AI Search Visibility Agent

What this agent does

Samples the answer, never claims the cause

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

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

Reason

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

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

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

Decide

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

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

Out

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

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

AgentHuman

1Prompt panel runNamed assistants, a fixed prompt panel, repeated runs and the window they were taken in

2Spread establishedThe runs taken, the answers returned, how far they differed and the model version each ran under

3Movement tested against varianceThe movement observed, the spread it sits inside and whether a repeat run reproduces it

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▼

6Publication and disclosure records updatedOnly where write access and the publication policy allow it

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 required8 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 boundaryAgent 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 panelIllustrative example

Assistant

Recorded as

Prompt

Sample of record

Confidence

Held for

Consumer assistant, retrieval-backed

Answer varied across the runs

Spread, not a rate

Run record, 3 August 2026

Held unadopted

The named editor, by name

As receivedDrawn 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 hereCalling a movement an effect is a judgement a named editor makes.

ActionAdoptAdd runsHold for senior read

What the score decidesBelow the configured run count the read gets a senior look before the editor 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

Any answer sampledFrom 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.

04Build 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 assistantsConsumer and enterprise assistants
Answers, citations and runs

Your own web estateCMS · site and asset store
Published text and its editor

Sampling infrastructureRun 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 recordsEditorial register · release log
Named editors and their timestamps

Observability & evaluationOpenTelemetry · 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 defenceInward → 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 – L2Test whether a read may be published

L3Leaves the causal call to a named editor

L4 – L5Keep the answer and the run behind it

L6Reports 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

Depth of coverage ▼

E1Final-output evaluationDid the read carry the run count and the spread it was drawn from?

E2Step-level evaluationDid the agent ask the right prompts, on the right assistants, in the right window?

E3Tool evaluationDid it sample the correct assistant and store the correct run?

E4Confidence calibrationDo low-confidence reads actually attract more editor corrections?

E5Slice evaluationHow does performance change across specific assistant classes?

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 lifecycleDirection of processing →

01 · Retrieval1 mode

UB-01

Rewrite that loses retrieval

Text tuned for the generator falls out earlier.

Stage gathersThe prompts, the answers, the runs and the window

02 · Reasoning2 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 assemblesThe runs, the spread and the model versions

03 · Tool / write2 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 writesOnly where release access and records policy allow it

04 · Output1 mode

UB-06

Read quoted without its runs

One number travels on, the spread does not.

Stage returnsThe read a comms team and a board are given

05 · Change / Version1 mode

UB-07

Silent model swap

The endpoint changes and earlier reads stop matching.

Stage tracksModel, 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 aggregateIllustrative example

Slice	Failure rate	Lift	Status
Retrieval-backed assistants	10.2%	3.7×	Review
Long-tail buyer prompts	7.2%	2.6×	Review
Non-English prompt panels	4.5%	1.6×	Watch
Fixed-corpus test harness	2.0%	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 stagesSwitchback — the path turns at Improve and returns at Learn

01Detect

Correction rate rises on retrieval-backed assistants.

02Diagnose

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

03Improve

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

04Verify

A single unreproduced movement case stops the whole read publishing.

05Learn

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

Learn → DetectThe 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

01Prompt-panel scope and the automation-boundary map.

02Assistant, prompt and run sources.

03Answer-attribution and run-reproducibility mapping.

04Answer-run ingestion.

05Prompt, assistant and run binding.

06Spread scoring and editor routing.

07Editor adoption workflow.

08Publication-record integration.

09Reproducibility and sampling cases.

10Guardrails and sampling 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 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 prompt panel, one cycle ProductionProduction reporting workflow AdvancedMultiple 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 price From $5,000 From $8,000 Custom quote

Final build priceConfirmed after discovery based on integrations, workflow complexity, assistant coverage, sampling 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 live prompts and the assistants they are asked on → Prompt-panel capture and run schedulingWeek 1

02Representative assistants, prompts and windows → Source binding, sampling rules and the run baselineWeek 2

03Your publication calendar and the editors it names → Panel mapping, sampling rules and the automation boundaryWeek 1

04Access to relevant assistant APIs or exports → Assistant, prompt and run-store assessment, then integration setupWeek 2

05Numbers you would not want re-run → Repeat-run cases and the failure roundWeek 4

06What no read may claim caused it → Editor routing, adoption holds, guardrails and release controlsWeek 3

07A named editor who adopts the read → Release to the named editor, then pilot and production validationWeeks 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 W1W2W3W4W5W6

Discovery W1

Build W2 – W3

Evaluate W4 – W5

Pilot & Launch W5 – 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 bandEach bar spans only the weeks its own work is named for, and week five carries two by design.

At the end of W6When the run record validates, Agent Care picks the agent up.

DurationSix-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.

Discuss this agent →

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