalogs.

How does AI-driven sentiment analysis go beyond basic review aggregation to provide deeper insights?

DataWeave’s AI-driven sentiment analysis decodes nuanced customer feedback, detecting emerging trends and categorizing reviews by themes. This allows brands to uncover deep consumer insights, identify shifting market preferences, and adjust product strategies, customer experiences, and market positioning more effectively.

How do AI agents in retail enable faster decision-making through natural language interactions?

AI agents enable retailers to process queries in plain language, delivering instant insights on pricing, inventory, competition, and consumer sentiment. This real-time, data-driven decision-making empowers businesses to act quickly, optimize strategies, and stay competitive in dynamic retail environments.

How does AI help optimize content and keywords for changing search trends?

AI analyzes search patterns, ranks keyword relevance, and suggests content improvements to enhance discoverability and drive conversions. By staying updated with shifting trends and consumer behavior, AI ensures that content is optimized for maximum visibility and engagement, ultimately boosting search rankings and sales.

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