You reduce customer support costs with AI by moving resolvable volume off human agents and onto a system that charges less to close a ticket than a person costs to handle it. How much you save depends less on the vendor's marketing and almost entirely on which charging model you sign, because the four models in this market bill very differently at the same ticket volume.
This article compares five platforms on one criterion: the cost to resolve a ticket, computed from each vendor's own published pricing page. Where a competitor is cheaper per unit it ranks above Lorikeet, and we say why. Two of the five publish no unit price at all, which is itself a finding.
The short version
Per published list prices in September 2026, the cheapest fully published cost per resolved conversation is HubSpot's Breeze Customer Agent at $0.45, ahead of Intercom Fin at $0.99 per outcome and Lorikeet at $0.95 falling to $0.80 per resolution. Zendesk publishes seat prices but not a per-resolution rate. Ada publishes no prices at all.
Metric | Figure | Source |
|---|---|---|
Human-handled ticket cost | $6 to $12 | Fin, published on fin.ai |
AI resolution list prices, this vendor set | $0.45 to $0.99 | Vendor pricing pages, verified 4 Sep 2026 |
Reported year-one support cost reduction | 15% to 40% | Comm100 benchmark reporting |
Time to full ROI | 9 to 15 months | Comm100 benchmark reporting |
Median AI resolution rate, 195 deployments across 38 vendors | 70% (P25 56%, P75 80%) | My AskAI, May 2026 |
AI resolution rate across 220 million-plus live chats | 44.8% | Comm100 2026 AI Live Chat Benchmark Report |
Common service issues resolved autonomously by 2029 | 80%, with a 30% operating cost reduction | Gartner |
The 15% to 40% year-one reduction and the 9 to 15 month payback are Comm100's industry benchmark figures, not a Lorikeet result. Lorikeet publishes no cost-reduction percentage and no payback period, and nothing here should be read as one.
Define the billing unit before you compare any price
Four words get used interchangeably in this category. They are four different numbers, and four different invoices. Fix the definitions before you compare a single price.
Term | What it means | What it means on the invoice |
|---|---|---|
Resolution | The customer's issue is closed without a human touching it | You pay only when the problem is actually solved |
Deflection | The customer did not create a ticket, for any reason | Counts a person who gave up as a success |
Containment | The conversation ended inside the bot | Counts abandonment as containment |
Automation | The AI did something on the ticket, including partial work | Can be charged even when a human finished the job |
Conversation or session | One customer interaction, resolved or not | You pay whether or not it worked |
The gap is not academic. In My AskAI's May 2026 dataset of 195 deployments across 38 vendors, those reporting a metric labelled "Resolution" averaged 72.5% while those reporting "Automation" averaged 61%: a 12-point swing produced by the label alone. If your contract bills per automation and your business case assumed resolutions, you have already lost the argument.
The four charging models
Per resolution or per outcome. You pay when the AI closes the issue. Failed attempts are free. This is the model that most closely tracks value delivered, and it is what Lorikeet, Intercom Fin, HubSpot Breeze and Gorgias all use in some form.
Per conversation or per session. You pay for every interaction the AI touches, resolved or not. At a 50% resolution rate, a $2.00 per conversation price is an effective $4.00 per resolution.
Per seat. You buy licensed agent capacity by the month. This model punishes seasonal businesses hardest, because you buy twelve months of peak capacity to cover four weeks of peak.
Platform fee plus usage. A fixed annual commitment, often with implementation billed separately, then usage on top. The fixed component decides whether a small deployment is viable, and it is the part vendors are least likely to publish.
Most real contracts are hybrids. Zendesk and HubSpot charge seats and resolution-linked usage. Lorikeet and Fin sit on top of a helpdesk you already pay for, so their published price is not the whole bill either.
Five platforms ranked by published cost per resolved ticket
1. HubSpot Breeze Customer Agent: $0.45 per resolved conversation, the lowest published unit price
HubSpot's published pricing page prices Breeze through HubSpot Credits at $9.00 per 1,000 credits when paid annually, and states that the Customer Agent consumes 50 credits per conversation resolved. That works out to $0.45 per resolved conversation, the cheapest published unit price in this set by a clear margin. Service Hub Professional is listed at $90 per seat per month billed annually, includes 3,000 credits a month, and carries a one-time $1,500 onboarding fee. Enterprise is listed at $150 per seat per month with a $3,500 onboarding fee.
