Fixed query panel
A stable set of buyer questions, markets and engines used across repeated runs so movement is comparable rather than anecdotal.
White-label AI search
Measure the answers. Then change what earns them.
For agencies that want a real AEO/GEO service without pretending a monitoring dashboard is the implementation.
A visibility score tells you where the client appears. It does not decide which questions matter, why a competitor is cited, which source can be influenced or whether the site change shipped correctly.
The short answer
What is white-label AI-search delivery?
White-label AI-search delivery helps an agency measure and improve how a client is named, cited and recommended across a fixed set of answer-engine questions. LOKAL combines query design, source mapping, entity and page work, implementation QA and repeatable reporting under the agency’s brand.
A visibility score tells you where the client appears. It does not decide which questions matter, why a competitor is cited, which source can be influenced or whether the site change shipped correctly.
What reaches your client
Delivery you can inspect before you put your name on it
Source and citation map
The domains and exact pages appearing around the client, classified by authority, relevance and whether an intervention is realistic.
Entity and technical repair
Organisation, service, person, place, page ownership, schema and internal-link inconsistencies corrected where they obstruct a coherent entity.
Answer-ready page work
Question headings, complete first-sentence answers, evidence, comparisons and commercial handoffs written into the page that owns the intent.
Influence plan
A prioritised mix of owned-page changes, proof, mentions and source relationships based on source weight and attainability.
Named, cited, recommended report
Repeated results separate whether the client is mentioned, receives a source citation or is actually recommended. Runs and cited URLs stay in the record.
Operating workflow
Who does what, and when
- 01
Lock the panel
Agree the questions, buyer, market and engines before anyone reports a baseline.
- 02
Map the sources
Record the answers, cited URLs, competitor framing and source patterns across repeat runs.
- 03
Ship interventions
Prioritise the page, entity, evidence or third-party source changes LOKAL and the agency can actually influence.
- 04
Repeat without moving the goalposts
Run the same panel, record named/cited/recommended share and explain what changed without treating one screenshot as a trend.
What you can verify
Proof with the edges left on
CCA-F
Claude architecture capability
LOKAL has Claude Certified Architect — Foundations capability. That credential supports technical judgement; it does not imply Anthropic endorses the engagement.
Founder-level
OpenAI community participation
LOKAL’s founder is a member of the OpenAI Champions Network. LOKAL is not described as an OpenAI partner.
Monitor + intervene
A defensible tooling boundary
Commercial tools can monitor AI visibility. LOKAL’s service adds query design, source mapping, account strategy, QA and implementation around the monitoring.
Before we start
The boundary is part of the service
- AEO, GEO and AI SEO are consolidated here; they are not split into three near-duplicate services.
- Traditional crawl, indexation and organic-search ownership remains on the principal white-label SEO page.
- A single answer-engine screenshot is not reported as a durable citation win.
- No platform, citation or recommendation outcome is guaranteed.
- One consolidated page owns white-label AEO, GEO and AI SEO; new variants need a genuinely different buyer job before they earn another URL.
Read the partner-protection rules before you register an account.
Questions agency owners ask before the first account
Is AEO different from GEO and AI SEO?
The labels overlap heavily in current buying language. LOKAL treats them as one AI-search delivery service at launch and separates a page only when the search intent and commercial work are genuinely different.
Can software do this without an agency?
Software can run prompts and monitor visibility. It does not choose the commercially useful panel, resolve source opportunities, rewrite the right page, coordinate implementation or own the QA and account decision.
How is AI-search performance reported?
The fixed panel separates named, cited and recommended outcomes across repeated runs. The report records the engine, answer, cited URL, competitor framing and any material run variance.
What does white-label AI-search delivery cost?
The current public range is USD 1,500–8,000 per client per month. The final fee depends on the query panel, markets, source work, implementation load, reporting cadence and client-facing support.
Does this replace SEO?
No. Technical search health, indexation, page ownership and link structure still matter. The AI-search service adds answer-engine measurement, source analysis and citation-oriented interventions around that foundation.
Can the service run under our agency brand?
Yes. Reports, decks and client communication follow the registered account’s white-label mode, while the agency retains commercial ownership and final approval.
A useful first call
Bring one account, one deadline and the part your team cannot absorb
We’ll review the brief before the call. You’ll speak with someone responsible for delivery, not a qualifier reading a script.