Ground each synthetic answer in the real research it was derived from, stamp it so the stamp survives the deck, and hand the finding to the named researcher who owns it.
A persona is built from real studies, and each trait it carries names the study it came from.
02
An answer is generated, and the real research under it travels inside the same block of text.
Reason
03
An answer is stamped synthetic, and the stamp sits inside the sentence, not in a caption beside it.
04
A question reaches past the corpus behind the persona, and the agent declines instead of improvising.
05
An answer is exported, and the label rides into the deck rather than staying behind in the tool.
Decide
06
A segment is small, and the run is flagged as one the published literature says conditioning degrades.
07
A run is repeated, and the spread between runs is reported rather than the tidiest answer of the set.
Out
08
An answer heads for an advertisement, a review or an investor deck, and the export stops at a person.
09
Execute write actions only inside the approval boundaries agreed during implementation.
→Product statement
Generation, grounding and labelling belong to the agent. The finding belongs to a named researcher, who takes it into the decision and owns it there.
Example workflow
One question, corpus to finding
AgentHuman
1Real research receivedInterview transcripts, survey waves, support logs or win-loss notes
2Persona built and boundedThe segment it stands for, the studies under it and the questions it may not be asked
3Answers generated in voiceThe answer, the grounding it rests on, the spread across runs and confidence
4Controls appliedGrounding checks, label checks, out-of-corpus refusal and answer confidence
No human action required
Stages 1 to 4 run unaided, and nothing is a finding at any of them — the agent is answering, and the researcher lane opens at the grounding gate.
5DecisionSplits at the grounding gate
Grounded in the corpus
Goes to the named researcher to accept.
Anything thin
Adds a research lead read first.
Researcher review
The answer is held with its persona, its grounding and the studies it was drawn from.
Accept · Append evidence · Send to research review
Accepted — by the named researcher▼
6Research repository updatedOnly where write access and records policy allow it
7Outcome evaluatedGrounding rate, label survival, researcher corrections and what review found
Corrections
A correction from the researcher is scored in the evaluation.
What should not run autonomously
Human approval stays in control
Outside the boundary — human approval required8 items
Accepting a synthetic answer as a research finding.
Putting a synthetic quote in front of a customer.
Deciding a segment is understood well enough to price.
Substantiating an advertising claim about buyers.
Automation boundaryAgent acts unaided
✓Generate answers in the persona voice on request.
✓Attach the real research behind each answer it gives.
✓Stamp each answer as synthetic before it leaves the workspace.
✓Refuse any question the corpus behind the persona cannot reach.
Nothing becomes a finding except by a named researcher, inside the agreed boundaries.
Judging whether a persona may stand for a segment.
Telling an investor what demand research shows.
Choosing which real study a persona is built on.
Changes to the grounding, labelling or persona rules.
Example output
One synthetic answer, annotated
This serves a product team who may be asked, long afterwards, where a sentence in a deck came from; below is one answer exactly as the agent leaves it.
Synthetic answer · single personaIllustrative example
Persona
Answer
Grounding
Evidence of record
Confidence
Held for
Enterprise security buyer
Would push back on the seat-based rise
Synthetic, generated
Win-loss notes, 2 June 2026
Held unaccepted
The named researcher, by name
As receivedTaken from the transcripts on file — the persona is a construct, and this sentence was said by no one.
What the record holdsInterview transcriptsWin-loss notesSurvey wave
Why no finding hereTurning a synthetic answer into a finding is a named researcher call.
ActionAcceptAppend evidenceSend to research review
What the score decidesBelow the threshold an answer picks up a research lead read before the researcher sees it.
Value
Where AI adds value
The same four claims, placed at the point in the workflow where each one applies.
Where the value landsValue 01 – 04
Every answerFrom the corpus behind it
03Grounding
Where the answer is used
The agent does not vouch for what a persona says, only for the real research it was built from, the question it was asked, and the label the answer leaves with.
01Approved path
Nobody said any of this
A market-research agent checks that a source exists; this one answers in a voice that never did, fluently, and with nobody having lied.
02Human review
What was checked, and not found
No statute requires a synthetic finding to be labelled, and none makes fabricated internal research unlawful. The one enforcement action touching AI-generated consumer voices was set aside in December 2025. The ICC/ESOMAR Code of July 2025 names synthetic persona, and can expel a member.
04Build an evidence trail
The synthetic answer, the real data behind it and the label it carries stay together.
Integrations
Typical integrations
Five system groups connect to the same agent. Which of them are in scope is decided in discovery.
Research repositoriesDovetail · Condens · EnjoyHQ Tagged transcripts and study notes
Survey and panel dataQualtrics · SurveyMonkey Fielded waves and raw responses
Win-loss and CRM recordsSalesforce · HubSpot · Gong calls Deal outcomes and buyer objections
Agent
Synthetic persona research
Reads the corpus Answers in voice Holds for the researcher
Support and product signalsZendesk · Intercom · Productboard Tickets and logged user feedback
A panel-level grounding figure can read clean while small B2B segments carry most of the corrections. Nestack reports the correction rate by persona class, not only across a panel in total.