If your goal is the lowest arithmetic cost per closed ticket on straightforward volume, this is the row that wins, and no amount of positioning changes that. HubSpot's page also states unused credits do not roll over month to month, so the saving is real only if your volume is steady enough to consume what you buy.
Who it suits: teams already on HubSpot, with FAQ-shaped and order-status-shaped volume, whose data lives in the HubSpot object model. Who it does not suit: teams whose resolutions require calling three external systems in sequence under a policy that changes by jurisdiction, and teams not otherwise buying a HubSpot seat, since the credit price arrives attached to a full helpdesk licence.
Model your credit burn at your actual volume before signing, because unused credits expire monthly and overage is bought at the same published rate.
Check which other Breeze features consume credits from the same pool, because the Customer Agent is not the only consumer.
Price the migration honestly if you are not already on HubSpot: you are changing helpdesk, not adding an AI layer.
2. Intercom Fin: $0.99 per outcome, with no platform fee
Fin publishes $0.99 per outcome on fin.ai/pricing, with a 50 outcome per month minimum, and states plainly: "No setup, integration, or platform fees." Fin runs on your existing helpdesk including Salesforce and HubSpot, so at low volume it is the cheapest way to get outcome-priced AI live without buying a platform. If you also take the Intercom helpdesk, intercom.com/pricing lists seats at $29 (Essential), $85 (Advanced) and $132 (Expert) per seat per month, with a Pro add-on from $99 per month and Copilot at $29 per agent per month.
Fin also publishes the most useful comparative number in the category: human ticket handling at $6 to $12, AI resolution at $0.99 to $2.00. Treat the human figure as a vendor estimate rather than your baseline, but the order of magnitude is not controversial.
Who it suits: teams under roughly 5,000 tickets a month who want outcome pricing with no annual floor, and teams who want the AI on the same data model as the helpdesk. Who it does not suit: teams whose resolutions depend on multi-step actions in systems Fin has to reach through custom integration work, where the setup cost lands outside the published price.
Confirm what counts as an "outcome" in your contract, including Procedures that end in a configured handoff, since those are billable outcomes on Fin's published terms.
Model the seat layer separately if you are also buying the Intercom helpdesk, because seats are the larger line for teams with many agents and low volume.
Set usage alerts and limits from day one, which Fin's pricing page explicitly supports.
3. Lorikeet: $0.95 falling to $0.80 per resolution, no seat charge, but a plan floor
Lorikeet publishes its full price list on lorikeetcx.ai/pricing. Start is $1,500 a month paid annually with 18,000 credits a year, for teams under 5,000 monthly tickets, at 0.95 credits per chat, email or SMS resolution, 1.50 for a voice resolution up to three minutes, and 0.30 per ticket for routing, analytics tagging or automated QA. Scale is $4,000 a month with 48,000 credits a year for 5,000 to 20,000 monthly tickets, at 0.80, 1.20, 0.25 and 0.25. One credit is one dollar. There are no per-seat charges, and implementation and platform fees are included on both plans.
The commercial promise on that page is quotable verbatim: "We only charge for successfully resolved tickets. If you're unhappy with how Lorikeet handled a ticket, you don't pay for that ticket."
The honest problem with that price list is the floor. The plan is a prepaid credit block, so at 1,000 tickets a month and a 60% resolution rate you consume roughly 6,840 credits a year against 18,000 already paid for. Your effective cost is about $2.50 per resolution, not $0.95. The published rate only becomes the real rate once your volume consumes the block: above roughly 1,500 to 2,000 tickets a month on Start, and around 16,000 on Scale.
Who it suits: fintech, healthtech and insurance teams above roughly 2,000 monthly tickets whose resolutions require the AI to call APIs and change state in external systems under guardrails. Who it does not suit: anyone below that volume, and anyone whose only decision criterion is unit price.
Divide your annual plan cost by your realistic annual resolution count before you compare the headline rate to anything.
