Orion Confidential · May 2026
Official Audit Report

Algebra Bernays
in the AI Era

AI-Search Visibility · University & Program Discovery

Prepared exclusively for Algebra Bernays University · Zagreb
Strictly confidential This document is prepared solely for Algebra Bernays University. Distribution to third-party vendors, competitors, or external parties is strictly prohibited without written consent from Orion.
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ChatGPT
Where can I study a bachelor's in AI and data science in Europe, taught in English?
ChatGPT
Ask anything
Algebra Bernays — 0 mentions An accredited university with MIT and Goldsmiths partnerships is invisible to AI.
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Algebra Bernays in the AI Era

Algebra Bernays University
Simón Aguía · Orion
13 May 2026
Institution + 5 programs

01 · What is GEO

The search moment has moved upstream

Generative Engine Optimization is the practice of making an institution visible, accurate, and well-cited in the answers produced by AI search engines: ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude, Copilot.

This is not SEO

SEO optimizes for a ranked list of blue links. GEO optimizes for inclusion in a synthesized answer — typically one or two paragraphs that name a small set of institutions. The competitive question is no longer "where do I rank?" It is "am I one of the universities the AI named at all?"

The scale is real and accelerating

ChatGPT crossed 700 million weekly active users in Q1 2026. Perplexity crossed 35 million MAU. A growing share of prospective students now ask an AI engine to shortlist programs before they ever reach a ranking site or a university's own page — increasingly in their own language.

"AI citation share is becoming the leading indicator of enrollment-inquiry share."

When an AI engine answers a discovery question — "where can I study a bachelor's in AI in Europe in English?" — it composes an answer from three layers: the training corpus, real-time web search retrieving a small set of authoritative sources, and structured entity graphs. An institution can be invisible in any one of these layers. Algebra Bernays, as the audit shows, is suppressed across all three.

02 · Real-Time Citation Probe

We asked AI where to study AI in Europe. Algebra did not appear. Then we found out why.

We asked "Where can I study a bachelor's in AI and Data Science in Europe, taught in English?" through gpt-5.1 with live web search — the current ChatGPT-generation model. It named a clear shortlist. Algebra was not on it.

gpt-5.1 + web search — "bachelor's in AI & Data Science in Europe, English-taught"
Universitat Ramon Llull — La Salle Barcelona— BSc AI & Data Science
University of Stuttgart— BSc AI & Data Science
University of Bamberg— BSc AI & Data Science
Leiden University— BSc Data Science & AI
Maastricht University— BSc Data Science & AI
PSL Paris · FHNW Switzerland · CentraleSupélec— AI / Data Science BScs
Algebra Bernays University — not mentioned

So we probed each authority source AI engines trust, by name. The result explains the absence — and it is not what we expected.

Authority source What the model actually returned for "Algebra Bernays University" Recognized
QS World University Rankings"not listed… However, Algebra University College is listed."no
Times Higher Education"not listed… Algebra University College in Croatia is listed."no
Croatian Ministry (MZO)"not listed… two separate institutions — Algebra University College and Edward Bernays University College — are mentioned."no
Wikipedia"no dedicated article… no such institution."no
StudyInCroatia (regulator)"listed… in the Institutions in the Spotlight section."yes
0
Discovery-question mentions Across the questions Algebra's programs are built to answer, the institution is named zero times. AI engines have no authoritative entity called "Algebra Bernays University" to surface.
2 names
The authority is real — under retired names QS, Times Higher Education, the Ministry registry and EduRank all carry Algebra's history — filed under Algebra University College and Edward Bernays College. The rebrand severed the link. The engines treat the current name as unknown.

03 · Headline Score

8 out of 100 — and the authority AI does see is filed under the wrong name

Orion's education GEO pipeline scored Algebra Bernays and five flagship programs against the same 27-dimension rubric. Every program returned the same near-floor result, for the same reasons: a firewall that blocks AI crawlers, and a rebrand that AI engines never registered.

ProgramLevelURL auditedScore
Data Science & AIBScalgebra.hr/.../data-science-and-artificial-intelligence/≈ 8 / 100
Software EngineeringBScalgebra.hr/.../software-engineering/≈ 8 / 100
CybersecurityMScalgebra.hr/.../cybersecurity/≈ 8 / 100
Digital MarketingMScalgebra.hr/.../digital-marketing/≈ 8 / 100
Computer & Data ScienceJoint PhDalgebra.hr/.../joint-doctoral-study-programme.../≈ 8 / 100

Five identical scores is itself a finding. Every program page shares one template and sits behind one firewall configuration. This is one problem to solve, not five — a single program of work lifts the entire catalog at once, and any new program added later inherits the fix.

