EvaluAgent Review (2026)

Publishes its pricing, which in the QA category makes it immediately easier to evaluate than most of its competitors.

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Visit EvaluAgent ↗Opens www.evaluagent.com in a new tab.

Not rated yet. Too little published information about EvaluAgent to score it fairly against the rest of the category.

What the score measures. Five things we can verify from published material: whether pricing is transparent, whether the product can act on your systems or only answer from documents, whether the vendor still owns its own roadmap, how much independent review evidence exists, and whether the bill stays predictable as volume grows. Weighted, then scored against an ideal platform that scores 5.

Evidence scoreNot rated yet

Starting price$35 /user/mo

Pricing modelPer seat

Free planNo

Self-serveYes

IndependentYes

BEST FOR: TEAMS THAT WANT A QUOTE WITHOUT A SALES CALL · LAST UPDATED 2026-07-30

EvaluAgent in depth

EvaluAgent is a UK-founded quality assurance platform covering automatic and manual scoring, coaching workflows and calibration. Capability-wise it sits close to MaestroQA.

Its most practical distinction is that it publishes per-seat pricing. In a category where most vendors want a discovery call before they will name a number, being able to price a tool from its website is a real advantage for a buyer trying to build a shortlist.

What it does

Automatic and manual QA scoring
Custom scorecards with weighting
Agent feedback and coaching workflows
Published per-seat pricing
Help desk and contact centre integrations
Reporting and calibration tooling

More detail on how it works

It covers both AI-assisted automatic scoring and traditional manual review, which suits teams that want to keep humans in the QA loop rather than hand it entirely to a model.

Published pricing

The reason it is easy to shortlist. You can build a business case in ten minutes rather than waiting for a sales cycle, and that matters more than it should in this category.

Automatic plus manual scoring

Both, rather than forcing a choice. Useful for teams that want AI coverage across everything with human review on the cases that matter.

Coaching workflows

Feedback loops from scores to agents. Competent, and less opinionated than Kaizo's coaching-first design.

Setting EvaluAgent up

Realistic time to a working deployment: Days. These are the standard steps for this category. We have not published a walkthrough specific to this tool yet.

01
Connect your conversation source
Help desk, contact centre or CRM. Read-only in most cases.
02
Backfill historical conversations
Gives you a baseline before any coaching starts. Hours for large volumes.
03
Build the scorecard
The step that decides whether this is useful. Few, specific, observable criteria beat a long rubric.
04
Calibrate against human scores
Have a manager grade fifty conversations by hand and compare. If the AI disagrees systematically, fix the rubric before trusting the dashboard.
05
Set the sampling scope
Most teams move from the 2% a manager samples to 100% coverage. Decide what you will act on before you generate it.
06
Wire scores into coaching
A dashboard nobody reviews weekly changes nothing. This is the step that produces the return.

The step that takes longer than they imply. Scorecard design. The tool grades whatever you tell it to, so a badly designed rubric produces confident, useless numbers at scale.

What the AI actually does

Every platform here says “AI agent”. It covers a bot that reads your help centre and a system that can refund a customer. This is which one you are buying.

Assists a human

EvaluAgent scores conversations and then does something most QA tools stop short of: it turns the score into work.

A failed check can trigger a coaching session, an escalation, a training assignment or a formal improvement plan.

All of that happens inside EvaluAgent rather than in your help desk, so the thing it acts on is your agents' development rather than the customer's ticket.

Scores every conversation across voice, chat and email on bespoke drag-and-drop scorecards, with weighted criteria, auto-fail logic and rules that adapt by queue. The product is AutoQM, not AutoQA
Blended scorecards mix automated checks and human observations on the same card, which is a cleaner answer than arguing about whether AI grading is trustworthy in general
A score, a sentiment shift or a compliance flag can trigger a workflow immediately — coaching, escalation to a human reviewer, an assigned training course, or an HR-ready improvement plan tied to the evidence
A separate product, AI Agent Observability, grades your bots rather than your people, and does it across vendors: its own line is that cross-vendor reporting grades Cognigy, Sierra, Decagon and your humans against the same definition of quality
It plugs into Genesys Cloud, NICE CXone, Five9, Talkdesk, Amazon Connect, Salesforce, Zendesk and others, with REST APIs and webhooks, but in its own words the conversations, scores and trend reporting sit in evaluagent rather than in the bot platform

Who Should Use It

The second list is the more useful one.

Teams wanting QA without a sales cycle

Published pricing, so you can evaluate on your own timetable.

Teams keeping humans in QA

Automatic and manual scoring together, rather than full automation of the review process.

Non-Zendesk teams

Where Zendesk QA's integration advantage does not apply and the field is open.

Who should look elsewhere. Very small teams where a manager reviews conversations directly, and organisations with unusually complex QA requirements where MaestroQA's configurability is worth the sales cycle.

Strengths and Weaknesses

What Works

Published pricing in a category that mostly hides it.

What Does Not

Less well known than the larger QA vendors.
Not as deep as MaestroQA on intricate rubric design.

EvaluAgent pricing

Read from evaluagent.com/pricing (vendor's own) on 2026-08-11.

AutoQM & Improvement

$35

/user/mo

Starting figure. The page calls its numbers ballpark and asks you to request a tailored quote

AutoQM + Conversation Intelligence

$65

/user/mo

Starting figure

AutoQM for AI agents

$0.05

/conversation

Sits on top of a seat tier rather than replacing it

Full bundle for AI agents

$0.13

/conversation

Verified 2026-08-11 · evaluagent.com/pricing (vendor's own)

Per-seat pricing, published, which puts it ahead of most QA vendors on evaluability alone.

Against Zendesk QA at around $35 a seat, EvaluAgent is worth quoting directly, particularly if you are not on Zendesk and lose that integration advantage.

The full arithmetic

Against MaestroQA, EvaluAgent's advantage is that you can price it without a call; MaestroQA's is depth on complex rubrics. Both are worth putting side by side.

INTEGRATIONS

ZendeskSalesforceFreshdeskGenesysNICE CXoneFive9Slack

Our Recommendation

Who we would tell to buy this, and who we would not.

EvaluAgent deserves a place on most QA shortlists for a simple reason: you can price it from its website. In a category where nearly everyone requires a discovery call, that lets you build a business case on your own schedule, and the capability is close enough to the better-known alternatives that the transparency is a real tiebreaker. Keeping both automatic and manual scoring suits teams that do not want to hand review entirely to a model. If your rubrics are genuinely intricate, MaestroQA goes deeper — quote both.

Where we write about EvaluAgent

3 pieces on this site name it.

As the volume moves to AI, nobody is reviewing what the AI said unless a QA tool does it.Support QA was built to review what human agents did. Now tier-one is answered by software, and the question is whether the grader can grade it. Here is what the QA platforms in this directory actually document, including the one publishing evidence against its own automation.
78 is average. Whether that is good depends entirely on what you sell.The cross-industry average, benchmarks for eight sectors, and the three ways a CSAT score gets inflated before it reaches a dashboard.
Can AI grade support conversations?Guide — Quality assurance and scoring