Preparing your data for AI
Our Data Readiness Assessment shows: where your data stands, what to fix and in which order before you invest further.
Why AI projects underdeliver
Most merchants sit on a wealth of data: customer behaviour, transactions, product catalogue, inventory and order history. The problem is that this data is scattered between systems and hard to keep current. AI models fed with conflicting inputs produce unreliable outputs no matter how good the model is. Personalisation turns generic and recommendations point customers to products that are out of stock. Without clear data ownership, quality keeps degrading and every new AI initiative starts on shakier ground.
The Data Readiness Assessment
A fixed-fee engagement over 4 to 6 weeks that scores your data on five dimensions: completeness, freshness, consistency, accessibility and governance. You get:
Scored quality baseline: an AI readiness rating showing where your data stands today
Gap map: exactly where AI systems can and can't reach in your current architecture
Remediation roadmap: prioritised actions for the next 30, 90 and 180 days, with effort, impact and owner for each initiative
Business-case-ready view: which AI use cases are within reach now and what it takes to make the rest viable