Benchmark — how the score breaks down by layer

University of Amsterdam · peer reference
readable · cited · reachable
64
Reputation · Algebra L2
EduRank + StudyInCroatia + press name the current entity
26
Reachability · Algebra L4
robots OK · firewall blocks bots
45
Readability · Algebra L1
7
7
Content readiness · Algebra L3
0 — firewall blocked the fetch
0

All scores produced by Orion's education pipeline against the live site. The firewall block zeroed the content layer and triggered a 0.5× penalty on the composite — pre-penalty 16, final 8.

04 · Audit Findings

Top 12 issues identified across the institution

Ranked from lowest to highest impact. Items 10–1 are available in the full engagement briefing. Issue #12 alone is actionable today — it is one setting in a dashboard.

12
TechnicalCritical
The firewall blocks the AI crawlers that robots.txt explicitly allows — one setting halves the entire score
Algebra's robots.txt welcomes every major AI crawler. The Cloudflare configuration blocks them anyway. When we tested with the real user agents AI engines use, 0 of 5 got through: GPTBot, ClaudeBot, OAI-SearchBot, PerplexityBot, Google-Extended were all blocked at the network layer. This fires the cloudflare_waf ×0.5 penalty that halves the composite, and it is why the content-readiness layer scored zero — the auditor, like the AI engines, never reached a single page. This is almost certainly unintentional: Cloudflare's "AI Scrapers" rule was switched on without anyone realizing it overrides the site's own robots.txt.
Allowlist the AI crawler user agents in the Cloudflare WAF / bot-management rules. This is one change in a dashboard. It removes the ×0.5 penalty and lets AI engines read the content the institution already publishes — visible lift within the first week, before a single line of schema is written.
11
TechnicalCritical
Program pages carry no Course, Offer, credential, or FAQ schema — AI engines see generic web pages, not programs
Every audited program page emits only the CMS default WebPage / BreadcrumbList markup. There is no EducationalOccupationalProgram, no Offer (tuition), no educationalCredentialAwarded, no cohort dates, and no FAQPage. The readability layer scored 7 of 100. The content is good; the machine-readable signal is absent.
Author one program-page schema template — Course / EducationalOccupationalProgram with Offer, credential, language, and cohort dates — and apply it across the catalog. Brings per-program readability from near-floor to the high band in one pass, and any new program inherits it.
10
StrategicCritical · highest leverage
The rebrand stranded the institution's authority — AI engines know the predecessor names, not "Algebra Bernays University"
Algebra merged and rebranded its predecessor institutions — Algebra University College and Edward Bernays College — into Algebra Bernays University. AI engines never registered the change. We probed each authority source by name; the verdict was the same every time — the current name is not recognized, but a predecessor name is, treated as a separate institution. These are verbatim model responses:
QS World University Rankings
"not listed… However, Algebra University College is listed."
no
Croatian Ministry of Science (MZO)
"not listed… two separate institutions — Algebra University College and Edward Bernays University College — are mentioned."
no
Wikipedia
"no dedicated article… no such institution."
no
Reconnect the current name to its legacy authority: sameAs + alternateName schema to the predecessor names, a Wikipedia entity with redirects from Algebra University College / Edward Bernays College, and update requests to QS, Times Higher Education, EduRank and the MZO registry. This is the single highest-return move — every other fix builds on a name the engines do not yet recognize.
9
TechnicalMedium
No llms.txt and no discoverable sitemap
The site returns 404 for llms.txt and declares no sitemap in robots.txt, so AI engines have no manifest of what to read or where to find it.
Publish an llms.txt summarising the institution and its programs, and declare an XML sitemap in robots.txt. Low effort, immediate reachability lift.
8
ContentMedium
No structured FAQ on any program page
Prospective-student questions (tuition, language, entry requirements, cohort dates) are answered nowhere in extractable text. The Direct-Answer bucket scores zero.
Add a static Q&A block with FAQPage schema to each program template, covering the highest-volume applicant questions.
7
ContentMedium
Program outcomes and curriculum not exposed as machine-readable evidence
Learning outcomes, faculty credentials, and curriculum detail live in prose and PDFs AI engines do not parse, so the content-readiness layer has nothing to extract.
Restructure program pages with clear headings, outcomes lists, and teaches/educationalLevel fields once the firewall is reopened.
6
AuthorityHigh
No Wikipedia entity the engines can cite
Algebra is mentioned softly but has no Wikipedia article cited as an entity — the dominant grounding source for AI knowledge graphs.
Seed a properly sourced Wikipedia article for the institution, citing accreditation, partnerships, and independent coverage.
5
AuthorityHigh
Absent from the AI-research network the engines weight for AI programs
For "best AI program" queries the engines lean on ELLIS, research-group, and publication signals, where Algebra has no presence.
Pursue ELLIS-style network presence, faculty workshop placements, and AI-program comparison-content citations.
4
AuthorityHigh
Only one press release surfaced across the citation probe
The reputation layer rests almost entirely on the regulator signal; the press surface is thin, leaving rankings and editorial coverage underweighted.
Run a quarterly press sequence on the partnership constellation and accreditation milestones.
3
TechnicalCritical
provider.sameAs chain entirely missing at institution level
There is no Organization block, so no machine-readable link from "Algebra Bernays" to MIT, Goldsmiths, Microsoft, ISC2, or the Ministry — the highest-leverage readability gap.
Author the institution EducationalOrganization block with the full sameAs graph as the first schema deliverable.
2
StrategicCritical
Authority does not propagate from the institution to the program pages
Even the reputation Algebra has earned does not reach the program pages where applicants decide, because the entity graph that would carry it does not exist.
Connect the entity graph so parent-institution authority lifts every program page automatically.
1
StrategicCritical
Firewall block + empty schema compound to a 13/100 floor
The 0.5x firewall penalty and the near-zero readability layer reinforce each other: content the engines cannot reach cannot be read, and content with no schema cannot be understood even when reached. The result is a 13/100 score and zero discovery-question citations.
Resolve the firewall and ship the schema templates first — they are the prerequisite to every authority and content fix in this list.
9 issues identified beyond what's shown

