How we make this list: we compare pricing pages, product documentation and public user reviews. Ratings come from G2, Capterra or Trustpilot, with the date we checked them.
Key takeaways
- Zendesk QA, the product formerly known as Klaus, is the natural pick inside Zendesk at $35 per agent per month, scoring every conversation with AI and keeping reviews inside the helpdesk your team already lives in.
- MaestroQA, now operating as Rippit, is the ticket heritage specialist: detailed scorecards, screen capture and calibration, with self serve tiers from $185 a month and a free tier for a first test.
- EvaluAgent publishes the clearest pricing in the field, AutoQM from $35 per user per month, with blended human and AI scorecards and a feedback experience agents actually rate.
- Playvox by NICE, Kaizo, Scorebuddy, Level AI and Voxjar cover the remaining shapes: QA bundled with workforce management, AI coaching agents, the easiest onboarding for new QA programmes, hands off automation, and flat pricing with unlimited users from $99 a month.
Quick comparison
| Tool | Best for | Starting price | Free plan |
|---|
 Zendesk QA | Zendesk native ticket QA | $35 per agent/month | No |
 MaestroQA (Rippit) | Detailed scorecards and calibration | $185 per month | Yes |
 EvaluAgent | Published per user pricing | $35 per user/month | No |
 Playvox by NICE | QA with workforce management | See website | No |
 Kaizo | AI scoring plus AI coaching | See website | No |
 Scorebuddy | New QA programmes | See website | No |
 Level AI | Hands off automated QA | See website | No |
 Voxjar | Flat pricing, unlimited users | $99 per month | Yes |
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We review this list regularly. Vendors can request a listing, send updated pricing or ask about featured placement.
Starting price$35 per agent/month
Free planNo
Zendesk QA wins where most ticket QA actually happens, inside Zendesk. Klaus built its reputation as the friendly QA tool support teams loved, and Zendesk bought exactly that goodwill plus its scoring engine. For a Zendesk shop, a native audit layer ends the integration project that used to precede any QA programme.
The trade is the walls. Your QA history, scorecards and calibration data become Zendesk assets, priced per agent, and a future helpdesk migration carries them awkwardly. Teams certain of their platform will not care.
What we like- The former Klaus, acquired by Zendesk and rebuilt as its native QA layer: AI scoring across every ticket, chat and call inside the helpdesk, with no separate system for agents to learn, $35 per agent per month in current pricing comparisons, scorecards, calibration and agent feedback workflows designed around Zendesk data from day one, the lowest friction route to 100 percent coverage for the large share of teams already on Zendesk
Watch out for- The value is Zendesk shaped: teams on other helpdesks get a fraction of the point, per agent pricing means QA leaders and reviewers count in the bill in ways flat priced rivals avoid, AI scoring quality still depends on your scorecard and calibration discipline, as everywhere here
Starting price$185 per month
Free planYes
MaestroQA earned its name in ticket QA before AI scoring was fashionable, and its scorecard and calibration depth still reads like it was designed by people who have run QA programmes, because it was. The Rippit self serve line finally gives smaller teams a way in without the enterprise sales cycle.
The trade is a company in motion. A rebrand split across products is a manageable annoyance, and the underlying tool is the same, but buyers should confirm which name, contract and roadmap their tier sits on.
What we like- The ticket first QA specialist, founded on support tickets rather than calls: deep scorecard building, calibration sessions, screen capture for seeing what the agent saw, and workflow automations, the company now operates self serve tiers as Rippit, with a free tier of 100 agent runs a month, Starter at $185 and Growth at $495 in current pricing, AutoQA scores 100 percent of tickets against criteria you set, using language models, phrase matching and process logic, also audits AI agents, integrating with the major bot platforms, so human and machine work is graded in one place
Watch out for- The brand is mid transition between MaestroQA and Rippit across two sites, which buyers will feel in documentation and contracts, enterprise MaestroQA pricing is quote based, with reported annual figures from about $18,000 to $60,000 for 25 to 100 agents, self serve tiers integrate with Zendesk and Intercom
- Call centre platforms sit on the enterprise tier
#3EvaluAgent
Best for: Published per user pricing4.5/5 on
G2 (448 reviews, checked Oct 2026)
Visit evaluagent.com
Starting price$35 per user/month
Free planNo
EvaluAgent's whole pitch respects the buyer: here is the price, here are the scorecards, here is how an agent disputes a score they think is wrong. That last feature sounds small and is not. QA programmes die when agents decide the scoring is a black box that cannot be argued with; the dispute workflow is the pressure valve that keeps the data honest.
The trade is the remaining opacity at the edges, per conversation AI agent pricing, and the usual reality that the published tier is the start of the negotiation, not the end.