Price routing, tagging and automated QA separately at 0.30 or 0.25 per ticket, because those are charged per ticket rather than per resolution and apply to volume the AI never resolves.
If your resolutions are knowledge-base lookups with no system actions, this price assumes work you are not asking it to do.
4. Zendesk: $19 to $115 per agent per month published, resolution price not published
Zendesk publishes seat pricing openly: Support Team at US$19 per agent per month paid yearly, Suite Team at US$55, Suite Professional at US$115, Suite Enterprise on request. Add-ons are published at US$50 per agent per month for Copilot, US$50 for Workforce Engagement and US$83 for Contact Center.
What Zendesk does not publish is a per-resolution number. Its AI agents page describes a "resolution allowance" included in your service plan, "tiered outcomes" categorised "based on the value delivered", and the option to pre-purchase additional allowance. No dollar figure appears. Fin's competitor comparison page reports Zendesk at $50 per agent per month plus $2.00 per overage resolution, but that is Fin's characterisation of a rival, not a Zendesk-published price, and it should not be treated as one.
Who it suits: teams already standardised on Zendesk who want AI on the same tickets, reporting and knowledge base, with one vendor and one data model. Who it does not suit: anyone who needs to compare total cost across vendors before a sales call, because you cannot complete the arithmetic from public information.
Ask for the resolution allowance included in your specific plan, in units, in writing.
Ask which tier each of your top ten ticket types falls into, since tiered outcomes mean your blended rate depends on your ticket mix.
Price the Copilot add-on separately at US$50 per agent per month if agent assist is part of the business case.
5. Ada: no published price
Ada's pricing page publishes no prices. It offers a free consultation with an expert, a custom demo and a review of your channels. There is no plan tier, no per-interaction rate and no platform fee on the page. Fin's comparison page reports Ada at $0.15 to $0.45 per interaction and labels it "reported deal pricing" that is "not publicly listed", which matches what we found: there is nothing to verify.
Per-interaction billing charges you for failures as well as successes, so the effective cost per resolution is the quoted rate divided by the resolution rate. At 50%, a $0.30 interaction price is $0.60 per resolution.
Who it suits: teams comfortable running a procurement process to get a number, typically at enterprise volume. Who it does not suit: anyone building a business case this quarter from public information. Flex, whose story is published on lorikeetcx.ai, moved off Ada before selecting Lorikeet, citing flows that could not match the policy precision its renters depend on.
Ask whether the quoted unit is an interaction, a conversation or a resolution, and get the definition in the contract.
Divide any per-interaction quote by your expected resolution rate to get a comparable number.
Ask what the annual platform commitment is, separately from usage.
The arithmetic at 1,000, 5,000 and 20,000 tickets a month
Assumptions, so you can change them: 60% of tickets resolved by AI, human agents handle 500 tickets each a month, annual-billing list prices verified 4 September 2026, year-one figures including one-time fees. Lorikeet and Fin sit on a helpdesk you pay for separately, so add your existing helpdesk cost to those rows to compare like for like. The HubSpot and Zendesk rows include the helpdesk seat.
Vendor | 1,000 tickets/mo (600 AI resolutions) | 5,000 tickets/mo (3,000) | 20,000 tickets/mo (12,000) |
|---|---|---|---|
HubSpot Breeze, Service Hub Professional | $5,496 year one | $21,696 | $83,256 |
Intercom Fin, on your existing helpdesk | $7,128 | $35,640 | $142,560 |
Lorikeet, Start then Scale | $18,000 (Start, block not consumed) | $48,000 (Scale, block not consumed) | $115,200 (Scale plus overage) |
Zendesk Suite Professional | $1,380 seats, resolutions not published | $5,520 seats, resolutions not published | $22,080 seats, resolutions not published |
Ada | Not computable | Not computable | Not computable |
Effective cost per AI resolution, from those totals: HubSpot $0.76, $0.60 and $0.58. Fin $0.99 at every volume. Lorikeet $2.50, $1.33 and $0.80. Zendesk and Ada cannot be computed from published information.
