Intelligence

Context: dashboards that read themselves

Open any view and the summary, the anomalies and the suggested next steps are already there. No question needed.

Chat: ask the way you'd ask a colleague

"Why is Kestrel Energy 250ml down in Walmart Dallas–Fort Worth, and what do I tell the buyer?" Intelligence picks the analyses, the Advise Engine computes them, and you get the answer with the evidence: sales down 44%, stores selling 102 → 40, rate of sale stable. It's a distribution problem, not a demand problem. Follow-ups like "compare it to Red Bull" just work.

Research: a written brief, ready for the meeting

Set the scope (category, retailer, brands and period), then pick a brief such as a Brand Performance Review, a Competitor Intelligence Brief or a Pricing and Promotion Review, or describe the job and let Intelligence choose. You get a structured brief with recommendations, over figures the Advise Engine has computed, and export it to PowerPoint in your own template, or to PDF, in one click.

Example: Harbour Drinks, a fictional brand owner.

Generic AI tools guess at your data and produce confident, wrong answers. Intelligence works differently.

1. You ask in plain English, on any dashboard, on desktop or phone.
2. Intelligence selects the right analyses from the governed Function Registry. It never touches raw data.
3. The Advise Engine computes them on your harmonised data.
4. You get a verified answer, and every figure is traceable to the analysis and the source behind it.

The AI never runs a query. It never invents a number.

Intelligence uses a Microsoft Azure OpenAI model served within your data region. Your data never trains the model. It inherits Core's role-based access, so people see only what they are allowed to see. AI governance

Intelligence is an add-on to Core and can be bought as its own AI line item. Pricing · Put your AI budget to work