Your best upseller never calls in sick.
Veloci's AI upselling engine analyses each order in real time and suggests complementary items — drinks with mains, desserts after savoury dishes, sides that pair with the chosen entrée. It works across the AI phone agent, web ordering, and WhatsApp.
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Context-aware suggestions: recommends items based on what is already in the cart
Time-of-day logic: suggests coffee in the morning, desserts at dinner, late-night snacks after 22:00
Popularity-weighted: promotes high-margin items that other customers pair with the same order
Decline-respecting: the AI does not repeat a declined suggestion in the same session
A/B testing: test two suggestion strategies and Veloci picks the winner automatically
Revenue attribution: tracks the exact revenue generated by AI suggestions per week
Trusted by 500+ restaurants across Europe and Africa
Toast upselling is limited to in-store POS prompts shown to staff. Veloci's AI upselling works on every channel including phone and WhatsApp where staff have no involvement.
Flipdish shows static upsell recommendations on the ordering page. Veloci's suggestions are dynamic — generated fresh per order based on cart contents, time of day, and individual customer history.
Yes. In the menu editor, you can tag items as 'upsell candidates' and set pairing rules manually. The AI combines your explicit rules with data-driven patterns to generate suggestions.
Yes. During the AI phone call ordering flow, after the customer confirms their main order the AI naturally suggests a complementary item in a conversational way — not a scripted hard sell.
Veloci tracks individual customer behaviour. If a customer consistently declines certain categories, the AI reduces those suggestions for that customer and focuses on what they have previously accepted.
The analytics dashboard has a dedicated upselling revenue report showing how many suggestions were made, how many were accepted, and the total incremental revenue attributed to AI upsells over any period.
Yes. On web ordering, suggestions appear as "You might also like" cards after the customer adds an item. On WhatsApp, the AI sends a conversational prompt. Both are tracked with the same attribution model.
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