Siemens Healthineers.
Siemens Healthineers owns the MAGNETOM 3T story.
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 two lanes. Commerce: can an agent find Siemens Healthineers, and once it arrives, transact. Talent: can a candidate's agent find an open engineering role on Siemens Healthineers's own career surface and prepare the application. After-sales, procurement, investor and press lanes run on different surfaces and are not yet measured.
Your brand isn't measured yet
What does an AI agent do with your website?
The same measurement as Siemens Healthineers, free for your domain. Five agent classes, one real task, your score in 48 hours.
AI agents find Siemens Healthineers. Hospital procurement awards the contract.
We tested a real purchasing task: specifying a MAGNETOM-class 3T MRI system for a German university hospital. Our audit ran 18 measurements across three AI providers, in German, with zero errors. The full agent-fleet test has not run yet. A follow-up measurement is scheduled.
The agents reach siemens-healthineers.com. The site carries the MAGNETOM Cima.X specification, the clinical evidence for high-field neuroimaging, and the full range: Cima.X for premium neuro, Vida for whole-body, Skyra for productivity. The MR physics spec is machine-readable, as text and as code.
The contract runs elsewhere. Hospital purchasing departments and, in larger clinic networks, group purchasing organizations decide the deal. The agent finds Siemens Healthineers. The buyer's procurement path closes the contract.
One label, many breeds. From a plain reader to an autonomous operator, the kinds behind ChatGPT, Perplexity, and Claude Code:
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 specify a 3T MRI system for a tertiary-care hospital, does it route to Siemens Healthineers?
Siemens Healthineers comes up about a third of the time. The rest of the time, an agent recommends an alternative first.
Discoverability · 18-datapoint auditOnce an agent is on Siemens Healthineers's site, can it issue an RFQ via hospital procurement?
Search-class agents surface a quote in some runs; the full agent-fleet access profile lands in a later wave.
Evidence · 65 / 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.
The talent lane.
A candidate's agent, sent to find an open software-engineering role at Siemens Healthineers and prepare the application. Same brand, second surface: the career portal.
Readable posting, unresolved apply step.
Every HTTP-class and coding-class agent reads the full job posting and requisition fields (title, req-ID, location, employment type, core requirements) directly from the raw HTML response, with no JavaScript rendering required; the application form itself sits behind a client-side-rendered Workday flow that this measurement class cannot inspect.
Furthest close-state reached: spec match · frozen task locked 2026-07-02
The score above is provisional where a class shows untested: untested classes are excluded from the calculation, so the pending check can only confirm or raise the value, never silently lower it.
AI Visibility · in measurement — the audit run for this lane has not landed yet. No Talent-lane composite is shown until both axes are measured.
What this does not yet cover
This measurement did not submit or attempt to submit an application, did not log in, and did not fill any form. Whether the apply flow requires an account/login, what artifacts it demands (CV, cover letter), or how long the form is could not be determined from raw HTML for this Workday-CXS tenant — that requires a rendered (JS/browser) pass, which is out of scope for this HTTP/Coding message class.
Fairness note
This measurement tested one real, open software engineering position (Req R-27513, Dättwil/Baden, Switzerland, locked 2026-07-02) on Siemens Healthineers' own global career site, which uses the same front end and Workday application stack across all locations. AI agents could read the full posting and its requirements directly from the page; the application step itself runs in a client-side Workday flow that the tested agent classes could not inspect, and browser-based agents were not tested. No application was submitted, no form was filled, and no personal data was used; a login requirement is recorded as a fact about the process, not counted as a deficiency.
What this means for Siemens Healthineers.
On product discovery, Siemens Healthineers is not lacking findability. The brand is a top-three global medical imaging OEM, named in every 3T MRI question alongside GE HealthCare and Philips Healthcare. The gap is not the brand-own surface. It is the institutional procurement mode: the 3T MRI decision does not run on a public-facing self-service flow. It runs through hospital procurement and, in larger networks, group purchasing organizations. The agent reaches siemens-healthineers.com, reads the MAGNETOM Cima.X spec and the clinical evidence, then the contract routes through the hospital's purchasing path. Siemens Healthineers owns the MAGNETOM-3T story, the procurement department owns the contract.