The full audit is ready.

Issues 9 through 1 — including the critical-severity findings — are covered in detail in the engagement kickoff. Each comes with priority sequencing, effort estimates, and owner assignments.

Schedule the kickoff →

05 · Targets

What winning looks like in 12 months

Conservative against the headroom the audit identifies. Aggressive against the current baseline of 13.

Metric Today 6-month 12-month
Overall AI-search visibility 8 45–55 65–70 — peer / top-tier band
AI recognizes "Algebra Bernays University" as the entity No — predecessor names only Name linked to legacy authority Recognized + cited under current name
Readability (structured data) 7 60 80+
Reputation AI engines see (current name) ~26 45 75 — Wikipedia + AI-research presence
AI crawlers reaching the content 0 of 5 5 of 5 5 of 5, sustained
Share of AI answers naming Algebra on discovery questions ≈ 0% +20 pp +35 pp — regional shortlist
Presence on "AI / data-science program" questions Absent Emerging Named in the regional shortlist
The admissions cycle is the marker. The autumn intake is the peak of AI-search demand from prospective students. The firewall and schema work ships well inside that window; the reputation track carries into the following cycle, where the full 12-month curve is in place.

06 · How Orion Helps

Measurement first. Everything else follows.

Orion is a Generative Engine Optimization platform purpose-built to measure and improve AI-search visibility at the institution level. The audit in this document was produced end-to-end through Orion's education pipeline against the live site.

Track 1 · Weeks 1–4 · highest leverage

Entity reconnection

Link the current name to its legacy authority: sameAs + alternateName schema to the predecessor names, a Wikipedia entity with redirects, and update requests to QS, THE, EduRank and the MZO registry.

Track 2 · Weeks 1–8

Reachability + readability

Cloudflare AI-crawler allowlist, llms.txt and sitemap (removes the 0.5× penalty), then one EducationalOrganization block and a program-page schema template across the catalog.

Track 3 · Months 1–6

Reputation building

Wikipedia entity seeding, a quarterly press sequence on the partnership constellation, and an AI-research-network presence plan.

Track 4 · Monthly

Measurement & iteration

Weekly re-audit across the same programs with score deltas and the next-highest-leverage fix surfaced automatically. Citation share tracked per question cluster.

The engagement

ScopeInstitution + flagship program catalog (5 programs audited, extensible)
DiagnosticThis audit in full, data exports, and a working session with your operator and academic-communications leads
Entity reconnection (lead)sameAs + alternateName to predecessor names · Wikipedia entity + redirects · QS / THE / EduRank / MZO update requests
Reachability fixCloudflare allowlist · llms.txt · sitemap
Readability buildEducationalOrganization graph · program-page schema template
Reputation trackWikipedia entity · quarterly press · AI-research presence
Continuous re-auditWeekly, with citation tracking on discovery questions
Monthly platform fee€1,500 / month
Commitment12 months
Year-one total€18,000
Annual prepay option€16,200 — 10% discount

Let's talk

The window is open.
Pick a time that works for you.

30 minutes with Simón. We'll walk through the findings shown above, confirm the scope, and tell you exactly what the first two weeks of the engagement look like — starting with the one-setting firewall fix.

Prepared by
Simón Aguía
Orion · useorion.ai
Email
simon@useorion.ai
Prepared for
Algebra Bernays University
Zagreb, Croatia