Palona priced on revenue impact

This pricing model turns Palona from a software line item into a revenue share proxy, which is why it can support much higher contract value than a simple phone bot. A restaurant will pay more if the system clearly catches orders that would have gone to voicemail, nudges callers into larger baskets, and moves big catering inquiries into booked events. That is a much easier budget story than charging for seats, which have little connection to whether revenue actually moved.

• Palona is already built around store level revenue workflows, not generic automation. The Ordering Agent pushes orders into POS systems and sends payment links, while the Catering Agent gathers headcount, budget, and dietary needs, then hands sales ready briefs to the catering manager. That makes pricing against recovered sales and conversion concrete.
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• The clearest comparable is Olo, where catering is sold as a revenue product because average catering orders are far larger than normal tickets, and brands use it to raise order value. When a vendor can point to bigger baskets and more booked events, pricing naturally shifts upward from per seat software fees toward value based contracts.
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• This also helps Palona defend against cheaper voice vendors and bundled POS features. SoundHound has massive interaction scale, and Toast can bundle AI voice into a broader restaurant stack. Palona needs to win on measurable store economics, especially missed call recovery and catering revenue, because pure call handling will get cheaper over time.
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The next step is for restaurant AI pricing to look more like performance software and less like headcount software. If Palona keeps tying each module to specific revenue lift, it can expand from phone ordering into catering and operations with rising contract value per location, even as the underlying voice infrastructure becomes more commoditized.