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AI Brand Integrity Audit

AI shapes the first impression people have of your business
It builds that impression from sources most companies have never reviewed

AI draws from directories, databases, press archives, and citation networks — not just your website.
An audit maps exactly what those sources say about your services, your positioning, and your reputation.

Asteriada is a research-driven marketing agency with 22 years of experience across strategy, digital growth, and brand representation.

See what AI says about firms like yours → How the audit works
Before audit
ChatGPT Outdated services
"[Clinic] offers general practice and walk-in consultations. Appointments can be made by phone."
Reality: Specialist clinic with online booking only — AI sourced from a directory listing 3 years out of date.
Gemini Identity confusion
"[Firm] is an accounting practice founded in 2009, offering bookkeeping for sole traders."
Reality: Founded 2018, corporate clients only — conflated with a different firm sharing part of the name.

What AI currently says about businesses like yours

The Problem

This happens to well-run businesses
Because AI systems don't work the way most companies assume

Your website is one input, but AI builds answers from multiple external sources. And older, more-cited sources frequently outrank newer, more accurate ones.

The categories of error we find most consistently:
Outdated information Identity confusion Wrong category Missing from relevant queries Fabricated details

How AI systems build business descriptions, and what determines how: read our guide →

What this means commercially

AI misrepresentation affects growth and trust

AI now shapes how potential clients discover, evaluate, and trust your business during high-intent research.
Even strong businesses can lose visibility, credibility, and opportunities when AI systems misunderstand their positioning, category, or relevance.

Wrong category or audience

AI may place your firm in the wrong service category entirely. Buyers asking for a specialist find a generalist. Buyers asking for your specific service don't find you at all.

Identity confusion

Businesses that share a name, location, or service area with another firm are frequently conflated. AI may combine details from both, producing descriptions that misrepresent each.

Outdated positioning

AI draws from sources that were accurate at the time of indexing. A rebrand, a location change, or a service pivot may not be reflected for months — or at all — if the underlying source infrastructure hasn't been updated.

Missing from high-intent queries

When a buyer asks an AI assistant who handles a specific problem in a specific location, weak entity representation means your firm isn't named. The query is answered. You're not in the answer.

Our Approach

A structured diagnostic, not a search session

What makes this different from running a few prompts? →

01

Capture

We query six platforms across multiple prompt types. We map the full output pattern — the complete picture of how your business is described.

02

Diagnose

Each finding is assessed for accuracy, completeness, consistency, and source origin. We identify what is wrong and which source is causing it.

03

Prioritise

We prioritise by commercial impact — what a prospective client encounters at the point of decision, and what is most likely to influence their choice.

04

Deliver

A written report with exact platform outputs, root cause for each finding, and a sequenced action plan — each item with a named owner and expected outcome. The Advanced Audit adds a 30-day retest.

How we work

Asteriada combines 22 years of experience across strategy, research, and digital marketing to build structured, evidence-based marketing systems designed for real implementation

Meet the team behind the work →

✓
One-time engagement — fixed scope, fixed price, no retainer
✓
Findings in 5–10 working days from briefing
✓
Six platforms tested: ChatGPT, Gemini, Claude, Perplexity, Grok, DeepSeek
✓
Every finding includes a root cause, not just a description of the problem
✓
Every recommendation includes an owner, a sequence, and an expected outcome
✓
Implementation designed to be executable without external agencies
Example Findings from Our Audits

How real businesses are represented

Each card shows the exact AI output, the source of the error, and the business consequence.
Two named cases are published with client consent.
Two are anonymised, covering finding types that appear consistently across professional services audits.

Identity Confusion
DIABOLIQUE bar, Belgrade
Five of six platforms either confused DIABOLIQUE with bars of the same name in Moscow, Saint Petersburg, Kazan, Paris, and Italy, or declined to answer confidently. Only Grok identified the venue correctly.
What caused itThe name is shared by venues across multiple cities. With no authoritative source anchoring the correct location — no website, no schema markup, no structured directory listings — AI systems defaulted to whichever version of the name had the most citation weight.
Business consequenceA guest asking any major AI platform about DIABOLIQUE Belgrade received either wrong information or no information. The venue was effectively invisible or misidentified on five of six platforms.
FixEstablish an official website with location schema, standardise directory listings across all major platforms, and build citation authority through verified external references.
Missing Contact Data
Hotel Constantine the Great, Serbia
Perplexity and DeepSeek retrieved direct contact information at 44–48% accuracy. DeepSeek generated an incorrect address.
What caused itContact data existed on the website but was not structured for machine extraction. DeepSeek, facing an information gap, generated a plausible-sounding address rather than returning no answer.
Business consequenceGuests who asked AI for booking contact details either received nothing or received the wrong address. For a hospitality business, this is a direct conversion failure at the moment of highest intent.
FixSchema.org Hotel markup on the website, audit and correction of external listings and directories, and standardised social media naming across platforms.
Category Misclassification
Anonymised — strategy consultancy, Cyprus
"A general marketing agency offering campaign management and social media services."
What caused itThe homepage led with delivery-focused services. The firm's strategic positioning existed only in content AI did not treat as authoritative. The highest-cited external sources described the delivery work, not the strategic work.
Business consequenceTarget clients — founders and senior executives seeking strategic guidance — encountered a description that placed the firm in the wrong competitive category before any contact was made.
FixHomepage restructure to lead with positioning, entity schema, and one authoritative external citation establishing the strategic practice.
Fabricated Facts
Anonymised — professional services firm, EU
"[Firm] was founded in 2019 in Amsterdam and raised Series A funding for its enterprise logistics platform."
What caused itLow citation authority created an information vacuum. With insufficient verified sources to draw from, AI generated plausible-sounding details — founding date, location, funding history — with apparent confidence.
Business consequenceFalse facts discoverable by any buyer who conducts basic due diligence. Particularly damaging in professional services, where verifying a firm's background before engagement is standard.
FixWikidata entry, Crunchbase profile, and 2–3 authoritative external citations establishing verified facts.
Audit Packages