Read the Lorikeet row honestly. At 1,000 tickets a month it is the most expensive computable option here by a wide margin, and the published $0.95 rate is not what you would pay. At 5,000 it is still dearer than Fin. Only at 20,000, where the credit block is fully consumed and the marginal rate governs, does it beat Fin, and even there HubSpot's unit price is lower.
The formula, and a worked example
Monthly gross saving equals AI-resolved tickets multiplied by your fully loaded human cost per ticket, minus AI-resolved tickets multiplied by your effective AI cost per resolution, minus fixed platform and seat cost. Fully loaded human cost per ticket is total support spend for the period, including salaries, benefits, management overhead, tooling and recruitment, divided by tickets handled.
Input | Value |
|---|---|
Monthly tickets | 8,000 |
Fully loaded human cost per ticket | $8.00 |
AI resolution rate | 55% |
AI-resolved tickets a month | 4,400 |
Effective AI cost per resolution | $0.99 |
Gross monthly saving on resolved volume | 4,400 x ($8.00 minus $0.99) = $30,844 |
Less: human cost per ticket rises on the remaining mix, say to $9.50 on 3,600 tickets | 3,600 x $1.50 = $5,400 |
Net monthly saving | $25,444 |
Net annual saving | $305,328 |
The seventh row is the one most business cases omit, and it is why a modelled saving rarely survives the finance team. When AI takes the simple tickets, the tickets left for humans are harder, so average handle time on the human queue rises. Fin's own guidance says exactly this: per-interaction handle time falls, "overall human AHT usually rises". Model it, or your forecast will be wrong in the direction that embarrasses you.
Why the lowest unit price is often the wrong buy
This article ranks on unit price because that is what the question asks, but the ranking argues against itself. Unit price is the least important number in the model. Resolution rate matters more at every volume, because every ticket the AI fails to close is a ticket a human handles at $6 to $12.
Run it. At 5,000 tickets a month, a tool at $0.45 resolving 40% costs $900 a month in AI charges and leaves 3,000 tickets on humans at $8.00: $24,900 total. A tool at $0.95 resolving 65% costs $3,088 and leaves 1,750 tickets on humans: $17,088 total. The dearer unit price is $7,800 a month cheaper. A 25-point resolution difference outweighs a 111% unit price difference, and it is not close.
This also reframes what a good resolution rate looks like. Comm100 measured 44.8% across more than 220 million live chat interactions, well below the 70% median My AskAI found across 195 deployments and far below the 80%-plus figures vendors advertise. Resolving 46% of a healthcare or lending queue, where every answer has a compliance consequence and most resolutions require writing to a system of record, is harder work than resolving 80% of order-status lookups. Compare rates within a queue type or not at all.
Five pitfalls that break the business case
Buying a unit price without an effective price
Every plan with a floor, a minimum or a prepaid block has an effective rate that differs from its published rate until you consume the commitment. Lorikeet's Start plan is the clearest example in this set: $0.95 published, roughly $2.50 effective at 1,000 tickets a month. Do this division for every vendor before you shortlist.
Comparing a resolution price to a conversation price
A per-conversation price is a per-resolution price divided by the resolution rate. Fin's published vendor comparison on fin.ai lists Salesforce Agentforce at $2.00 per conversation regardless of outcome. At 50% resolution, that is $4.00 per resolution. Normalise everything to cost per resolved ticket before you build a table.
Forgetting the second invoice
Lorikeet and Fin sit on your existing helpdesk, which you keep paying for. Zendesk and HubSpot bundle the helpdesk into the seat price. Put the helpdesk line in the model explicitly, or you will flatter one side of the table.
Counting deflection as saving
Deflection counts customers who did not create a ticket, including the ones who gave up and the ones who churned. A containment number counts conversations that ended inside the bot, including abandonment. Neither is a saving. Only a resolution is a saving, and only if the customer did not come back about the same issue, so check reopen and repeat-contact rates alongside the resolution rate.
Assuming the saving arrives as headcount reduction
It usually does not. Most teams deploying AI support absorb growth without hiring rather than cutting existing staff. That is still real money, since SHRM puts the average cost per hire at $4,700 before salary, but it lands as cost avoided rather than cost removed, and finance treats those two differently. Say which one you are forecasting.
