• Product catalogue with thousands of SKUs and inconsistent, thin product descriptions hurting conversion and SEO?

  • Customer support volume dominated by order status, returns, and product FAQ that AI could handle consistently?

Generative AI in Retail

Retail generates more product data, customer interactions, and operational content than teams can manage manually. Generative AI in retail applies LLMs to the work that scales poorly with headcount -- product descriptions, customer support, personalised recommendations, and merchandising content at catalogue scale.
We build generative AI applications for retail and ecommerce that connect to your product catalogue, customer data, and inventory systems -- delivering value across customer experience, content operations, and merchandising efficiency.

  • Product description generation at catalogue scale with brand voice and SEO compliance

  • AI customer support handling returns, order status, and product FAQ without agent involvement

  • Personalised shopping experiences using customer behaviour and purchase history

  • Automated merchandising content for email, ads, and on-site promotions

RaftLabs builds generative AI applications for retail and ecommerce -- product description generation at catalogue scale, AI-powered customer support for order management and product FAQ, personalised shopping experiences, merchandising content automation for email and ads, and search and discovery improvements using LLMs. Generative AI in retail delivers measurable impact on content production cost, customer support cost, and conversion rate. Most retail AI projects deliver in 8--14 weeks at a fixed cost.

Vodafone
Aldi
Nike
Microsoft
Heineken
Cisco
Calorgas
Energia Rewards
GE
Bank of America
T-Mobile
Valero
Techstars
East Ventures

Retail's content and support problems scale with volume. Generative AI doesn't.

A team of 10 copywriters producing product descriptions can't scale when your catalogue grows by 10,000 SKUs. A support team sized for 500 contacts per day can't absorb 2,000 without proportional headcount. The operations that work at one scale break at the next.

Generative AI in retail solves the scaling problem -- product content, customer support, and personalised communication that grows with your catalogue and customer base without proportional cost increase.

What we build

Product description generation

LLM pipeline for generating product descriptions at catalogue scale -- from your product attributes, specifications, category context, and product images. Brand voice guidelines embedded in the generation system. SEO-optimised structure: title, bullet points, feature descriptions, and long-form description. Variant handling for products with multiple sizes, colours, or configurations. Batch generation for new catalogue imports. The content production that took days per SKU, automated.

AI customer support

AI-powered customer support handling the high-volume, predictable retail support queue: order status (live OMS integration), return and refund initiation (connected to your returns management system), product questions (product catalogue and support knowledge base), and account management. Scope-controlled responses with clean escalation to human agents for complex or sensitive queries. Integration with your ecommerce platform, OMS, and existing support tool (Zendesk, Freshdesk, or custom). Reduces support contact volume without degrading resolution quality.

Personalised shopping experience

Personalised product recommendations, category page merchandising, and shopping assistant features built on your customer behavioural data and purchase history. LLM-powered search that understands natural language queries ("something to wear to a summer wedding under $150") and maps them to your catalogue. Personalised email recommendations generated from customer segments and browsing history. The customer experience that turns first-time buyers into repeat customers.

Merchandising content automation

Automated merchandising content for email campaigns, promotional banners, social ads, and on-site promotions -- generated from your product data, pricing, and campaign parameters. A/B test copy variants generated at scale. Seasonal content updated automatically from your product and pricing data. The merchandising production that your content team currently produces manually at high per-piece cost.

Search and discovery

AI-powered search connecting natural language queries to your product catalogue -- understanding customer intent beyond exact keyword match. Synonym handling, colour and size interpretation, and category navigation via conversational query. Search personalisation based on customer history and behaviour. Zero-results handling suggesting alternatives and collecting demand signals. The search experience that converts more browsers to buyers.

Inventory and merchandising intelligence

AI analysis of your sales data, inventory levels, and market signals to support merchandising decisions -- demand forecasting summaries, markdown timing recommendations, replenishment alerts, and assortment gap identification. Presented as natural language summaries for merchandising teams rather than raw data dashboards. The insight that sits in your data but isn't being extracted because the analysis takes too long.

Generative AI for retail -- content, support, and personalisation at scale

Product description generation, AI customer support, and personalised shopping experiences. Fixed cost.

Let's talk about your project

Tell us the retail workflows you want to automate and the platforms you're currently running on. We'll scope the right solution and give you a fixed cost.

Frequently asked questions

The highest-ROI applications in retail are: (1) Product description generation -- retailers with thousands of SKUs and thin or inconsistent product descriptions can generate brand-consistent, SEO-optimised descriptions at scale. Content production cost drops 80--90%; time to publish new SKUs drops from days to hours. (2) Customer support deflection -- order status, return and refund requests, and product FAQ are consistent, high-volume, low-complexity queries that AI handles accurately without agent involvement. Support cost per contact drops significantly. (3) Personalised email and promotion copy -- LLMs generate personalised product recommendations and promotional messaging based on customer segments and purchase history. These three have the clearest ROI measurement and the shortest path to production.

We build a pipeline that takes your product data (attributes, specifications, category, images) and generates brand-consistent product descriptions using LLMs with your brand voice guidelines built into the system prompt. For image-based products (fashion, homewares, food), we use multimodal models that analyse product images as part of the generation context. Output goes through quality review before publishing -- human review for new categories, automated publishing for high-confidence outputs in established categories. Generated descriptions can include SEO-optimised headings, bullet points, and feature callouts matching your template structure.

AI retail customer support handles the high-volume, predictable queries: order status (connected to your OMS), return initiation (connected to your returns workflow), product FAQ (sourced from your product data and support knowledge base), and account management. The AI handles what it can confidently answer within your defined scope; complex queries, complaints, and situations outside the defined scope route to human agents with context. Integration with your ecommerce platform (Shopify, Magento, or custom) and order management system is required. The AI layer reduces support contact volume by 40--60% on typical retail support queues.

A product description generation pipeline for catalogue scale with brand voice controls and quality review workflow typically runs $20,000--$50,000. An AI customer support system handling order status, returns, and FAQ with OMS integration typically runs $30,000--$70,000. A comprehensive retail AI platform with product content, customer support, and personalised recommendations typically runs $60,000--$130,000. Cost depends on catalogue size, integration complexity, and the number of AI-powered workflows in scope. We scope every project before pricing it.