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PR AI agent · AI search visibility

AI Search Visibility (GEO) Agent

Influence a system that publishes no rules and answers differently each time it is asked: sample the prompt across repeated runs, report the spread, and leave the published text to a named editor.

Typical delivery
4–6 weeks
Deployment
Your stack
Named editor
Spread first
After launch
Agent Care

What this agent does

Samples the answer, never claims the cause

In

  1. 01

    A prompt is asked many times over, and the answers are kept apart rather than merged into one.

  2. 02

    An answer moves, and the spread it moved inside is written beside it before anyone calls it a gain.

Reason

  1. 03

    A brand attribute comes back wrong in a minority of runs, and that minority is kept, not smoothed.

  2. 04

    An asset is published, and the person holding editorial responsibility for it is recorded that day.

  3. 05

    A text is drafted to inform the public, and it leaves disclosed or it leaves over a named editor.

Decide

  1. 06

    An assistant returns nothing about the company, and the silence is filed as a result, not a gap.

  2. 07

    A model version changes under the panel, and reads taken before it stop being comparable.

Out

  1. 08

    A run cannot be reproduced, and the irreproducibility is the finding rather than a defect to hide.

  2. 09

    Publish assets only within the release boundaries agreed during implementation.

Product statement

Sampling, the run record and the spread belong to the agent. Editorial responsibility belongs to a named editor, who holds it for the text and carries it afterwards.

Example workflow

One visibility read, prompt to adoption

  1. 1Prompt panel runNamed assistants, a fixed prompt panel, repeated runs and the window they were taken in
  2. 2Spread establishedThe runs taken, the answers returned, how far they differed and the model version each ran under
  3. 3Movement tested against varianceThe movement observed, the spread it sits inside and whether a repeat run reproduces it
  4. 4Controls appliedRun-count checks, version checks, citation checks and sampling confidence

No human action required

Stages 1 to 4 run unaided, and nothing is published or claimed at any of them — the agent is sampling, and the editor lane opens at the adoption gate.

5DecisionSplits at the adoption gate
Movement reproduced across runs

Goes to the named editor to adopt.

Anything inside the spread

Adds a senior read first.

Editor review

The read is held with its runs, its spread and the model version behind each answer.

Adopt · Add runs · Hold for senior read

Adopted — by the named editor

  1. 6Publication and disclosure records updatedOnly where write access and the publication policy allow it
  2. 7Outcome evaluatedRun-count adequacy, version currency, editor corrections and what the review found

Corrections

Each editor correction is counted in the evaluation.

What should not run autonomously

Human approval stays in control

Outside the boundary — human approval required

8 items

  • Adopting a visibility read into a board pack.
    • Holding editorial responsibility for a text.
    • Deciding a published asset moved an answer.
    • Signing off a claim about AI visibility.

  • Automation boundary

    Agent acts unaided

    • ✓Run the prompt panel again and keep each run apart.
    • ✓Report the spread a movement sits inside rather than a single rate.
    • ✓Record the model version behind each answer the panel returned.
    • ✓Hold a public-interest draft for the named editor.

    Article 50(4) accepts a company; nothing publishes here except over a named human.

    • Judging whether a movement is real at all.
    • Telling a board that a read is repeatable.
    • Choosing which prompts stand for the market.
  • Changes to the panel, the runs or the rules.

Example output

One visibility read, annotated

This serves a comms team who may have to show, later, what a visibility claim rested on. Regulation (EU) 2026/1744 left Article 50(4) standing but deleted the Article 50(7) implementing-act power, and Article 50 sits in the middle penalty tier, not the top one.

Visibility read · single prompt panel

Illustrative example
Assistant
Consumer assistant, retrieval-backed
Recorded as
Answer varied across the runs
Prompt
Spread, not a rate
Sample of record
Run record, 3 August 2026
Confidence
Held unadopted
Held for
The named editor, by name

As received

Drawn from repeated runs against one named assistant, and it asserts nothing about why an answer moved.

What the read holds

  • Runs taken
  • Model version
  • Citations returned

Why no adoption here

Calling a movement an effect is a judgement a named editor makes.

What the score decides

Below the configured run count the read gets a senior look before the editor sees it.

Action

AdoptAdd runsHold for senior read

Value

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

Any answer sampled

From the assistant that returned it

03Spread

What the read may claim

The agent does not claim a place or a share, because neither exists; it records the prompt asked, the assistant that answered, how many runs were taken and how far those runs differed.

01Approved path

It will not answer twice

The only live duty runs backwards: since 2 August 2026, AI Act Article 50(4) binds the deployer, not the engine, to disclose machine-written text published to inform the public.

02Human review

What was searched for, and not found

Federal full-text search returns nothing for generative engine optimization, nothing for large language model and nothing for answer engine, while artificial intelligence and search engine both return hits, so the controls work. No regulator defines, audits or certifies visibility in an answer.