One missed client covers this cost
The audit tells you whether you are missing them

The two packages differ in scope and depth, not in quality of analysis.
Both deliver a complete diagnostic with root causes and a remediation plan designed to be executed internally.
Most corrections can be handled by a marketing manager or office administrator working from the roadmap.

Starter

€350

5 working days

For single-location businesses or firms wanting a focused first look

  • Six platforms tested, 5–7 queries each
  • Full misrepresentation report with root cause for each finding
  • Prioritised action plan
  • 60-minute consultation
  • 2 weeks email support
Request your audit →
Advanced

€700

10 working days

For multi-location businesses or firms wanting a documented before-and-after and a deeper implementation plan

  • Six platforms tested, 10–12 queries each
  • Full representation scoring across all findings
  • Detailed implementation plan with owner assignment
  • 30-day retest against the same prompt set
  • 60-minute consultation
  • 2 weeks email support
Request your audit →

Not sure which package fits? Speak with us first →

The action plan is written for internal execution. If you would prefer Asteriada to handle the implementation, that is available as a separate service. Ask about our implementation service →

Questions

What to know before you request an audit

The engagement
Can we improve how AI systems describe our business?+
Yes, but it takes time. We can accurately identify existing issues, explain why they occur, and recommend actions that are highly likely to improve how your brand is represented. Many companies begin to see the first improvements within 4–8 weeks after implementing the recommendations.
Do we need to hire someone to implement the recommendations?+
In most cases, no. The majority of corrections — structured data updates, directory standardisation, content adjustments, Wikidata entries — are executable by a marketing manager or office administrator working from our roadmap. We design the action plan to be implemented without specialist technical knowledge or external agencies. Where a specific fix requires technical involvement, we say so explicitly.
How quickly will we see results after implementing changes?+
It depends on the type of change and the platform. Structured data corrections and directory updates typically surface in AI outputs within 2–4 weeks. Changes that require building citation authority — Wikidata entries, external references — take longer: 6–10 weeks is a realistic expectation. The 30-day retest in the Advanced Audit gives you a documented comparison against the same prompt set used in the original audit.
Is there any ongoing commitment after the audit?+
None. Both packages are one-time engagements with a fixed scope and a fixed price. You receive your findings, your roadmap, and two weeks of email support for implementation questions. No subscription, no retainer, no ongoing obligation. Some clients return for a re-audit 6–12 months later to track progress — that is entirely their choice.
Which businesses need this most?+
Professional services firms where trust and accurate representation are commercially critical: law firms, medical clinics, accountancy practices, financial advisors, specialist consultancies. Also, businesses that have recently changed name, location, ownership, or service focus in the past two to three years — where outdated signals may still dominate AI outputs despite a current, accurate website.
The methodology
Is this the same as SEO?+
No. SEO affects where your website ranks in search results. This concerns what AI systems say when they generate a direct answer about your business — a different mechanism that relies on entity authority, citation networks, structured data, and positioning clarity across external sources. Some corrective actions benefit both. The problems and solutions are not the same.
Why would AI get our business wrong if we have an accurate, current website?+
Because AI systems don't read your website as their primary source. They synthesise from directories, third-party databases, press archives, and citation networks — weighting sources by authority and consistency, not recency. A directory listing from three years ago that contradicts your current website will frequently outweigh the website itself. Your website matters, but it is one input among many.
We're a well-established firm. Surely AI has accurate information about us?+
Prominence on Google does not translate directly to accurate AI representation. Established firms are frequently misrepresented — particularly those that have changed services, location, or positioning in recent years, or whose name is shared by another business. The audit findings on this page are from established, professionally managed firms. None considered themselves at risk before the audit.
Can't we check this ourselves?+
You can query individual platforms — but a meaningful audit requires consistent methodology: the same prompt set applied across all six platforms, evaluated against defined criteria, with root cause diagnosis for each finding. A self-conducted check produces snapshots. Without a framework for interpreting what you find and identifying what's causing it, the snapshots don't tell you what to do. That's the gap the audit fills.

Let's discuss the project!

hello@asteriada.com
+357 24 022488
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