AI cost governance at retail scale
For retail and consumer brands running high-volume customer-facing AI - personalisation engines, virtual assistants, and recommendation systems that generate millions of LLM calls every day.
Modelled cost reduction
Up to 60%
$92,000 capped
Black Friday peak spend
100% scoped
Customer PII and payment data
Loops detected
18
Paused in seconds
Runaway shopping assistant
Per-channel caps
Product, channel, campaign
Where it hurts
Seasonal spend spikes
Black Friday and end-of-year campaigns send AI call volumes through the roof. Without caps and forecasting in place, a successful campaign can generate an eye-watering invoice.
Chatbot loop risk
Customer service and shopping assistant agents can enter infinite loops during peak traffic - a single runaway agent at scale can cost more in an hour than your daily AI budget.
Margin pressure
Retail margins are thin. AI costs that aren't actively governed erode contribution margin on your highest-volume SKUs - and most retailers don't know it's happening.
Customer data exposure
Personalisation and recommendation engines process customer PII and payment-adjacent data on every call. That puts them in scope for the Australian Privacy Principles and, where card data is involved, PCI DSS - without a governance layer, you can't show what data reached which model.
What SAVI brings
Budget Caps
Set seasonal spend limits at the product, channel, or campaign level. SAVI enforces them automatically and alerts your team before you breach - not after.
Learn moreCost Dashboard
See AI spend broken down by channel, product category, and customer segment in real time - so you can understand the true cost of every AI-powered experience.
Learn moreLoop Detection
Automatically detect runaway shopping assistant or recommendation engine loops and raise a pause signal your agents act on - before they generate runaway costs during high-traffic events.
Learn moreAI cost reduction, modelled on a retail deployment scenario
Protect your margins at every scale
See how SAVI can model AI cost reductions of up to 60% for retail-scale personalisation workloads. Talk to our team for a free spend audit.