The true cost of per-resolution pricing

The Suvenna team · July 12, 2026 · 6 min read

A dollar per resolved conversation sounds like the fairest deal in software. You pay only when the AI actually does its job. No results, no bill. It's a genuinely appealing pitch, and it's why per-resolution pricing has become the default model for AI support.

We think the pitch survives exactly until you do the math on a store that's growing. This post works through that math with the public numbers, explains the billing mechanics that the headline price doesn't mention, and tries to be fair about the cases where a meter really is the right choice.

How the meter actually works

Two published pricing models dominate the category, so let's use them.

Intercom's Fin popularized the model at $0.99 per resolution. Crucially, Fin also bills what it calls an assumed resolution: if the customer simply stops replying after the AI's answer, that counts as resolved, and you're charged. More on why that matters below.

Gorgias, the incumbent helpdesk for Shopify stores, charges $0.90 to $1.00 per AI-resolved conversation on top of its ticket-capped plans, with $1.50 per-ticket overages once you exceed your plan's cap. And per their published pricing as of July 2026, a fully automated resolution is billed as both a ticket and a resolution. Read that again: when the AI handles a conversation end to end, it consumes one of your plan's tickets and incurs the resolution fee. The automation you bought to reduce your helpdesk bill is also draining the plan you're paying for underneath it.

That double-counting has a sharp edge at the cap. Once automated resolutions have burned through your included tickets, each additional fully automated conversation costs the resolution fee plus a $1.50 overage ticket: roughly $2.40 to $2.50, all-in, for a conversation no human touched.

The worked math

Here is what the meter alone costs at three volumes, before any base plan. The table assumes conversation volume roughly tracks resolution volume, which is generous to the metered vendors, since in reality your total conversations exceed your AI resolutions and the base plan is priced on the larger number.

| Monthly AI resolutions | Gorgias resolution fees ($0.90 to $1.00 each) | Fin resolution fees ($0.99 each) | Suvenna, total | | --- | --- | --- | --- | | 500 | $450 to $500 | $495 | $199 flat (Growth) | | 3,000 | $2,700 to $3,000 | $2,970 | $499 flat (Scale) | | 10,000 | $9,000 to $10,000 | $9,900 | $499 flat (Scale) |

The metered columns are resolution fees only. The base helpdesk plan comes on top, and for Gorgias, the double-billing means heavy AI usage also accelerates you into $1.50 overages. The Suvenna column is the entire bill: Growth includes 2,000 conversations a month with unlimited seats, and Scale includes 10,000.

Annualized, the gap stops being a rounding error. At 10,000 resolutions a month, Fin's meter alone runs about $118,800 a year. Suvenna's Scale plan is $5,988 a year at monthly billing, and less with annual billing, which includes two months free. That's roughly a twenty-fold difference, and the twenty-fold-more-expensive option is the one that gets pitched as pay-for-performance.

Notice the shape of the curve, because it's the real story. At 500 resolutions the meter costs a few hundred dollars and feels reasonable. Every improvement in the AI's resolution rate, and every month of store growth, moves you up the table. Per-resolution pricing is cheapest at the exact moment the product is least useful to you, and most expensive at the moment it's working best. Merchants call this the success tax for a reason.

The "assumed resolution" problem

The meter has a measurement problem underneath the math problem: what counts as a resolution is decided by the vendor charging for it.

Fin's assumed resolution is the clearest example. If a customer reads the AI's answer and never replies, that's billed as a resolution. But silence is not satisfaction. Sometimes the customer got what they needed. Sometimes they gave up, went to the store's Instagram comments, opened a chargeback, or just decided never to order again. From the meter's perspective, all of those are identical, successful, billable outcomes.

In practice, what per-resolution vendors measure is "conversation ended without a human touching it," which is a statement about workflow, not about whether the customer's problem was solved. A deflected customer and a delighted customer produce the same line item. You are not paying per outcome. You are paying per absence of follow-up, and an AI that's unhelpful enough can manufacture plenty of that.

The incentive problem

None of this requires assuming bad faith from anyone. It's just worth being clear-eyed about what a per-resolution business model rewards, because product decisions follow revenue gradients over time.

A vendor paid per claimed resolution grows revenue by maximizing claimable resolutions. That gently but persistently pushes in specific directions: classify borderline conversations as resolved rather than escalated, tune the AI to close conversations rather than invite follow-up questions, and treat abstention (the AI saying "I don't know, let me get you a person") as a revenue leak rather than a feature worth engineering well. The customer's incentive, a correct answer even when that means a human, and the vendor's incentive, a billable close, point in different directions exactly when it matters.

There's also a budgeting cost that has nothing to do with the vendor's behavior. Under a meter, your support spend becomes a function of order volume, seasonality, and the AI's performance, which makes it structurally unforecastable. Your best Q4 ever arrives with your biggest support bill ever, at precisely the moment your ad spend and inventory costs peak too.

When per-resolution pricing is actually fine

Fairness requires saying that the meter is sometimes the right call.

If you handle a few dozen conversations a month, a meter is cheap and a flat plan is wasted capacity. Pay the dollar, enjoy the service. If you're piloting AI support and want to evaluate real performance before committing to anything, pay-per-use is a low-risk way to test, and that's a legitimate use. And if your volume is extremely spiky around a couple of events a year with a near-zero baseline, metered billing can genuinely beat any flat tier.

The trouble is the transition. The meter is cheapest exactly until the product starts working and the store starts growing, and the crossover arrives earlier than most merchants expect: at typical resolution rates, a store doing a few hundred conversations a month is already past it. Almost nobody re-runs the pricing math after onboarding. The bill just grows.

The flat alternative

Suvenna's position is simple: your bill should not grow because our AI did its job. Plans are flat, conversations are included, Growth and above have unlimited seats, and there are no per-resolution fees, ever. Caps are soft, meaning we never cut you off mid-conversation, and annual billing includes two months free. The full breakdown is on the pricing page, and the head-to-head is on the Suvenna vs Gorgias comparison.

And because "pay only if it works" is the one legitimately good idea inside per-resolution pricing, we kept it, without the meter: if Suvenna doesn't independently resolve at least 30 percent of your conversations in your first 60 days, we credit your money back.

We onboard in limited waves so every store gets a clean rollout. If flat, predictable pricing for AI support that actually resolves sounds like the right side of this math, request early access. Founding members lock in 20 percent off their first year.