Product AI agent · Synthetic research
Synthetic Research Persona AI Agent
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.
- Typical delivery
- 4–6 weeks
- Deployment
- Your stack
- Named owner
- Label first
- After launch
- Agent Care
What this agent does
Answers in a voice, never as a finding
In
- 01
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
- 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.
Goes to the named researcher to accept.
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 required
8 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 boundary
Agent 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 persona
Illustrative example- Persona
- Enterprise security buyer
- Answer
- Would push back on the seat-based rise
- Grounding
- Synthetic, generated
- Evidence of record
- Win-loss notes, 2 June 2026
- Confidence
- Held unaccepted
- Held for
- The named researcher, by name
As received
Taken from the transcripts on file — the persona is a construct, and this sentence was said by no one.
What the record holds
- Interview transcripts
- Win-loss notes
- Survey wave
Why no finding here
Turning a synthetic answer into a finding is a named researcher call.
What the score decides
Below the threshold an answer picks up a research lead read before the researcher sees it.
Action
AcceptAppend evidenceSend to research reviewValue
Where AI adds value
The same four claims, placed at the point in the workflow where each one applies.
Where the value lands
Value 01 – 04
Every answer
From the corpus behind it
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.
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.
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.
Build 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 repositories
- Dovetail
- Condens
- EnjoyHQ
- Tagged transcripts and study notes
Survey and panel data
- Qualtrics
- SurveyMonkey
- Fielded waves and raw responses
Win-loss and CRM records
- Salesforce
- 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 signals
- Zendesk
- Intercom
- Productboard
- Tickets and logged user feedback
Observability & evaluation
- OpenTelemetry
- Langfuse
- Supported monitoring/evaluation sources
Integration availability depends on the client's existing systems and API access.
Agent controls
Six stamps between the persona and the deck
Six stamps on one page, the last the deepest. What is passed on is set out in the map below.
L6 · Outermost — last line of defence
Inward → L1 · closest to the model
- L1 – L2
- Test whether an answer may stand
- L3
- Leaves the finding to a named researcher
- L4 – L5
- Keep the answer and the label behind it
- L6
- Refuses to answer in voice when signals degrade
How Nestack evaluates it
Evaluate the whole run — not only the answer that comes out.
Coverage runs the whole depth of the workflow, and every layer is cut by slice.
Surface — the answer a deck carries
- E1Final-output evaluationDid the answer carry the real research it was actually built on?
- E2Step-level evaluationDid the agent read the right studies, the right segment and the live persona?
- E3Tool evaluationDid it read and write the correct persona and the correct run?
- E4Confidence calibrationDo low-confidence answers actually attract more researcher corrections?
- E5Slice evaluationHow does performance change across specific persona classes?
- E6Business outcomeHow many answers needed a correction before the researcher accepted?
Floor — the corpus an answer rests on
Failure modes
Where each failure originates in the agent
Seven failure modes, set at the stage each one first becomes visible.
Agent lifecycle
Direction of processing →
01 · Retrieval
1 mode
- QL-03
Stale corpus read
The studies read are not the ones now on file.
Stage gathers
The studies, the waves, the segments and the notes
02 · Reasoning
2 modes
- QL-04
Answer given beyond the corpus
A view is voiced that no study on file supports.
- QL-06
Persona read as a population
One construct is taken for a segment speaking.
Stage proposes
The persona, the grounding and the run spread
03 · Tool / write
2 modes
- QL-02
Thin run passed forward
An answer moves on without the lead read.
- QL-05
Answer bound to wrong persona
The answer is filed under another segment.
Stage writes
Only where write access and approval policy allow it
04 · Output
1 mode
- QL-01
Label stripped in export
The answer reaches a deck with nothing marking it.
Stage returns
The answer a deck carries and a room reads
05 · Change / Version
1 mode
- QL-07
Silent persona drift
A persona widens while the stored answers keep the old one.
Stage tracks
Model, prompt, persona rules and corpus dates
- Sev-1 · a synthetic quote reaches a customer
- Sev-2 · an unlabelled answer reaches a deck
- Sev-3 · corpus degrades, answer held back
Affected slices
Small B2B segments absorb the corrections
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 aggregate
Illustrative 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 threshold
2 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 stages
Switchback — the path turns at Improve and returns at Learn
- 01
Detect
Correction rate rises on small B2B persona classes.
- 02
Diagnose
The sentence in the deck that reads like a customer and was said by nobody is worked backwards until one cause is left standing.
- 03
Improve
Numbered changes leave, with the runs that prompted them attached beneath.
- 04
Verify
One red labelling case is enough to hold the whole release.
- 05
Learn
It is kept permanently, and the labelling rules change in that same commit.
Learn → Detect
The 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.
Workstream
Week 1Week 2Week 3Week 4Week 5Week 6
- 01Corpus discovery and automation-boundary definition.Week 1
- 02Transcript, survey and CRM sources.Week 1, Week 2
- 03Transcript-to-persona and grounding-coverage mapping.Week 1, Week 2
- 04Research corpus ingestion.Week 2
- 05Persona, corpus and segment binding.Week 2, Week 3
- 06Grounding scoring and review routing.Week 3
- 07Researcher acceptance workflow.Week 3, Week 4
- 08Repository and deck integration.Week 5
- 09Labelling and grounding cases.Week 4, Week 5
- 10Guardrails and export controls.Week 4
- 11Run-trail instrumentation.Week 5, Week 6
- 12Deployment, documentation and Agent Care handover.Week 6
12 workstreams · 6 weeks · bar shows the weeks a workstream is active — several run in parallel
Final 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 tier | PilotOne persona, one round | ProductionProduction research workflow | AdvancedMultiple 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 price | From $5,000 | From $8,000 | Custom quote |
- Final build price
- Confirmed after discovery based on integrations, workflow complexity, corpus volume, approval controls and deployment requirements.
- Separate from build
- Build 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 bring
We build with it
01Your real studies and the segment each one covers
→Corpus capture and persona grounding
Week 102Representative transcripts, waves and win-loss notes
→Corpus binding, persona logic and the grounding baseline
Week 203Your research calendar and the people it names
→Grounding rules, labelling rules and the automation boundary
Week 104Access to relevant APIs, feeds or exports
→Repository, panel and CRM source assessment, then integration setup
Week 205Answers you would not want attributed
→Grounding cases and the evaluation round
Week 406What no persona may stand for
→Grounding scoring, review routing, guardrails and release controls
Week 307A named researcher who accepts the finding
→Release to the named researcher, then pilot and production validation
Weeks 5–6
Nothing else is required
Deployment, 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.
Phase
W1
W2
W3
W4
W5
W6
- DiscoveryW1
- BuildW2 – W3
- EvaluateW4 – W5
- Pilot & LaunchW5 – W6
Week focus
W1Corpus discovery, grounding rules and the automation boundary
W2Source integration and the ground-truth baseline
W3Persona construction, answer logic and release controls
W4Evaluation suite, grounding cases and failure-mode testing
W5Repository integration, pilot runs and targeted corrections
W6One research round run under the insights owner, then Agent Care handover
- Reading the band
- A bar runs across the weeks its own work is named for, and week five carries two by design.
- At the end of W6
- Once the labelling record validates, Agent Care assumes the agent.
- Duration
- Six-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.
- Typical delivery
- 4–6 weeks
- Deployment
- Your real studies
- Named owner
- Label first
- After launch
- Agent Care available
Nestack Agents · Synthetic research
AGT-PRD-08 · Agent Care available after launch