Infineon.
A reference-grade agent surface that AI finds about four times in ten.
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 Infineon, 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 same measurement as Infineon, free for your domain. Five agent classes, one real task, your score in 48 hours.
Every agent class reaches the cart. The checkout asks for an account.
We asked five kinds of AI agent to find and order the AUIRFP4110 automotive MOSFET (TO-247) on infineon.com. Spec fidelity held the whole way: a plain fetch and a script both extracted the part from the finder context through to where-to-buy, and the browser agent completed all three runs. The agent reached the distributor cart. The one stop is the final continuation: cart and checkout require a registered account.
One label, many breeds. From a plain reader to an autonomous operator, the kinds behind ChatGPT, Perplexity, and Claude Code:
Scope. This is one part in one portfolio. Infineon spans automotive, power and sensor systems, green industrial power, and connected secure systems.
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 source a component, does it route to Infineon?
Infineon 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 Infineon's site, can it place the order?
Search-class agents surface order-ready in some runs; the full agent-fleet access profile lands in a later wave.
What this does not yet cover
The agent reaches order-ready: product selected, price visible, no login. The actual checkout, cart and payment, sits behind a login wall and was not part of the test. The agentic purchase itself is unproven.
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 Infineon.
On product discovery, Infineon is not failing on surface quality, every agent class held spec fidelity from the part finder to the distributor cart. It loses earlier: on broad part-selection prompts, an agent reaches Infineon only about four times in ten. The reach is the gap, not the surface.
Discovery packaging, not surface repair. Reference Pages that concentrate the part-selection authority already in the product tree, Answer Pages for the application questions an engineer asks before naming a vendor, Concept Pages that own the parametric vocabulary, so Infineon is the cited part before the shortlist forms.
The proof isn't a cleaner datasheet. It's agents naming Infineon parts on broad application prompts, not only when the part number is already known, re-measured each wave.
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No intermediary stands between agents and Infineon. The gap is being found, not the channel.
No marketplace structurally displaces Infineon for this part class. Authorized distributors (Mouser, Digi-Key, Arrow) are the brand's own where-to-buy channel, reached directly from the product page, not an intermediary that captures the demand.
Hyperize-selected tasks.
One task from the public sector grid. Task list is frozen before each wave runs.
Infineon AUIRFP4110 Automotive MOSFET
- Close state
- order-ready
- Bottleneck
- Spec-fidel from finder to where-to-buy across all classes; only the cart/checkout continuation is gated by a registered account. The earlier gap is discovery, not the surface.
Fairness note
Wave 2 (a fleet wave Industrials). Single measured task (AUIRFP4110 automotive MOSFET, order_ready close state, checkout login-gated). AI Visibility 39.15 (18/18 valid datapoints across 3 providers); AI Usability derived from the a fleet wave access profile. Confidence C, single task; 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
22 May 2026
Wave · ProtocolWAVE-Q2-2026-W2
ars-methodology/v1.1
First v3 measurement. AI Visibility 39.15 (18/18 valid datapoints, 3 providers, DE). AI Usability derived from a fleet wave: HTTP/coding/browser all success with full spec fidelity, ACT reached the distributor cart, checkout continuation gated by a registered account. Confidence C, single task.
Evidence and provenance.
Public methodology references and internal evidence pointers behind every claim above.
- [S1]Accessed · 22 May 2026
Gate-1 audit run · Infineon Wave Q2 2026
Internal · Hyperize evidence
- · AI Visibility score (18/18 valid datapoints across 3 providers)
- · the close state reached (order_ready)
- [S2]Accessed · 22 May 2026
Hyperize fleet · a fleet wave Industrials (access profile)
Internal · Hyperize evidence
- · how each kind of agent fared (HTTP/coding/browser success, ACT cart reached + checkout login)
- · the close state reached (order_ready, checkout login-gated)
- · the tested product (AUIRFP4110, TO-247)
- Accessed · 22 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.
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.
