Why 85% of AI programmes stall before production
A structured review of the architectural, organisational, and governance factors that cause AI programmes to stop between proof of concept and production. Includes a self-assessment framework.
What is in your AI cloud bill and what it means for the business
A practical guide to understanding, attributing, and reducing AI infrastructure spend. Includes the cost taxonomy Aravian uses across retail and fintech programmes to identify waste without cutting capability.
EU AI Act: what changes in August 2026 and who it applies to
The obligations applying to organisations deploying customer-facing AI in EU markets from August 2026, written in plain language for technical and legal leadership teams.
Shopify Plus AI personalisation: why it is not working and how to fix it
The five most common reasons Shopify Plus AI personalisation fails to deliver in production, and the data architecture patterns that fix each one. Practical, not theoretical.
Agentic AI in the enterprise: a board primer for non-technical leaders
A plain-language guide to agentic AI for CFOs, General Counsel, and board members who need to understand what is being deployed in their name, what the risks are, and what questions to ask.
The data quality problem nobody talks about in Salesforce Agentforce deployments
Agentforce deployments fail most often not because of the agent configuration but because of the data it runs on. This is the problem, how we find it, and the pattern we use to fix it.
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