Decagon pricing: model the curve, not the quote

Decagon does not publicly disclose pricing, instead offering custom enterprise contracts typically based on resolved conversations or other usage outcomes alongside platform or implementation fees, with rates, minimums, overages, and add-ons negotiated through sales. This outcome-based approach is common among AI customer support vendors because it links costs to customer-service results, though it also means expenses can rise substantially as automation rates improve, even if total conversation volume remains stable. The text advises buyers to model projected costs across different automation levels and secure written contract terms defining resolutions, volume caps or floors, minimum commitments, overages, and renewal pricing. It also contrasts fully managed outcome-priced platforms with options such as Voiceflow that offer more published pricing information and operational controls, including per-intent cost visibility and model-routing choices, emphasizing that buyers should assess both headline pricing and their ability to manage spending over time.

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