Fresenius Medical Care.
A working dialysis-center finder that closes on a paper form, not a treatment intake.
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 Medical Care, 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 world's largest dialysis network that ends on a contact form.
We asked five kinds of AI agent to find a Fresenius Medical Care dialysis center in Munich for a hemodialysis patient, then reach a registration path. The plain reader fetched nephrocare.com and got a partial render, center names loaded, therapy-type filtering did not. The coding agent reached more structure but lost the HD-versus-PD distinction. The browser navigated to NephroCare München-Ost Neuperlach, confirmed HD and Online-HDF as offered treatment types, found the holiday-dialysis path, and landed on a generic contact form. ACT completed the same handoff.
One label, many breeds. From a plain reader to an autonomous operator, the kinds behind ChatGPT, Perplexity, and Claude Code:
Scope. This is one therapy type at one center. Fresenius Medical Care operates 4,100+ dialysis centers worldwide across hemodialysis, peritoneal dialysis, and home therapies, each with its own intake 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 Medical Care?
Fresenius Medical Care 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 Medical Care'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 Medical Care.
On specialised healthcare-facility discovery, NephroCare is not lacking a center finder, the patient-facing surface reaches the right center with the right therapy type when the agent runs a browser. It is losing on two layers. Text and code agents miss the HD-versus-PD distinction because therapy filter renders JS-side. And the handoff that should carry "hemodialysis patient in Munich needs intake" drops to a generic contact form, dropping the treatment context that took the agent four steps to establish.
The fix is not redesigning the patient portal. It is publishing a treatment-typed intake path the agent can reach with context preserved: Reference Pages per center carrying center + treatment types + intake URL with treatment parameter pre-filled, Answer Pages for "Wo Dialysezentrum für X in Y?", a structured-data layer over the contact form so the treatment context survives the handoff.
The proof is not a new intake form. It is plain readers and coding agents extracting "NephroCare München-Ost, HD + Online-HDF, intake URL with hemodialysis pre-selected" directly, alongside the existing browser path, re-measured each wave.
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No intermediary stands between agents and Fresenius Medical Care. 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 NephroCare's own contact form, so the close-state is brand-owned rather than intermediated; the patient discovery competition with KfH and health-insurer 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.
NephroCare München-Ost — hemodialysis patient registration
- Close state
- the booking form
- Bottleneck
- Therapy filter behind JS render; text and code agents miss the HD/PD distinction; browser closes on a generic contact form that drops treatment context.
Fairness note
Wave 5 Q2 2026 audit complete on a single task (NephroCare München-Ost Hämodialyse intake, booking-form-ready close state). AI Visibility from Cody Gate-1 on an unbranded informational probe (Dialysezentrum-München-Anmeldung). 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: NephroCare München-Ost hemodialysis intake across ceiling + http + coding + browser-agent + act breeds. Found JS-rendered therapy filter blocking text/code agents from HD/PD distinction; browser success 3/3 Score 87.3; ACT booking-form-ready on a generic contact form that drops treatment context.
- 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 (Dialysezentrum-München). 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 · FMC 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 · NephroCare phases 1-4 (Giorgio repo)
Internal · Hyperize evidence
- · per-breed access profile (text/code partial; browser success 3/3 Score 87.3; ACT generic contact form Score 89)
- · JS-render finding (center identity at HTTP, therapy filter only after JS)
- · generic-contact-form ACT (treatment context dropped at handoff)
- [S3]Accessed · 07 Apr 2026
Ground-truth ceiling run · NephroCare München-Ost Hämodialyse
Internal · Hyperize evidence
- · Ground-truth center (NephroCare München-Ost Neuperlach)
- · Treatment-type verification (HD + Online-HDF + holiday dialysis path)
- Accessed · 24 May 2026
Public · hyperize.ai
- · fairness declaration
- · Third-Party Interception framing
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Task Selection.
The fairness doctrine behind the slate above. Five failure modes, six criteria, public before each wave.
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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.