What changes the outcome is closing the surface-to-procurement gap. The brand-own page surfaces the MAGNETOM-3T story cleanly. The remaining lever is on the channel side: the agent reads the Cima.X spec, then has to identify the right hospital procurement or GPO contact path for the RFQ. Named Hyperize offerings here: Answer Pages on "Welches 3T-MRT für deutsche Universitätsklinik-Neuroradiologie?" that route directly to the brand-own MAGNETOM portfolio plus the hospital-procurement-channel discovery, and Reference Pages that make Siemens Healthineers' named instruments (the MAGNETOM family taxonomy, BioMatrix-Tuner sequence library, the syngo.via clinical workflows) agent-readable rather than human-readable. If your brand sits behind GPOs, distributors, or institutional buyers, this is the AI test that decides whether agents reach you first or your channel does.
The proof isn't more content. It's a repeatable lift in whether agents find, verify, cite, recommend, and complete the brand journey directly — re-measured each wave.
Commission an audit.
Where the BrandScore opens the question, an audit closes it. An interpretive engagement on your full surface, scored under the same methodology.
Get the auditFound with us.
Strategic partnership for brands building agent success as a long-term capability, not a one-off engagement.
ApplyAudit an adjacent property.
The BrandScore covers the primary domain. Get the same methodology applied to an adjacent property: a country site, a sub-brand, a category beyond the DAX-40 slate.
Get a SnapshotThis is Siemens Healthineers. What about your brand?
You just saw how an AI agent treats a DAX 40 brand.
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.
Hospital group purchasing organizations and medical-device distributors capture 60% of medical imaging equipment demand before Siemens Healthineers.
Third-Party Interception derived from AI Visibility response analysis: the institutional procurement mode applies. 3T MRI contracts route through hospital procurement departments and group purchasing organizations — the structural intermediary layer for medical-equipment specification that the agent surfaces alongside Siemens Healthineers' direct MAGNETOM-3T portfolio.
Intermediaries University-hospital procurement · Hospital group purchasing organizations · Vizient-equivalent GPOs · Medical-device distributors
Hyperize-selected tasks.
One task from the public sector grid. Task list is frozen before each wave runs.
Siemens Healthineers MAGNETOM-class 3T MRI for tertiary-care neuroimaging suite, German university-hospital procurement
- Close state
- a quote
- Bottleneck
- Producer page surfaces the MAGNETOM-3T spec and clinical evidence; hospital-procurement intermediation (university-clinic purchasing departments and group purchasing organizations) captures the contract close.
Fairness note
Wave 10 Q2 2026 partial measurement. Single task (Siemens Healthineers MAGNETOM-class 3T MRI for tertiary-care neuroimaging suite, quote_ready close, German university-hospital procurement). AI Visibility from the audit pass (Q2-2026, openai/perplexity/anthropic, DE language, 18/18 valid datapoints). AI Usability axis pending the agent-fleet run (scheduled for a later wave) — current Usability score reflects structural defaults for the catalog_only B2B equipment close, not a measured per-class access profile. 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
26 May 2026
Wave · ProtocolWAVE-Q2-2026-W10-INDUSTRIALS
ars-methodology/v1.1
Wave 10 partial measurement landed. AI Visibility pass complete (18/18 valid, 0 errors). The agent-fleet run is scheduled for a later wave — Usability axis on this wave reflects structural defaults for the catalog_only B2B equipment close. Producer-page survival of the MAGNETOM-3T story confirmed by the AI Visibility response analysis; hospital-procurement channel position derived from the AI Visibility response texts (university-hospital purchasing departments and GPOs dominate the contract layer).
Evidence and provenance.
Public methodology references and internal evidence pointers behind every claim above.
- [S1]Accessed · 26 May 2026
AI Visibility audit · Siemens Healthineers Wave Q2 2026 (dispatched 2026-05-26)
Internal · Hyperize evidence
- · AI Visibility score
- · the close state reached (quote_ready)
- [S2]Accessed · 26 May 2026
Agent-fleet run · industrials · Siemens Healthineers phase 1-4 (scheduled for a later wave)
Internal · Hyperize evidence
- · the per-class access profile (a later wave)
- Accessed · 26 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.
Challenge ExtendSubmit your own task.
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.
