Product content and catalogue enrichment
Speeding up repetitive content work such as product descriptions, attribute extraction and category mapping, with human approval.
AI for E-commerce
In e-commerce, AI can save time and cost in areas such as product content, customer support, search and recommendation, and operations automation. Huaris AI prioritises these scenarios, selects the right model and integrates it while protecting customer data.
Example use cases
Customer support assistant
An assistant (RAG) that answers order, return and shipping questions based on your policies and catalogue information.
Search and recommendation experience
Natural-language product search and recommendations based on customer intent, evaluated together with your existing search infrastructure.
Operations and internal processes
Automating internal workflows such as classifying order emails, supplier correspondence and reporting.
Review and feedback analysis
Summarising customer reviews and extracting recurring issues.
Points to watch in this industry
- Customer personal data (name, address, order history) should be masked before being sent to a model; an on-premise model should be considered where needed.
- For changing information such as price, stock and campaigns, you need an architecture connected to a current data source rather than the model's general knowledge.
- Limits and human handover rules should be defined against the risk of giving wrong product information or commitments such as returns and prices.
- Success measures (resolution rate, response time, customer satisfaction) should be defined up front.
Our approach
We first identify the highest-value areas through AI Strategy and Discovery. We design solutions such as the support assistant under Custom AI Solutions, and address the data and security side with our Product Development, Security and Compliance service.
Frequently asked questions
Where should AI start in e-commerce?
It usually starts with a repetitive, measurable task, for example an assistant that answers part of the support questions, or product content generation. A discovery engagement determines with your data which area will bring the highest value.
Is customer data sent to the AI model?
It depends on the architecture. Designs in which personal data is masked or never sent are preferred; an on-premise model is used where needed. See the Security and Compliance page for details.
Let's work together
Let us listen to your processes and goals, and evaluate together where AI can add value.
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