Standalone AI quality assurance scores every conversation your existing support team handles, human or AI, without asking you to replace your helpdesk. If you already run Zendesk Suite, Zendesk QA (formerly Klaus) is usually the simplest choice. If you run another helpdesk, or a mix of human agents and an AI agent, evaluagent, Lorikeet, Scorebuddy, Level AI and Rippit all connect to systems you already have and grade conversations automatically rather than by sample.

The differences that decide the pick are which systems each tool connects to, whether it scores AI agent conversations as well as human ones, how quickly data arrives, and whether the price is published. This guide compares six tools on those points, using only what each vendor publishes.

Key takeaways

• Already on Zendesk Suite? Zendesk QA is the native add-on, and its AutoQA scores all interactions, including AI agents and voice (Zendesk). For most Zendesk teams it is the better pick.

• Not on Zendesk? evaluagent publishes seat pricing from $35 per user per month and connects to Intercom, Zendesk, Salesforce, Genesys and Five9 (evaluagent pricing).

• Running an AI agent too? Lorikeet prices automated QA per ticket, $0.30 on Start and $0.27 on Scale, with built-in system checks free, and links each finding to a fix you can test (QA page).

• Sampling is the constraint to remove. NICE puts traditional manual QA at 2 to 5 percent of interactions reviewed (NICE); every tool here scores all of them.

• Regulated teams need evidence, not anecdotes. The UK Consumer Duty says firms "will need to understand and evidence" whether good customer outcomes are being met (FCA PS22/9).

Which tools offer standalone AI QA for an existing support team?

Lorikeet runs quality checks on every ticket its AI agent handles, scores each one Good, Warning or Critical, and can score human-agent tickets the same way once enabled for your account (QA page). Three alternatives cover the same job from different starting points:

• Zendesk QA uses AutoQA to analyse every interaction, including AI agents and voice, for teams on Zendesk (Zendesk QA).

• evaluagent scores 100% of conversations for human and AI agents, priced by seat for people and by conversation for AI agents (evaluagent).

• Scorebuddy auto-scores voice, chat and email and reviews both human agents and AI chatbots (Scorebuddy).

How we chose and checked these tools

We included a tool only if it met four tests: it scores conversations automatically rather than by sample, it connects to helpdesks or contact-centre platforms a team already runs, it covers AI agent conversations as well as human ones, and its vendor publishes enough about connections or pricing to compare. Every vendor fact below was checked on that vendor's own public pages on 30 October 2026, and each claim links to its source.

Two housekeeping notes. Klaus and Zendesk QA are one product: Zendesk's own help centre lists "Zendesk Quality Assurance (formerly Klaus)" (Zendesk help), so it appears once. MaestroQA's old address, maestroqa.com, now redirects to Rippit, so we describe Rippit as its own site presents it today.

Lorikeet publishes this guide and is one of the tools listed. We have tried to describe every product, including our own, using only what each vendor publishes, and we link to the source for each claim.

Standalone AI QA tools compared

Sources: Zendesk QA, Zendesk QA connections, evaluagent pricing, evaluagent integrations, per-ticket QA pricing, Scorebuddy pricing, Scorebuddy integrations, Level AI QA, Level AI integrations, Rippit pricing.

1. Zendesk QA (formerly Klaus): teams already on Zendesk Suite

Zendesk QA is the right first look for any team whose tickets already live in Zendesk. Zendesk says AutoQA scores the quality of all interactions, including AI agents and voice, and covers all channels, including BPOs (Zendesk QA). You can use built-in categories such as Empathy or Solution, or write prompt-based categories of your own. Spotlight flags churn risks, escalations and knowledge gaps, and the AI-agent QA view lets you compare bot and human scores side by side.

It is not limited to Zendesk tickets. Zendesk's help centre describes connecting Front and Gorgias, setting up custom integrations, and adding up to 50 connections through sales (help desk connections, Front connection). Two details matter for a standalone buyer: imported tickets sync every four to six hours rather than instantly, and one native connection must remain active.

Pricing: the Zendesk pricing page lists quality assurance as requiring the QA add-on and does not print a price (Zendesk pricing). Pick it if you run Zendesk Suite and want QA in the same vendor contract. Look elsewhere if Zendesk is not your system of record and you want a published price.

