Product Retail Solutions
An AI Shopping Assistant Tailored to Your Retail Brand
icitech builds tailored AI shopping assistants for retail brands — enabling customers to discover products through natural conversation rather than filter menus. ICI ShopAssist is a conversational commerce layer that runs on your product catalogue, stock data, CRM segments, and active campaigns. It is not an off-the-shelf chatbot.
02 The problem
Product discovery beyond catalogue filters
Customers often know what they want but cannot translate that intent into filter selections. ICI ShopAssist closes that gap. A user can type 'suggest a quiet coffee machine for a small kitchen' or 'I'm looking for running shoes under £80', and the system converts that query into structured criteria — product attributes, category, price range, intended use — before generating a response directly from the brand's live catalogue. In the next message the user can narrow the search, request a comparison, or take the conversation in a different direction entirely. This replaces the conventional filter experience with guided, natural product discovery.
03 Capabilities
Personalisation and campaign awareness
Where CRM data and consented purchase history are available, ShopAssist can enrich its recommendations with the user's previous orders, saved items, or segment profile. For a query such as 'suggest trousers to go with the shirt I bought last month', the system can evaluate the purchase record alongside current catalogue data. Where the user is anonymous, recommendations are based on in-session preferences and product data alone. The scope of personalisation is configured in line with the organisation's data privacy and consent management policies. Within the same conversation, the assistant can also surface active promotions, voucher codes, or loyalty programme benefits; where CRM and loyalty infrastructure is connected, personalised offers can be presented in real time.
Real-time stock, store direction, and basket
Through ERP and WMS integration, ICI ShopAssist does more than recommend products — it can show which store holds a particular item. When a user asks 'is this available at my nearest store?', location and stock data can be combined under appropriate permissions; the assistant can then initiate a store direction, a product reservation, or a click-and-collect flow. Products added to the basket within the conversation are passed to the e-commerce layer, and the customer is directed to the standard checkout. For cross-sell and up-sell suggestions, the system draws on product data to explain the relevance of each recommendation, producing a more considered purchase experience.
04 How it works
Omnichannel deployment and channel adaptation
ICI ShopAssist can be integrated across mobile app, website, in-store kiosk, customer services, and the ICI StoreMate store-associate application. The same AI layer presents a different experience depending on context: in the customer-facing channel the priority is purchase guidance, while in the store-associate channel the emphasis shifts to stock status and product technical detail. This flexibility allows the brand to deliver consistent but context-aware assistance across every touchpoint.
RAG architecture and AI governance
Product responses in ShopAssist are generated using a retrieval-augmented generation (RAG) approach, drawing on the organisation's catalogue, PIM, and approved content sources. Variable data — pricing, stock levels, and active promotions — is served from live API feeds. Guardrails, data access permissions, source attribution, response boundaries, and brand language are all configured to the organisation's AI governance policy. High-risk or ambiguous queries can be escalated to a live customer service agent. This architecture prevents the AI from generating off-brand or inaccurate content and maintains a trustworthy customer experience.
Enterprise system integration and conversion analytics
The value of ICI ShopAssist derives from its integration with the organisation's existing systems: ERP supplies pricing and product data; WMS provides stock status; CRM contributes customer and segment data; PIM delivers rich product content; the loyalty programme connects campaign and benefit logic; and BI receives performance analytics. Conversation searches, product interactions, and conversion signals can be analysed at anonymous or consented-user level, giving merchandising, content, and product teams new demand signals drawn directly from customer conversations. icitech designs the LLM architecture, RAG layer, integration framework, UX/UI, and channel experience in conjunction with the organisation's existing technology estate.
05 Same group
Other products
- Retail SolutionsDesign Your Loyalty Programme and Campaign Management Around Your Brand Strategy
- Retail SolutionsManage Hundreds of Stores from a Single Operations Centre
- Retail SolutionsICI Retail+: A Customer Super App Built for Retail Brands
- Retail SolutionsICI StoreMate: A Tailored Store Associate App for Retail Organisations
06 FAQ
Frequently Asked Questions
01How is ICI ShopAssist different from a standard chatbot?
ICI ShopAssist is a conversational commerce layer that operates on the organisation's own data infrastructure — catalogue, CRM, stock, and loyalty — rather than a general-purpose bot. It is built and configured alongside the brand, not deployed as a generic product.
02Which retail sectors is it suited to?
It can be adapted to any retail segment with high product variety — fashion, consumer electronics, home and living, and FMCG, among others. The solution is shaped around the sector's product logic and customer behaviour.
03How is customer data protected?
The system operates within the organisation's own security policies and data governance framework, including obligations under UK GDPR where applicable. Customer data is not shared with third-party platforms.
04How long does integration typically take?
The timeline depends on the existing technology estate and the maturity of the organisation's data. icitech works with the technical team to define a phased roadmap and manages the process accordingly.
05Can it work alongside physical stores as well as online channels?
Yes — in addition to digital channels, the system can be configured for in-store scenarios such as kiosk deployment. Real-time stock and store information can be surfaced to customers during the conversation.
06How are active promotions and campaigns reflected in the assistant?
Active campaigns are connected to the system so that the assistant can present relevant offers to the user at the appropriate point in the conversation. Campaign updates can be managed without manual intervention in the assistant layer.
07How is conversion performance measured?
The solution includes an analytics layer tracking metrics such as conversation-to-conversion rate, add-to-basket events, and completed purchases. This data can be fed into the organisation's existing reporting infrastructure.
08Why is a RAG architecture used rather than a fine-tuned model?
RAG ensures that the model generates responses solely from the brand's current catalogue and approved content, rather than from generalised training data. This keeps control of accuracy and brand language with the organisation.
09Can the assistant operate in multiple languages?
The system can be configured to support multiple languages aligned with the brand's target markets. Language handling is designed as part of the overall user experience rather than added as an afterthought.
10How does it connect to an existing e-commerce platform?
ICI ShopAssist integrates with common e-commerce platforms and bespoke development environments via API. No fundamental changes to the existing platform are required.
07 Contact