04

Build an evidence trail

The prompt, the answer it returned and the run that produced it stay together.

Integrations

Typical integrations

Five system groups connect to the same agent. Which of them are in scope is decided in discovery.

  • Generative assistants

    • Consumer and enterprise assistants
    • Answers, citations and runs

  • Your own web estate

    • CMS
    • site and asset store
    • Published text and its editor

  • Sampling infrastructure

    • Run schedulers
    • sample archives
    • Repeated runs and the spread found

Agent

AI answer sampling and run control

  • Reads the answers
  • Repeats the runs
  • Holds for the editor

  • Publication records

    • Editorial register
    • release log
    • Named editors and their timestamps

  • Observability & evaluation

    • OpenTelemetry
    • Langfuse
    • Supported monitoring/evaluation sources

Integration availability depends on the client's existing systems and API access.

Agent controls

Six probes between the answer and the read

Six probes on one bench, the last the sharpest. What repeats is drawn in the map below.

L6 · Outermost — last line of defence

Inward → L1 · closest to the model

L6Rollback / safe modeNarrow the agent to raw run capture when sampling or evaluation signals degrade.Roll back
L5Version monitoringTrack model, prompt and sampling rules, and note the version each answer was returned under.Track
L4TraceabilityRecord each read, the runs beneath it, the assistants that answered and each read of the file.Record
L3Editor releaseHold the read for a named editor; the hold governs release, not whether the movement is real.Gate
L2Sampling guardrailsTest each read against its configured run count, and refuse a claim drawn from a single draw.Restrict
L1Confidence thresholdsRoute a thin or contested sample to a senior read before the figure leaves the team.Require review
Model coreRead assembled — the prompts, the runs, the spread and the model versions behind them
L1 – L2
Test whether a read may be published
L3
Leaves the causal call to a named editor
L4 – L5
Keep the answer and the run behind it
L6
Reports the spread and no single number when signals degrade

How Nestack evaluates it

Evaluate the whole sampling run — not only the read that comes out.

Coverage runs the whole depth of the workflow, and every layer is cut by slice.

Surface — the read a comms team circulates

  1. E1Final-output evaluationDid the read carry the run count and the spread it was drawn from?
  2. E2Step-level evaluationDid the agent ask the right prompts, on the right assistants, in the right window?
  3. E3Tool evaluationDid it sample the correct assistant and store the correct run?
  4. E4Confidence calibrationDo low-confidence reads actually attract more editor corrections?
  5. E5Slice evaluationHow does performance change across specific assistant classes?
  6. E6Business outcomeHow many reads needed a correction before the editor adopted?

Floor — the runs a read rests on

Failure modes

Where each failure originates in the agent

Seven failure modes, each at the stage where it first surfaces.

Agent lifecycle

Direction of processing →

  1. 01 · Retrieval

    1 mode

    • UB-01

      Rewrite that loses retrieval

      Text tuned for the generator falls out earlier.

    Stage gathers

    The prompts, the answers, the runs and the window

  2. 02 · Reasoning

    2 modes

    • UB-02

      Lift inside run variance

      A movement smaller than the spread reads as a gain.

    • UB-03

      Minority answer dropped

      A false attribute shows in few runs and is smoothed.

    Stage assembles

    The runs, the spread and the model versions

  3. 03 · Tool / write

    2 modes

    • UB-04

      Instruction text published

      The asset carries injection text on your own domain.

    • UB-05

      Public-interest text unowned

      It went live with nobody holding editorial responsibility.

    Stage writes

    Only where release access and records policy allow it

  4. 04 · Output

    1 mode

    • UB-06

      Read quoted without its runs

      One number travels on, the spread does not.

    Stage returns

    The read a comms team and a board are given

  5. 05 · Change / Version

    1 mode

    • UB-07

      Silent model swap

      The endpoint changes and earlier reads stop matching.

    Stage tracks

    Model, prompt, sampling rules and run dates

  • Sev-1 · publishes text nobody owns
  • Sev-2 · a single draw reaches the board
  • Sev-3 · runs too few, read held back
See the complete Public Relations failure-mode catalogue

Affected slices

Retrieval-backed assistants absorb the corrections

A panel-level visibility figure can read clean while the retrieval-backed assistants take most of the corrections. Nestack reports the correction rate by assistant class, not only in total.

Slice performance — reported separately, not only in aggregate

Illustrative example
SliceFailure rateLiftLift vs. thresholdStatus
Retrieval-backed assistants10.2%3.7×Review
Long-tail buyer prompts7.2%2.6×Review
Non-English prompt panels4.5%1.6×Watch
Fixed-corpus test harness2.0%0.7×Normal

Bar: correction-rate lift vs. fixed-corpus baseline · scale 0–4.0× · tick marks the 2.0× review threshold

2 of 4 slices over threshold

Evidence-linked improvement

What one unreproduced movement costs

A loop closes when the movement no repeat run reproduces is a standing case. That suite is what the next visibility read is measured against.

