Fresenius.
A working booking portal that only browser agents can drive end to end.
Found & recommended by AI agents
Search-class agents touched the close in some runs; the full agent-fleet access profile lands in a later wave.
This page measures the commerce lane: can an agent find Fresenius, and once it arrives, transact. Talent, after-sales, procurement, investor and press lanes run on different surfaces and are not yet measured.
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The €0 booking step a browser reaches and a plain reader can't.
We asked five kinds of AI agent to find a Helios clinic in Berlin offering orthopaedic surgery for an ACL reconstruction, then reach an appointment-booking path. The plain reader fetched helios-gesundheit.de and got a partial render, clinic names loaded, department detail did not. The coding agent did marginally better with structured selectors but still missed specialty filtering. The browser navigated to the Berlin-Buch clinic page, clicked Termin buchen, and reached patienten.helios-gesundheit.de/appointments/book-appointment?facility=232 at step 2 of 6, with Orthopädie selectable. ACT completed the same flow.
One label, many breeds. From a plain reader to an autonomous operator, the kinds behind ChatGPT, Perplexity, and Claude Code:
Scope. This is one specialty at one Helios clinic. Fresenius through Helios operates 89 hospitals across Germany with 100+ medical specialties, each with its own department structure and booking path.
Found, and able to transact?
Two questions, measured separately. A brand can be recommended and still un-buyable, or perfectly buyable and never found.
When someone asks an agent to find and order a kit, does it route to Fresenius?
Fresenius comes up about four times in ten. The rest of the time, an agent recommends an alternative first.
Discoverability · 18-datapoint auditOnce an agent is on Fresenius's site, can it place the order?
Search-class agents surface the booking form in some runs; the full agent-fleet access profile lands in a later wave.
Evidence · 70 / 100 A measure of how provable and consistent the result is, grounded in cross-method ground-truth agreement (the methods that ran returned the same price), not a separate measured run. A confidence layer on the two scores above, not a third sales axis.
What this means for Fresenius.
On healthcare-facility discovery, Helios is not lacking a booking portal, patienten.helios-gesundheit.de carries the appointment flow with the right step depth and facility pre-selection. It is losing the agent classes that can't render JavaScript. The clinic finder lands the brand correctly on text-only fetches; the specialty filter and the department detail don't render until the browser does. A patient using a text-only assistant can find "Helios Berlin-Buch exists" but not "Helios Berlin-Buch does orthopaedic surgery."
The fix is not removing the JS render, the patient portal trades off interactivity for it. It is publishing the SSR shadow of the clinic finder: Reference Pages per clinic carrying clinic + specialty + booking URL in plain HTML, Answer Pages for "Welche Helios-Klinik macht X in Y?", a structured-data layer over the booking portal so the appointment endpoint is reachable from a text-only fetcher with the right facility ID embedded.
The proof is not a redesigned portal. It is plain readers and coding agents extracting "Helios Berlin-Buch, Orthopädie, Termin-URL /book-appointment?facility=232" directly, alongside the existing browser path, re-measured each wave.
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The same measurement runs free against your domain: five agent classes, one real buying task, your Agent Success Score in 48 hours, in the exact format of this page.
No intermediary stands between agents and Fresenius. The gap is being found, not the channel.
Channel position derivation on the Wave 5 Cody Gate-1 response texts is queued; the displayed share values are the unmeasured default. The measured task closes at Helios's own booking portal (patienten.helios-gesundheit.de), so the close-state is brand-owned rather than intermediated; the discovery competition with hospital directories will be characterised in the next pass.
Hyperize-selected tasks.
One task from the public sector grid. Task list is frozen before each wave runs.
Helios Berlin-Buch — orthopaedic surgery, ACL booking
- Close state
- the booking form
- Bottleneck
- Department detail hidden behind JS render; text and code agents get clinic identity but not specialty match; browser completes booking portal step 2 of 6.
Fairness note
Wave 5 Q2 2026 audit complete on a single task (Helios Berlin-Buch Orthopädie ACL booking, booking-form-ready close state). AI Visibility from Cody Gate-1 on an unbranded informational probe (Privatklinik-Kreuzband-OP-Berlin). AI Usability from a fleet wave (2026-04-07) full phase 1-4. Fairness Review pending the sector fairness grid.