What complex resolution buys you, when it is worth paying for
Arbor helps consumers in 13 deregulated US states lock in lower fixed electricity rates. Its support queue mixes bill decoding and rate explanations with state-specific questions tied to brokerage rules, utility breakdowns and market conditions. Head of Customer Operations Jessica Mishlove is quoted on the published story saying "Most AI companies talk about deflection like it's the goal", and that her team wanted the opposite. Arbor evaluated Sierra and others, and found most were built for retail and e-commerce rather than retail energy supply.
The published outcome is not a cost figure. It is 89% CSAT, with AI CSAT on par with human agents, and a Trustpilot rating that moved from 4.6 to 4.7. Custom API endpoints were deployed within days, alongside a bespoke Notion integration syncing state, utility and energy-specific content in real time. That integration work is what the price assumes.
Flex, which lets renters split monthly payments, publishes 2x CSAT versus its previous support tool, 4x chat volume during rent week compared with the rest of the month, and a 50% decrease in median conversation duration to resolution. It reached those numbers by connecting the AI to more than 40 customer attributes across accounts, transactions and property integrations. Note what is absent from both stories: neither publishes a cost saving, because Lorikeet does not publish one.
For a broader treatment of the levers themselves rather than the price lists, our guide to reducing customer support costs with AI is worth reading alongside this comparison.
Who this is not for
Cost-only buyers, explicitly. Lorikeet's own ideal-customer definition disqualifies buyers whose sole focus is cost reduction. That is an unusual thing for a vendor to write down, and worth taking at face value. If the brief from your executive team is "get the cost per ticket down and nothing else matters", the arithmetic here says buy the cheaper tool. HubSpot Breeze publishes $0.45 per resolved conversation against Lorikeet's $0.95 and $0.80, and on simple volume that gap will not close. Lorikeet's price assumes the resolution involved actions in external systems, not a knowledge-base lookup. If it did not, you are paying for capability you are not using.
Teams below roughly 1,500 to 2,000 tickets a month. The plan floor dominates the per-resolution rate, as the arithmetic above shows. At 1,000 tickets a month your effective cost is about $2.50 per resolution against a published $0.95.
FAQ, how-do-I and password-reset volume with no system actions. A maintained help centre plus a native deflection bot serves this better and costs less.
Teams that want a helpdesk-native add-on. If you are already on Zendesk or Intercom, want AI on the same tickets, and need native reporting, knowledge base sync and agent-copilot tooling, the native add-on gives you one vendor and one data model. Lorikeet is genuinely behind on reporting and observability, knowledge base management and customer memory, and deliberately does not build an agent-assist copilot.
Teams buying on setup speed. Lorikeet trades plug-and-play for configurability. A small team with no engineering support that wants to be live within the hour should pick something else.
Pure B2B enterprise SaaS with account-managed, low-volume, high-touch support. The economics do not work and the ticket types do not suit automation.
Key takeaways
Published cost per resolved ticket, cheapest first: HubSpot Breeze $0.45, Intercom Fin $0.99, Lorikeet $0.95 falling to $0.80. Zendesk and Ada publish no per-resolution rate.
Effective cost is not published cost. Lorikeet's Start plan is roughly $2.50 per resolution at 1,000 tickets a month because the prepaid credit block is not consumed.
Normalise every quote to cost per resolved ticket. A per-conversation price at 50% resolution is double its headline.
Resolution rate outweighs unit price. A 25-point resolution difference beat a 111% unit price difference in the worked example above.
Comm100's benchmark reporting puts year-one cost reduction at 15% to 40% and full ROI at 9 to 15 months. That is an industry figure, not a Lorikeet result.
If cost is your only criterion, buy the cheaper tool. Lorikeet's documented ICP disqualifies cost-only buyers.
What to do next
Take one month of tickets, tag the top ten types by volume, and mark each type as either knowledge-only or requiring a write to an external system. Price the knowledge-only share against the cheapest published unit rate above, and price the action-requiring share against vendors that can complete those workflows. If more than about a third of your volume needs a system action, integration depth replaces unit price as the deciding number. If it is under a tenth, buy on price.