Improvement cycle · five stages

Switchback — the path turns at Improve and returns at Learn

  1. 01

    Detect

    Correction rate rises on retrieval-backed assistants.

  2. 02

    Diagnose

    The lift that showed last month and will not show today is worked backwards until one cause is left standing.

  3. 03

    Improve

    Number the read; the runs that produced it are filed beneath it.

  4. 04

    Verify

    A single unreproduced movement case stops the whole read publishing.

  5. 05

    Learn

    One case joins the suite, one line joins the sampling rules.

  6. Learn → Detect

    The return edge. The next read 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, sampling control, evaluation, integration, then production validation and handover.

Workstream

Week 1Week 2Week 3Week 4Week 5Week 6

  1. 01Prompt-panel scope and the automation-boundary map.Week 1
  2. 02Assistant, prompt and run sources.Week 1, Week 2
  3. 03Answer-attribution and run-reproducibility mapping.Week 1, Week 2
  4. 04Answer-run ingestion.Week 2
  5. 05Prompt, assistant and run binding.Week 2, Week 3
  6. 06Spread scoring and editor routing.Week 3
  7. 07Editor adoption workflow.Week 3, Week 4
  8. 08Publication-record integration.Week 5
  9. 09Reproducibility and sampling cases.Week 4, Week 5
  10. 10Guardrails and sampling controls.Week 4
  11. 11Run-trail instrumentation.Week 5, Week 6
  12. 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 tierPilotOne prompt panel, one cycleProductionProduction reporting workflowAdvancedMultiple assistants / markets
Introduced at Pilot
Read assembly to your prompt panels✓✓✓
Named editor adoption✓✓✓
Prompt-panel baseline✓✓✓
Introduced at Production
Reporting by assistant class—✓✓
Editor review workflow in your systems—✓✓
Approved publication write-back—✓✓
Sampler-and-store integration—✓✓
Introduced at Advanced
Multi-assistant reconciliation——✓
Cross-market read packs——✓
Large run archives——✓
Multi-assistant sampling controls——✓
Build priceFrom $5,000From $8,000Custom quote
Final build price
Confirmed after discovery based on integrations, workflow complexity, assistant coverage, sampling 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.

  1. 01Your live prompts and the assistants they are asked on

    Prompt-panel capture and run scheduling

    Week 1

  2. 02Representative assistants, prompts and windows

    Source binding, sampling rules and the run baseline

    Week 2

  3. 03Your publication calendar and the editors it names

    Panel mapping, sampling rules and the automation boundary

    Week 1

  4. 04Access to relevant assistant APIs or exports

    Assistant, prompt and run-store assessment, then integration setup

    Week 2

  5. 05Numbers you would not want re-run

    Repeat-run cases and the failure round

    Week 4

  6. 06What no read may claim caused it

    Editor routing, adoption holds, guardrails and release controls

    Week 3

  7. 07A named editor who adopts the read

    Release to the named editor, 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

Two of these phases genuinely share week five, and no band was stretched to tidy the column up.

Phase

W1

W2

W3

W4

W5

W6

  1. DiscoveryW1
  2. BuildW2 – W3
  3. EvaluateW4 – W5
  4. Pilot & LaunchW5 – W6

Week focus

W1Panel discovery, sampling rules and the automation boundary

W2Assistant integration and the prompt-panel baseline

W3Run control, spread scoring and release controls

W4Evaluation suite, repeat-run cases and failure-mode testing

W5Publication-record integration, pilot reads and targeted corrections

W6One sampling cycle run under the comms owner, then Agent Care handover

Reading the band
Each bar spans only the weeks its own work is named for, and week five carries two by design.
At the end of W6
When the run record validates, Agent Care picks the agent up.
Duration
Six-week plan shown · typical delivery 4–6 weeks depending on scope confirmed in discovery.

Next step · AI search visibility

Build an AI search visibility agent around the run count your last visibility number never carried.

Show us one prompt your buyers ask and the last visibility figure you were given. Arriving without a run count or an interval, it is one draw reported as a fact. The FTC set aside its own Rytr order on 22 December 2025, docket 232-3052.

Typical delivery
4–6 weeks
Deployment
Your live prompts
Named editor
Spread first
After launch
Agent Care available

Nestack Agents · AI search visibility

AGT-COM-07 · Agent Care available after launch

Build an AI search visibility agent

Four questions so the call starts from your actual setup — then pick a time that suits you.

About you
Your prompts

No obligation. We’ll map the workflow, name the automation boundary and tell you if an agent is the wrong answer.