AI for retail
AI for retail built on product and customer data
We organise catalogues, enquiries and measures so AI can work with your business context.
Discuss your project →Practical use cases
The first use case follows task frequency and the availability of a verifiable result.
- Product attribute and description normalisation
- Search and answers across catalogues and policies
- Customer enquiry classification
- Assortment, inventory and sales analytics
Required data
Typical sources include the product catalogue, transactions, inventory, enquiries and internal rules. Before a pilot, we align product identifiers, reference data, returns and time windows so the same metric is not interpreted differently.
Pilot boundaries
AI should not independently change prices, terms or customer records. During a pilot it prepares a recommendation, draft or analytical view for an accountable role to approve.
Fit before scope
Is this the right starting point?
Use these criteria for an initial orientation. The final recommendation follows a review of your context, data and constraints.
A good fit when
- A process or decision that needs improvement is identified
- An accountable sponsor and result user are available
- A measurable outcome or quality criterion can be defined
Resolve this first when
- The goal is simply to buy unspecified AI without a defined challenge
- A guaranteed impact is expected before data are assessed
- No one is accountable for accepting the result
A verifiable first stage
What you can use to make the next decision
The exact scope is agreed before work begins. These are typical decision artefacts, not promised business results.
AI use-case matrix
Challenges compared by value, data availability, risk and ease of verification.
Pilot boundary
One process with defined users, sources, human oversight and stop conditions.
Decision criteria
Quality measures and a process to scale, refine or stop the initiative.
Five questions · no datasets or credentials
Frequently asked questions
Frequently asked questions
Can we start with the product catalogue only?
Yes. Attribute normalisation and catalogue search can be a separate use case without customer-data access.