What we like- The transparent buy: its pricing page lists AutoQM and improvement from $35 per user per month, and AutoQM plus conversation intelligence from $65, in a field that mostly hides prices behind demos, blended scorecards mix AI scoring with human review, with calibration, agent disputes and appeals built in, a detail that decides whether agents trust the system, coaching, one to ones and performance plans connect scores to improvement, and training can trigger automatically when an agent crosses a low performance threshold
Watch out for- The AI evaluation of AI agents is priced per conversation with no published rates, so bot heavy operations cannot fully budget from the website, a demo and proof of concept still precede real deployment despite the published prices, vendor outcome claims, big percentage gains in quality scores, are customer stories, not guarantees
Starting priceSee website
Free planNo
Playvox answers the organisational question instead of the feature one: quality and staffing are the same conversation, since most quality failures are scheduling failures wearing a disguise, too few agents, wrong skills, peak hour shortcuts. Owning QA and workforce management in one suite makes that connection visible in the data.
The trade is platform commitment, the recurring theme of this support cluster. NICE is a large platform; Playvox inside it serves NICE customers best and prospects second.
What we like- QA as part of a workforce engagement suite: quality management alongside scheduling and forecasting, now inside NICE after its acquisition of Playvox, so it pairs with one of the largest contact centre platforms in the world, digital first heritage, built for chat, email and social support rather than retrofitted from call recording, reported starter pricing around $15 per agent per month in buyer comparisons, though current terms need confirming
Watch out for- Pricing is not published cleanly, and reported figures vary, so budget from a quote, not from comparisons, the NICE gravity well applies: the full value assumes more of the NICE stack over time, standalone buyers should test how much of the roadmap points elsewhere, suite breadth means the ticket QA depth competes for development attention with a very large platform
Starting priceSee website
Free planNo
Kaizo's bet is that QA data most teams collect and ignore becomes valuable when it converts itself into coaching: this agent, this week, this specific habit, with examples from their own tickets. That conversion, from audit to improvement, is where QA budgets are justified.
The trade is trusting the conversion. An AI coach drafting feedback on a person's work, from an AI's scoring of that work, stacks two models between the manager and the agent. Used as a draft the manager edits, it saves hours. Sent unreviewed, it teaches agents that the company grades by robot, and they will respond in kind.
What we like- Scores 100 percent of chat, email and AI agent conversations against criteria you write in plain language, then turns the results into AI generated coaching rather than leaving managers a spreadsheet, built for Zendesk and Salesforce Service Cloud environments, with scorecards, missions and performance views aimed at agent engagement, positions its criteria control as the differentiator: your rubric, your words, not a fixed vendor model
Watch out for- Pricing is not public, and its own comparison material describes rivals' prices instead, a tell that a sales process stands between you and a number, coaching generated by AI needs a manager's eye before it lands on a person
- Tone in feedback is a human responsibility, newer and smaller than the Zendesk and NICE entries, with the roadmap risk that implies
Starting priceSee website
Free planNo
Scorebuddy is what a first QA programme should buy: not the most automation, but the clearest path from no scorecards to a working monthly rhythm of sampling, scoring, calibrating and coaching. Programmes fail at setup far more often than at scale, and Scorebuddy's reputation is for being running by Friday.
The trade is the ceiling. A team that grows into 100 percent AI coverage across channels and bot auditing will shop this list again within a few years. That is an acceptable trade: buying for the programme you have beats buying for the one in the strategy deck.
What we like- The onboarding pick in current comparisons: scorecard building simple enough for a team standing up its first QA programme, without a consultancy phase, covers the core loop, evaluate, calibrate, report, coach, across contact centre channels, a long track record in QA specifically, predating the AI wave, which shows in the calibration and reporting design, suits teams whose alternative is a spreadsheet and a monthly argument
Watch out for- Pricing is quote based, with no published entry point for a small team to self assess, its AI automation story is lighter than the hands off claims of Level AI or Kaizo, larger operations may outgrow its reporting depth toward the enterprise entries here
#7Level AI
Best for: Hands off automated QA4.6/5 on
G2 (220 reviews, checked Oct 2026)
Visit level.ai
Starting priceSee website
Free planNo
Level AI pushes furthest toward the fully automated end of QA, and the correct response is neither fear nor faith but measurement: run it against your managers' scores on the same tickets for a month, publish the agreement rate internally, and let that number set how much human review you retire.
