Every conversation reviewed,not a sample of them.
Mira scores is web-based software (SaaS) for contact center quality assurance. It transcribes your team's conversations, answers your own scorecard from the transcript, and shows your evaluator exactly which words earned each point. Your evaluators review and sign every evaluation inside the platform.
What changes in the first month
What the Elite AI plan allows for each agent seat; Smart AI includes a smaller monthly allowance. Either figure is well beyond the few conversations an evaluator can work through by hand.
An agent hears about a conversation while they still remember having it.
Your scorecard, your teams, and your first calibrated results.
English and Spanish, and the AI reads a good deal more than that.
Why quality programs came to rely on sampling
A traditional quality program reviews a small sample of each agent's conversations, some weeks after they took place, with each evaluator applying the standard a little differently. It is a reasonable answer to a real constraint: there are only so many hours in an evaluator's week.
A sample describes part of the picture
A handful of conversations a month covers a small fraction of what an agent actually did, which makes the resulting score difficult to act on with confidence.
Feedback arrives some time after the call
By the time a review is written up, the conversation is weeks old and the detail has faded. That makes it a record of what happened rather than something to work on.
Evaluators read the same call differently
Two people scoring the same conversation often land a little apart. Without a way to compare them, the difference tends to surface only when an agent asks about it.
Contact reasons stay out of view
The score describes how a conversation was handled. It says rather less about why the customer got in touch, or which of those reasons is growing.
One platform, the whole quality program
From the first recording to the coaching conversation it leads to, and every audit trail in between.
How a conversation becomes coaching
Five steps. The AI does the listening and the first pass; your team does the judging.
The conversation arrives
Upload a recording, paste a chat, or have your dialer push them in through the API. Calls, chats and email all become the same kind of record.
It becomes text
Speaker-labelled, in the language it was spoken, with card numbers and identifiers masked before the text is stored. Chats and emails skip this step — they are already text.
The model answers your scorecard
Question by question, quoting the passage behind each answer, and flagging anything the conversation did not actually settle.
An evaluator signs it
They read the draft, change what they disagree with, and submit. The evaluation is theirs, and the changes are recorded.
It turns into something
A number on the dashboard, a dispute if the agent objects, a data point in the next calibration, and a line in that agent's coaching plan.
Two engines, and we are specific about which does what
Language runs on Google Gemini Enterprise. Everything acoustic, and every masking rule, runs on infrastructure we operate ourselves — no second AI vendor, and no third party holding your audio.
Multimodal
It reads audio and text in the same pass, so transcription and analysis come from the same understanding of the call.
Strong reasoning
It follows a scorecard the way a person does — weighing what was said against what your criteria actually ask for.
Answers from evidence
It is asked to answer only from what the transcript shows, and to mark a question as unverified rather than guess. Low hallucination, and candid when the evidence is not there.
Always the latest model
We move to the newest model as soon as it is available to us, so accuracy improves with no work on your side.
Teams running quality on Mira
Where the people running quality programs on the platform are, as a share of the total.
Built for the way your team actually works
The same platform, with a different definition of a good conversation. Choose the one closest to your own operation.
Your conversations do not leave your control
Sensitive data is masked the moment a transcript exists — before it is stored, before it is scored, before anyone sees it — and the untouched text is never written down at all.
Your data is yours
The audio of your calls, the transcripts produced from it and the resulting analysis belong exclusively to your organization.
Never used for training
We guarantee your data is NOT used to train Google's AI models or anyone else's. Your conversations do not improve the public models other customers use.
Isolated and encrypted
Everything is processed in an isolated environment and travels encrypted, both in transit and at rest, meeting the industry's highest security standards.
An evaluator with AI is worth more than a faster evaluator
The point is not to review the same calls in less time. It is to review far more of them, act on the same day, and recover the hours that actually change behavior.
Several times more evaluations
Teams using AI-assisted scoring review a multiple of what they could reach by hand in the same hours — a sample that finally represents the whole team rather than a handful of calls a month.
Feedback the same day
When scoring stops being the bottleneck, an agent hears about a conversation while they still remember it. Feedback weeks later is a report; feedback today is coaching.
Hours back for coaching
The time an evaluator spends listening is time not spent with the agent. Giving that back is where the return actually is — coaching changes behavior, scoring only measures it.
A human always decides
Every AI-scored evaluation is reviewed by a person before it is submitted, and the model flags anything the transcript did not prove. The AI drafts; your team signs.
Gains depend on your call volume, scorecard length and how much of your audio is transcribable. We will size it with you honestly before you commit.
See it on your own calls
Book a walkthrough of the software. Send us a few recordings and your current evaluation form; we load them into Mira scores so you can watch the platform score your own calls, side by side with the scores your team assigned.
A live walkthrough of the platform with a person, usually within one business day.