The platform
Voice agents interview everyone in parallel and run a validated instrument inside the conversation. From there the platform protects the people in it, attributes the result to a cause, sets it against your sector, and hands leadership ranked fixes with owners and a date.
Agents hold the conversation, administer the validated scale inside it, and score as they go. Thousands of calls at once.
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The agent speaks and listens. Scale items are read exactly as published and scored as they are answered, so the structured result exists the moment the call ends. Scoring and probing are the same loop, which is what lets a measurement instrument run as a conversation.
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There is no interviewer to schedule and no queue, so coverage is a question of how many people accept rather than how many slots exist. Everyone is reached, including shift workers and the teams a sample would have missed, and the protocol is byte for byte the same in every call.
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The two accent blocks are the mechanism. A high score inside the scale block decides which questions the probing asks next, which is how a number becomes a reason. The scored block sits early on purpose, so someone who stops halfway still counts.
A spoken conversation. People talk instead of typing, so you get the texture of an interview at the coverage of a census.
The scale, word for word. Fixed items, fixed order, identical in every call, which is what keeps waves comparable.
Scored during the call. Factor scores exist as the conversation runs, and they decide what gets probed next.
Any language, any hour. Each language version validated rather than machine translated. Employees pick their own slot.
A link, nothing to install. No account, works on a phone, and a partial session still contributes a scored result.
Unlimited concurrency. Fieldwork length is set by how fast people accept, not by interviewer availability.
The reason people answer honestly, built as architecture rather than policy.
"Marta asked me to rerun the Grupo Nabeiro renewal through CoPilot on the 3rd, and I spent most of Thursday checking the figures it produced against the originals."
Renewal processing in this team carries a verification step of roughly half a day per case. The pattern appears in 7 of 9 interviews across the function.
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Names, clients, systems and dates are stripped on ingest. The specific incident is abstracted into a described pattern, so the finding survives and the fingerprint does not. Nobody at the employer can request the left hand side.
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Groups below the floor are never rendered, and the floor does not move on request. The same check runs on combinations, because three filters that each pass can still isolate one person. Exec team is suppressed here for exactly that reason.
Audio discarded at once. Speech becomes text during the call and the recording is never retained, so no voiceprint exists to hold.
Stripped on ingest. Before anything is analysed, not before anything is shown.
Transcripts structurally isolated. No employer facing path exists. It is not a permission.
Intersection checks. Combined filters tested, not each one alone.
Full audit log. Every report, every access, timestamped and exportable.
Where a score becomes a cause you can assign to someone.
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Displaced work only appears if you interview across the handoff. A sample of one team would have reported a 41% gain and nothing else.
Two of these quadrants look identical in a usage dashboard, because both show low activity. They need opposite responses, and only asking people tells them apart.
The attribution split. Four trigger levels, so what you caused sits apart from what you inherited.
Verification tax. Checking and re prompting time, quantified rather than assumed.
Shadow AI inventory. What people use unofficially, which is where real demand shows.
Joined to your own metrics. Cycle times, rework rates, ticket volume, seat utilisation.
Context, because a score on its own is not a judgement.
You see the spread and your place in it, never which organisation is which dot. Matching is on sector, headcount, rollout stage, tool category and deployment age.
Sector and size matched. Compared against organisations that look like yours.
Wave over wave. Your own trajectory, which usually matters more than the percentile.
Distribution, not identity. You see the spread, never who is in it.
Grows with every engagement. The benchmark is the asset that makes year three sharper than year one.
Matched against a library of known patterns, never generated from scratch.
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Colour is the evidence tier, never confidence dressed up as certainty. A hypothesis is labelled as one and ships with a way to test it. Ranking is expected effect over effort, filtered by what you can actually do this quarter.
Pattern matched, not invented. An LLM asked to suggest improvements produces fluent, generic advice. This does not do that.
A named owner on everything. Exec, line manager, ops, IT or L and D. Unowned means unimplemented.
Honest expected effect. Over promising on wave one destroys wave two.
Human sign off. Nothing reaches a client without a person approving it.
Three audiences, three outputs, and a measurement that closes the loop.
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Lower is better. Two rows here did not improve, and they are reported exactly as plainly as the three that did. The last one was never implemented, which is recorded separately so a recommendation nobody actioned is not counted as one that failed.
Leadership readout. Delivered live. The discussion in the room is half the value.
Manager packs. Only for teams above the threshold, limited to what that manager controls.
Employee summary. What people said and what leadership committed to. This is what makes wave two honest.
Implementation rate, reported separately. So inaction is never mistaken for ineffectiveness.
Administration
The people who have to approve this are rarely the people who bought it. Each of them can check it themselves.
Single sign on. SAML and OIDC, least privilege by default.
Scoped roles. Programme owner, analyst, manager and auditor each see a different surface.
Data residency selection. Choose the region before fieldwork opens.
Retention controls. Set the deletion schedule and watch it execute.
Audit export. Every report and access, timestamped.
Employee representative portal. Method, de identification design and sample outputs, available before fieldwork rather than after.
Sub processor register. The current list, with 30 days notice before it changes.
Deletion on request. Honoured even though nothing is stored against a name.
Integrations
Findings are stronger joined to numbers your organisation already trusts. Everything below also works as a CSV, so nothing blocks a first engagement.
Limits
Design decisions, not gaps in a roadmap. Each exists because the alternative would make the measurement worthless or the product harmful.
There is no per person output. Not restricted, not permissioned, not available on request. Build it and nobody answers honestly again.
No keystrokes, no screen time, no message reading, no telemetry on a person. We ask people and aggregate the answers.
Agents work from what people say, never from how they sound. Inferring emotional state from voice in a workplace is a prohibited practice under the EU AI Act, and the recording is discarded during the call regardless.
It will not rank people for redundancy or justify a specific dismissal. Findings describe work, not workers.
We diagnose and recommend. Implementation stays with the people who know the organisation, which is also what makes the re measurement honest.
Design partners
The quickest way to judge whether this fits is a conversation about the deployment you already have running, and what your usage data is failing to explain.