How the score was produced.
Discoverability is audit-pipeline-derived. 3-provider sample (openai, perplexity, anthropic), 3 query variants per task, 2 runs per variant · 18 valid datapoints scored against a five-state handoff cascade. [S1]
AI Usability is derived from the access-profile above (usability-derivation/v1): how far the best agent reached (close state) modulated by how many agent classes succeeded. The per-class profile is the truth; the score is a reproducible summary of it, not a separate rating. Fleet phases (HTTP / Coding / Browser / ACT) produce the profile. [S2]
Agent Success Score = (AI Visibility × 0.20) + (AI Usability × 0.70) + (Evidence × 0.10)
On a 0–100 scale, displayed 0–10. AI Usability bundles the agent's reach + completion; AI Visibility is audit-derived discoverability. Weighting is public; the per-prompt derivation is not.
Measurement scope
Confidence C · one measured task on a 3-provider track (openai, perplexity, anthropic). Confidence promotes to B with a second task plus a fourth provider on the next wave.
Measurement timeline.
Each wave appends; nothing overwrites. Frozen Wave Rule.
- Entry · 01
07 Apr 2026
Wave · Protocola fleet wave
fleet/measured
First-pass FLEET measurement: Helios Berlin-Buch ACL booking across ceiling + http + coding + browser-agent + act breeds. Found JS-rendered specialty detail blocking text/code agents from full specialty match; browser success 3/3 Score 86.7; ACT booking-form-ready at step 2 of 6 with facility pre-selected.
- Entry · 02
24 May 2026
Wave · ProtocolWAVE-Q2-2026-W5-LIFE-SCIENCES
ars-methodology/v1.1
Wave 5 kickoff. Cody Gate-1 audit running on unbranded informational probe (Privatklinik-Kreuzband-OP-Berlin). AI Usability carried from a fleet wave full phase 1-4 access profile.
Evidence and provenance.
Public methodology references and internal evidence pointers behind every claim above.
- [S1]Accessed · 24 May 2026
Gate-1 audit run · Fresenius Wave Q2 2026 (Cody, unbranded informational)
Internal · Hyperize evidence
- · AI Visibility score (audit-derived, 18 datapoints, 3 providers)
- · AI platforms queried (openai/perplexity/anthropic)
- · close state reached (booking_form_ready)
- [S2]Accessed · 07 Apr 2026
a fleet wave Life Sciences wave · Helios phases 1-4 (Giorgio repo)
Internal · Hyperize evidence
- · per-breed access profile (text/code partial; browser success 3/3 with Score 86.7; ACT booking step 2/6)
- · JS-render finding (clinic identity at HTTP, specialty detail only after JS)
- · booking-form-ready ACT (patienten.helios-gesundheit.de book-appointment URL with facility=232)
- [S3]Accessed · 07 Apr 2026
Ground-truth ceiling run · Helios Berlin-Buch Orthopädie booking
Internal · Hyperize evidence
- · Ground-truth clinic (Helios Berlin-Buch)
- · Department verification (Orthopädie selectable at booking step 2/6)
- Accessed · 24 May 2026
Public · hyperize.ai
- · fairness declaration
- · Third-Party Interception framing
Read the doctrine. Challenge the score. Extend the slate.
Task Selection.
The fairness doctrine behind the slate above. Five failure modes, six criteria, public before each wave.
Read ChallengeDisagree with this score.
Send evidence under public Fairness Review. Failed reviews are documented with the named failure mode.
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Open Surface Run · additive measurement. The Hyperize-selected slate stays frozen; your task gets the same methodology.
SubmitEditorial coverage
The DAX 40 Agent Success Index is a point-in-time snapshot of the agent-success of public digital touchpoints. Results are not statements about product quality, company performance, service quality, or the legal obligations of the brands named. Brand names and logos remain the property of their respective owners and are used solely for identification and reporting purposes in the context of editorial coverage (§ 23 MarkenG, Art. 5 GG).
Brands wishing to respond, engage, or correct a factual error may contact hello@hyperize.ai. Responses received are published in full alongside the findings. Full methodology and editorial-coverage notice: coverage statement.