2. evaluagent: mixed human and AI teams on any helpdesk

evaluagent is built as a QA layer that sits beside your stack. Its homepage says it scores 100% of conversations automatically and offers AI agent observability that detects hallucinations and missed intents and tracks customer sentiment over time (evaluagent). Its integrations page lists Intercom, Zendesk, Salesforce Service Cloud, Genesys and Five9, among others, with Intercom described as a native integration that imports conversations automatically (evaluagent integrations).

Its pricing is the most transparent of the seat-based tools. AutoQM and Improvement starts from $35 per user per month, and AutoQM plus Conversation Intelligence from $65 per user per month; for AI agents and high-volume work it offers pay-per-conversation pricing quoted on your volume (evaluagent pricing). evaluagent lists SOC 2 Type II and ISO/IEC 27001:2022 on its homepage.

Pick it if you want a dedicated QA, coaching and calibration product for a human team on Intercom, Salesforce or a CCaaS platform, with AI agent coverage alongside. Trade-off: scoring finds problems; fixing an AI agent's workflow still happens in that agent's own platform.

3. Lorikeet: teams running or adding an AI agent who want findings turned into fixes

Lorikeet's QA is part of Coach, its AI operations agent. Quality checks run automatically on every ticket the AI agent handles and score it Good, Warning or Critical against built-in system checks plus custom checks you define; results roll up into a Ticket Quality Score you can track by concierge, workflow or agent (QA page). Human-agent tickets can be scored the same way once enabled for your account, and the product documentation says the quality dashboard then shows individual human team members and external AI agents alongside each other.

The difference from the tools above is what happens after scoring. Coach groups failed checks into themes, proposes a workflow or knowledge fix, and lets you test it with simulations before it ships (Coach). Firm360 runs a knowledge-gap analysis every two weeks, publishes new articles, and Auto QA keeps reviewing them, so the next similar conversation is handled end to end (Firm360 story).

Pricing: system checks are free; automated QA with custom checks is $0.30 per ticket on Start and $0.27 on Scale, on plans from $2,100 per month paid annually, with a 30-day free trial (pricing). Start and Scale include SOC 2 Type 2, ISO 27001 and a DPA or BAA as standard. Honest limit: Lorikeet is built around its own AI agent. Human-agent scoring is switched on by request, and standalone Coach pricing without the agent is by quote, so a human-only team with no plans for an AI agent will find evaluagent or Zendesk QA a more direct fit.

4. Scorebuddy: contact centres that want QA, coaching and learning in one place

Scorebuddy grew up in contact-centre QA. It says it auto-scores 100% of conversations across voice, chat and email, reviews both human agents and AI chatbots, and keeps a full audit trail for regulated environments (Scorebuddy). Its QA for Bots product checks each bot response against your approved knowledge base and monitors for guardrail violations and sensitive topics (QA for Bots). Intercom's VP of Customer Support is quoted on that page, and the integrations page lists Intercom, Genesys, Amazon Connect, Salesforce and NICE CXone (Scorebuddy integrations).

Pricing: three plans, all "request a price". AI Auto Scoring starts on Accelerate, which includes 500 monthly AI scores; Elite includes 1,000 and adds conversation analytics and EU, US or UK data regions (Scorebuddy pricing). Trade-off: if you want every ticket scored, check how your volume compares with the included AI scores before you sign.

5. Level AI: voice-heavy contact centres

Level AI positions its QA for call centres. It says it scores 100 percent of calls, chats, emails and bot conversations, and brings evaluation, calibration, dispute handling and actioning into one platform (Level AI QA). Dispute handling and calibration are useful when agents' scores feed pay or performance reviews. Its integrations page lists Zendesk, Intercom, Salesforce, Kustomer, Freshworks, Genesys, Five9, Talkdesk and Amazon Connect (Level AI integrations).

Pricing: not published; the site routes to a demo. Trade-off: Level AI sells a wider suite (agent assist, virtual agents, voice of the customer), so a team that only wants QA may be buying more platform than it needs.