What we like- The automation maximalist: AI scoring across all conversations with hybrid scorecards mixing machine and human judgement, built to minimise the manual review hours in the QA loop, conversation intelligence layered on top, themes, sentiment, root causes across the whole ticket base, positioned for operations that want QA as an always on signal rather than a monthly exercise
Watch out for- Reviewers on public platforms flag scoring accuracy issues, which matters more, not less, when the pitch is removing human review, pricing is enterprise and unpublished, automation confidence should be earned per deployment: its own category peers advise testing any tool on your own conversations before signing, and Level AI is no exception
Starting price$99 per month
Free planYes
Voxjar exists because the per agent model has a perverse effect: it charges you for transparency, every agent viewing their scores, every lead reviewing, costs a seat. Flat pricing removes the tax on the behaviour QA programmes need most. For a fifty agent team, the arithmetic against $35 a seat is not close.
The trade is maturity. You are buying a pricing philosophy from a company still building its integration list, and the due diligence, your helpdesk, your channels, your export needs, sits with you.
What we like- The pricing rebel of the field: $99 a month published, unlimited users, with a free tier, against an industry standard of $35 to $120 per agent per month, agents can see their own scores without each viewer costing a licence, which changes how openly a programme can run, self serve signup with AI QA and no mandatory sales call, aimed at small and mid market teams the enterprise tools ignore
Watch out for- A smaller, newer vendor than the platform entries, with the integration breadth and support depth still growing, call centre telephony coverage is its home ground
- Pure ticket and chat shops should verify their helpdesk is supported, unlimited user pricing works because the bet is on usage
- Very heavy volume teams should confirm the fair use terms
How we chose
We required ticket and conversation scoring against custom scorecards, calibration tooling, and evidence of current 2026 operation, and we tracked the category's consolidation, Klaus into Zendesk, Playvox into NICE, MaestroQA's rebrand to Rippit, because the name on the contract is now a buying fact. Prices are published figures where vendors publish them, flagged as reported or quote based where they do not. Vendor improvement percentages are treated as marketing, not outcomes. No hands-on testing is claimed; trial any tool against your own tickets, with your managers' scores as the reference.
Running an audit programme the scores deserve
Start with the scorecard, and keep it short enough to argue about: greeting and ownership, diagnosis, accuracy, policy compliance, tone, resolution and documentation. Every criterion beyond what a coach can discuss in one sitting dilutes all of them. Write the criteria with the agents' leads in the room; a rubric imposed finished is a rubric gamed politely.
Calibrate on a schedule, not on a complaint. Weekly at first, monthly when stable: the QA analyst, two team leads and the AI's output on the same five tickets, disagreements resolved into rubric wording, not into winners. The agreement rate between human and machine scores is the programme's vital sign; publish it, and let it decide how much sampling the AI still needs.
Close the loop where agents live. A score an agent cannot see, dispute or learn from is surveillance, and will be treated as such, fairly. The tools above all provide agent views and dispute flows; the programme's job is the human half, coaching tied to real tickets, and recognition when the difficult conversation was handled beautifully.
Frequently asked questions
How many tickets should we audit?
With AI scoring, all of them, that is the point of the category, but human review should concentrate where it teaches: a sample per agent per week for coaching, every ticket the machine flags as a policy risk, and every ticket in a dispute. Manual only programmes traditionally sample 2 to 5 percent, which misses patterns entirely.
Can AI scoring be trusted to grade agents fairly?
It can be trusted to apply your rubric consistently, a narrower and still valuable claim. Its fairness depends on the rubric, the calibration behind it and the dispute route in front of it. Publish the human machine agreement rate, let agents appeal scores, and never let a machine score alone trigger discipline.
What changed with Klaus, MaestroQA and Playvox?
Ownership and names. Klaus was acquired by Zendesk and is now Zendesk QA. Playvox was acquired by NICE and sits inside its workforce engagement suite. MaestroQA rebranded its self serve product as Rippit while the enterprise product keeps the MaestroQA name. If your shortlist is from 2023, rebuild it; the tools exist, but the contracts and roadmaps moved.
Should we audit our AI support agents with the same tools?
Yes, and the leading tools here now do it explicitly, MaestroQA's bot integrations and Kaizo's AI agent scoring among them. Grade bots against the same rubric as humans, with added checks for fabricated policy and confident wrong answers. A bot deflecting a ticket badly is a quality defect like any other, and full coverage auditing is how you find it before your customers explain it to you.
What does ticket QA software cost in practice?
Published anchors: Zendesk QA at $35 per agent per month, EvaluAgent from $35 per user per month, Rippit self serve at $185 and $495 a month, Voxjar flat at $99 a month with unlimited users. Quote based enterprise deals for 25 to 100 agents are reported at $18,000 to $60,000 a year. Model your own team's shape before comparing headline prices.
Sources we checked (0)
Is your product missing or out of date?
We review this list regularly. Vendors can request a listing, send updated pricing or ask about featured placement.
Shihab Mia · Founder, Rankite
Shihab has 5+ years in B2B and SaaS SEO. He writes Rankite's software buying guides from pricing pages, documentation and public user reviews. More about Shihab.