Slice performance — reported separately, not only in aggregateIllustrative example
Slice
Failure rate
Lift
Lift vs. threshold
Status
Small B2B buyer segments
7.1%
3.7×
Review
Cross-market personas
5.0%
2.6×
Review
New or unfamiliar categories
3.1%
1.6×
Watch
Broad consumer segments
1.5%
0.8×
Normal
Bar: correction-rate lift vs. broad-consumer baseline · scale 0–4.0× · tick marks the 2.0× review threshold2 of 4 slices over threshold
Evidence-linked improvement
What a stripped label costs
A cycle closes when the synthetic quote that reached a deck unlabelled is a case. That suite is what the next panel run is measured against.
Improvement cycle · five stagesSwitchback — the path turns at Improve and returns at Learn
01Detect
Correction rate rises on small B2B persona classes.
02Diagnose
The sentence in the deck that reads like a customer and was said by nobody is worked backwards until one cause is left standing.
03Improve
Numbered changes leave, with the runs that prompted them attached beneath.
04Verify
One red labelling case is enough to hold the whole release.
05Learn
It is kept permanently, and the labelling rules change in that same commit.
Learn → DetectThe return edge. The next run is measured against a suite one case longer.
Typical build scope
Twelve workstreams across six weeks
The build scope read against the delivery timeline. Week structure follows the six-week plan — discovery, sources, persona construction, evaluation, integration, then production validation and handover.
WorkstreamWeek 1Week 2Week 3Week 4Week 5Week 6
01Corpus discovery and automation-boundary definition.
02Transcript, survey and CRM sources.
03Transcript-to-persona and grounding-coverage mapping.
04Research corpus ingestion.
05Persona, corpus and segment binding.
06Grounding scoring and review routing.
07Researcher acceptance workflow.
08Repository and deck integration.
09Labelling and grounding cases.
10Guardrails and export controls.
11Run-trail instrumentation.
12Deployment, documentation and Agent Care handover.
12 workstreams · 6 weeks · bar shows the weeks a workstream is active — several run in parallelFinal scope and sequence confirmed in discovery
Engagement tiers
What each tier includes
Rows are the capabilities named in each tier's scope. Higher tiers include everything below them.
Capability✓ in scope · — not at this tierPilotOne persona, one roundProductionProduction research workflowAdvancedMultiple segments / markets
Introduced at Pilot
Answers grounded in your corpus✓✓✓
Named researcher acceptance✓✓✓
Ground-truth baseline✓✓✓
Introduced at Production
Reporting by persona class—✓✓
Researcher review workflow in your systems—✓✓
Approved write-back—✓✓
Panel-and-repository integration—✓✓
Introduced at Advanced
Multi-corpus grounding——✓
Cross-segment persona packs——✓
Large research corpora——✓
Multi-segment grounding controls——✓
Build priceFrom $5,000From $8,000Custom quote
Final build priceConfirmed after discovery based on integrations, workflow complexity, corpus volume, approval controls and deployment requirements.
Separate from buildBuild pricing is separate from recurring Agent Care, which covers managed monitoring, evaluations, incidents and verified improvements after launch.
What we need from you
What you bring, and what we build with it
Each input maps to a piece of build scope and a week in the delivery timeline.
You bringWe build with it
01Your real studies and the segment each one covers→Corpus capture and persona groundingWeek 1
02Representative transcripts, waves and win-loss notes→Corpus binding, persona logic and the grounding baselineWeek 2
03Your research calendar and the people it names→Grounding rules, labelling rules and the automation boundaryWeek 1
04Access to relevant APIs, feeds or exports→Repository, panel and CRM source assessment, then integration setupWeek 2
05Answers you would not want attributed→Grounding cases and the evaluation roundWeek 4
06What no persona may stand for→Grounding scoring, review routing, guardrails and release controlsWeek 3
07A named researcher who accepts the finding→Release to the named researcher, then pilot and production validationWeeks 5–6
Nothing else is requiredDeployment, documentation and Agent Care handover are ours.
Delivery timeline
Four phases across six weeks
Every band is as wide as its phase costs, so two share week five and nothing was stretched to fit.
PhaseW1W2W3W4W5W6
DiscoveryW1
BuildW2 – W3
EvaluateW4 – W5
Pilot & LaunchW5 – W6
Week focusW1Corpus discovery, grounding rules and the automation boundaryW2Source integration and the ground-truth baselineW3Persona construction, answer logic and release controlsW4Evaluation suite, grounding cases and failure-mode testingW5Repository integration, pilot runs and targeted correctionsW6One research round run under the insights owner, then Agent Care handover
Reading the bandA bar runs across the weeks its own work is named for, and week five carries two by design.
At the end of W6Once the labelling record validates, Agent Care assumes the agent.
DurationSix-week plan shown · typical delivery 4–6 weeks depending on scope confirmed in discovery.
Next step · Product AI agent
Build a synthetic-research agent around the label your last deck never carried.
Show us one segment you would ask a persona about and the studies behind it. What comes back is not a customer, not a finding, and not evidence of what anyone believes. No law requires that sentence to be labelled, so the agent stamps it and a person signs it.