6. Rippit: lean teams that want to analyse every conversation cheaply

Rippit, which now sits at the address MaestroQA used, describes itself as an AI conversation data platform. It analyses 100% of conversations and lets you build agents for jobs such as chatbot monitoring (incomplete resolutions, wrong answers, coverage gaps) and employee coaching (Rippit). It imports conversations from Intercom and Zendesk in one click, and can import AI agent conversations from Decagon (Rippit integrations).

Pricing: the only tool here with a free plan: 100 agent runs a month with $100 in AI credits, then Starter at $185 and Growth at $495 a month (Rippit pricing). Trade-off: you design the analysis yourself, so calibration, disputes and scorecard governance are less prescribed than in evaluagent, Scorebuddy or Level AI.

What should standalone AI QA do for an existing support team?

It should score every conversation, on your rubric, from the systems you already run. Sampling made sense when a person had to read each transcript; with automated scoring, the useful questions become whether the rubric matches your policies, whether a score explains its reasoning, and whether a low score turns into a coaching task or a fix. For a deeper walk-through of rubric design, see our guide to QA for 100% of tickets across human and AI agents and AI auto QA for every ticket.

Can one tool score your AI agent and your human team on the same scorecard?

Yes, and all six claim to. The practical test is whether both sources land in one dashboard with the same checks. Zendesk QA compares bot and human scores side by side; evaluagent applies every capability to human and AI conversations and only changes the pricing unit; Lorikeet shows contained, escalated and human-handled tickets in one Ticket Quality Score once human scoring is on. If you run an AI agent from another vendor, ask whether the QA tool imports that agent's conversations directly, as Rippit does for Decagon, or only sees what the agent writes back into your helpdesk. Teams comparing Zendesk's native AI with a specialist can also read our Zendesk AI comparison.

Why do regulated support teams need full coverage rather than samples?

Because regulators ask firms to show outcomes, and a sample cannot show what it never read. In the UK, the Consumer Duty came into force on 31 July 2023 for open products, and the FCA says firms "will need to understand and evidence" whether good outcomes are being met (FCA PS22/9). In Australia, ASIC says the standards in RG 271 on internal dispute resolution are enforceable, and most firms covered must report IDR data to ASIC (ASIC RG 271).

AI agents raise the stakes. The CFPB found that in 2022 over 98 million users, about 37% of the US population, engaged with a bank's chatbot, and warned that "the ability for chatbots and scripts to recognize a dispute may be limited" (CFPB). In the EU, Article 50 of the AI Act requires that people are informed when they interact with an AI system, from 2 August 2026 (EU AI Act Article 50). Full-coverage QA is how you check that disclosure, dispute recognition and escalation actually happened on every conversation. NIST's AI Risk Management Framework, released on 26 January 2023 for voluntary use, is a sensible structure for documenting how you measure an AI system once it is live (NIST AI RMF). For finance-specific tooling, see compliance AI QA tools for financial services.

What still needs a human?

• The rubric. Someone who knows your policies has to write and own the checks; AI applies them, it does not decide them.

• Calibration. Reviewers should regularly score a set of conversations by hand and compare with the AI, especially after a rubric or model change.

• Disputes and people decisions. When a score affects an agent's pay or performance review, a manager should review the evidence, which is why Level AI and Scorebuddy build dispute and calibration workflows.

• Complaints and vulnerable customers. QA can flag a missed complaint or a customer in distress; a trained person decides the remedy.

• Compliance sign-off. QA output is evidence for your compliance team, not a substitute for its judgement.

How to choose: questions to ask before you pick

1. Where do our tickets live? If the answer is Zendesk Suite, start with Zendesk QA. If it is Intercom, Salesforce or a CCaaS platform, start with evaluagent, Scorebuddy or Level AI.

2. Do we run, or plan to run, an AI agent? If yes, ask how the tool imports those conversations, and whether QA findings can change the agent's behaviour or only report on it.

3. How fresh does the data need to be? A sync every few hours is fine for coaching; it is slow for catching a broken workflow on a busy day.

4. What is the pricing unit at our volume? Convert seat prices and per-ticket prices into a monthly figure at your real ticket count and team size.

5. Can we see the reasoning behind a score? A score without evidence is hard to coach from and hard to defend to an auditor.

If you want to see per-ticket QA alongside an AI agent on your own tickets, you can start a Lorikeet 30-day free trial.