Coverage Was Never the Hard Part. Getting an Answer Was.

Inside QEval®’s new conversational analytics layer, and why an agentic AI analyst beats one more dashboard nobody opens.

Agent Guru

The agentic AI analyst inside QEval® that answers plain language questions about your own scored conversations, root cause and all. Every answer is held to the same 94%+ accuracy SLA as the rest of QEval®, dispatching more than 100 trained specialists per investigation. A leader asks why CSAT dropped, gets the driver broken out by brand with the calls that prove it, and turns the finding into a standing report in the same conversation.

• 100+ specialists dispatched per investigation, QEval®’s expert trained model bench, more than any single analyst applies by hand
• 94%+ accuracy SLA, the same contractual standard held across the rest of QEval®, not a looser one for conversational answers
• Under 1% of extracted intelligence currently changes frontline behavior industry wide, the utilization gap Agent Guru is built to close

You already know this moment. CSAT drops. Somebody pulls a report. The report tells you what moved, not why. So you open a dozen call recordings and start reading, hoping the answer is in there somewhere, because it usually is.

That is not analysis. That is archaeology.

Here is the arithmetic behind why the dig always takes so long. A contact center running full interaction coverage captures 100 percent of what happens on the phones. Roughly 15 percent of the intelligence sitting past basic compliance scoring ever gets extracted. About 5 percent of what gets found reaches the person positioned to act on it. Less than 1 percent changes what happens on the next call. The problem was never the ingestion rate. It was the utilization rate. Our industry spent years building better ways to capture every conversation and worse ways to ask them anything afterward.

I have watched that gap get closed by hand, the slow way, more than once. One month, on one account, 22 percent of contact volume turned out to be the same request wearing different words: a receipt that already existed online, nine clicks deep, that customers could not find. Somebody had to go looking, call by call, before the pattern surfaced. It should not take a research project to learn that your own digital experience is generating your call volume.

That is the gap Agent Guru closes.

What is Agent Guru?

Agent Guru is a chat panel inside QEval®, and the word that matters is agentic, not search. Type a plain language question, the kind you would put to an analyst on your own team, and it plans an investigation: dispatches the right specialists, more than 100 of them, each trained on a narrow slice of the problem, and isolates a root cause instead of returning a keyword match.

Ask it like you would ask a colleague

Ask why CSAT dropped this month and it does not hand you a chart. It tells you delivery delay calls doubled and are scoring well below average, breaks that out brand by brand, and pins the specific calls that prove each number. Ask the follow up in the same thread, cut it differently, isolate a queue, and it holds the context. It knows what “that” refers to without you restating the question. Ask it to turn a finding into a standing report for your brand leads and it builds one, citations attached, on whatever schedule you set, until you tell it to stop.

Here is how an answer actually gets built:

1. You ask, in your own words. Anything your scored conversations could answer, compliance to churn, is fair game.
2. It plans the investigation. This is agentic AI doing work a search box cannot: deciding which specialists to dispatch, and in what order.
3. It shows its work. Every answer cites the calls behind it. Open one and read the exact transcript line that earned the claim.
4. You keep the thread. The follow up question inherits everything already established, so the second question is faster than the first.
5. You decide what happens next. It drafts the action. It does not take it without you.

A dashboard chat box against an agentic analyst

Plenty of platforms now let you type a question at a dashboard. A dashboard chat box is still the faster path when you already know which metric to check. What it is not built for is the driver you did not know existed: the delivery delay pattern hiding inside a CSAT number, the one queue quietly dragging a brand average down. That is a different job, and it is the one Agent Guru is built for.

It cites its work, or it says nothing

Every number Agent Guru reports comes from the same deterministic scoring your calls already get, held to the same 94%+ accuracy SLA as the rest of QEval®. There is no second, looser standard for a conversational answer. And when the evidence underneath a question is thin, it says so instead of filling the gap with something plausible. A tool that will not tell you when it does not know is worse than no tool at all, because it fails quietly, and you find out later, usually in a meeting where the wrong number already made the rounds.

None of this runs through a third party model, and none of it leaves your tenant. PII is redacted at ingest, before any model, generative or otherwise, ever reads a transcript. If your compliance team’s first question is where the data goes when someone asks it a question, the answer is nowhere. It stays exactly where your calls already live.

Two doors into the same record

Agent Guru is not the only way in. Underneath it sits the Operator Hub: every transcript, searchable and filterable by date, campaign, branch, duration, or phrase, for the times you would rather sit with the actual conversation than a summary of it. Most sessions use both. Start wide with a question, then open the hub when you want to read the call yourself instead of taking the analyst’s word for it. That is still faster than the dozen recordings you used to open by hand, and now you know which dozen to open.

Built for the person who owns the number

Here is what Agent Guru is not. It is not a floor tool, and it was not built to be one. Seats are strategic licenses for the people who own the outcome: operations leaders, compliance owners, QA leadership, not an agent mid call. And it does not act past a line you draw. Every action carries a tier: reports and digests run on their own, changes like routing or bulk edits wait for a person to approve, and anything that reaches an agent or a customer directly never happens without one.

That is a design choice, not a limitation. An analyst that can investigate anything is worth nothing if you cannot also trust what it decided not to do on its own. Vendor neutral is the position we hold on architecture. Bounded is the position we hold on autonomy. Both are on purpose.

The conversations were always the record. Agent Guru is not a bigger dashboard sitting on top of them. It is the analyst headcount you never got approved to hire, one that has already read everything, cites everything, and reports to you instead of the other way around.

Five questions worth asking any conversational analytics vendor

1. Does it cite the specific calls behind every answer, or only a number?
2. Does it hold context across a follow up question, or does each question start over?
3. When the evidence is thin, does it say so, or does it answer anyway?
4. Does anything it drafts reach an agent or a customer without a person approving it first?
5. Where does the data go when someone asks a question, and is anything redacted before a model reads it?

Frequently asked questions

What is Agent Guru?

Agent Guru is the agentic AI analyst inside QEval®. It reads every scored conversation your operation has and answers plain language questions about them, with the calls that prove each answer cited and clickable.

What changes in the QEval® platform we already use?

Nothing. Scorecards, dashboards, reports, and permissions stay exactly as they are. Agent Guru reads the same scored record everyone already works from.

Can Agent Guru make something up?

No. Every number it reports comes from deterministic scoring held to the same 94%+ accuracy SLA as the rest of QEval®. Below a confidence floor, it says it does not know rather than filling the gap with something plausible.

Who should get Agent Guru seats?

Strategic licenses go to the people who own the outcome: operations leaders, compliance owners, QA leadership. It was not built as a frontline or mid call tool.

Does Agent Guru replace a business intelligence dashboard?

Not necessarily. A dashboard is still the faster path to a metric you already know to check. Agent Guru is built for the driver you have not found yet, the one that needs an actual investigation.

Where does the data go when someone asks Agent Guru a question?

Nowhere outside your tenant. There are no third party model calls, and PII is redacted at ingest, before any model reads a transcript.

If you want to see it running against your own calls instead of an illustration, that conversation starts with your account team.