PR has the least forgiving error surface in professional services. A consulting memo with a wrong fact embarrasses a firm in front of one client. A press release with a wrong fact embarrasses the client in front of everyone, permanently, screenshotted before the correction is drafted. Communications work is public by design, which means every AI-assisted shortcut in the drafting process is a shortcut taken in front of an audience.
And PR teams are taking those shortcuts, rationally, because the volume demands it: statements, briefing docs, Q&As, bylines, crisis holding lines, all faster with AI. The tension is that speed serves communications right up until the moment a fabricated detail, a stale figure, or a mischaracterized position ships under a client’s name. The fix is not less AI. It is a review layer built for work that cannot be quietly corrected later.
The most dangerous errors in comms work are the plausible ones: the founding year that is off by two, the product claim that was true last quarter, the executive quote that paraphrases a position the executive never took. These survive review because they sound right. Grounding drafts in the client’s own Evidence Base, the fact sheets, prior releases, approved messaging, position statements, turns “sounds right” into “traces to the approved document,” claim by claim, with citations a reviewer can click rather than trust.
Per-client workspaces carry the rest of what makes agency work survivable: this client’s voice, their banned phrases, the competitors never to name, the topics that are off-limits. The rules apply to the work automatically, which matters most at exactly the moments comms teams are weakest, at volume, on deadline, with the account lead on another call.
A public statement gets adversarially read the moment it publishes: by journalists, by critics, by the client’s competitors. The Multi Model Stress Test is a rehearsal of that scrutiny: three independent models read the same draft claims against the same evidence, and the Conflict Heatmap flags where they diverge, which is a reliable proxy for where a skeptical reader will push. The claim one model hedges on is the claim a journalist calls to check. Better to be the one who found it Tuesday than the one explaining it Thursday.
Comms already runs on approvals: nothing ships without the account lead, and often the client, signing off. The gap is that those approvals live in email threads that prove nothing later. Qonera makes the approval structural: gated review where the stakes demand it, a named reviewer recorded with a timestamp, annotations where the reviewer added the context that made a line safe, all inside the review and approval workflow, all landing in a tamper evident audit trail.
That record earns its keep twice. Internally, it is how an agency proves its own process when a release goes sideways and the postmortem starts, because “who approved this” has an answer instead of an argument. Externally, it is becoming a pitch asset: clients burned by AI mishaps elsewhere are starting to ask agencies how AI-assisted work is checked, and the agency that answers with a process and a record sounds different from the one that answers with reassurance. In a business where the product is the client’s reputation, being able to show the care is very nearly the same thing as the care itself.
Multi-model stress testing, Conflict Heatmap, tamper-evident audit trail, and structured sign-off, built for teams who need defensible AI output.