{
  "format": "hyperize/v1",
  "@id": "https://www.hyperize.ai/en/dax40-index/brands/infineon.json",
  "type": "BrandScore",
  "pageType": "BrandScore",
  "releaseState": "pilot_probe",
  "releaseLabel": "Pilot Probe",
  "title": "Infineon — Pilot Probe (Single-Task Observation, Wave Q2 2026)",
  "pilotProbe": {
    "status": "pilot_probe",
    "rationale": "Single-task observation under a narrower provider track than a full BrandScore. The Agent Success Score is computed but should be read as an early signal, not a fully-qualified score.",
    "promotionCriteria": "Confidence promotes to B (and releaseState to brand_score) when the next wave adds a second task and the fourth provider on the Discoverability track.",
    "nextWave": "WAVE-Q3-2026"
  },
  "hook": {
    "en": "An agent can find the AUIRFP4110 automotive MOSFET, read its TO-247 specs, follow the where-to-buy path, and reach the distributor cart, in every run and every agent class. A plain fetch works, a script works, the browser agent goes three for three. The only wall is the last step: cart and checkout ask for a registered account. Up to the login, this is a reference-grade agent surface.",
    "de": "Ein Agent findet den Automotive-MOSFET AUIRFP4110, liest die TO-247-Specs, folgt dem Where-to-buy-Pfad und erreicht den Distributor-Warenkorb, in jedem Lauf und jeder Agent-Klasse. Ein simpler Abruf klappt, ein Skript klappt, der Browser-Agent dreimal von drei. Die einzige Wand ist der letzte Schritt: Warenkorb und Checkout verlangen ein registriertes Konto. Bis zum Login ist das eine referenz-grade Agent-Surface."
  },
  "summary": {
    "en": "A reference-grade agent surface that AI finds about four times in ten.",
    "de": "Eine referenz-grade Agent-Surface, die KI etwa vier von zehn Malen findet."
  },
  "brandName": "Infineon",
  "legalEntity": "Infineon Technologies AG",
  "daxTicker": "IFX",
  "sector": "industrials",
  "sectorLabel": "Industrials",
  "inLanguage": "en",
  "datePublished": "2026-05-18",
  "dateModified": "2026-05-22",
  "nextReview": "2026-09-30",
  "confidence": "C",
  "evidenceTier": "proprietary",
  "wave": "WAVE-Q2-2026-W2",
  "url": "https://www.hyperize.ai/en/dax40-index/brands/infineon",
  "alternateLanguage": {
    "de": "https://www.hyperize.ai/de/dax40-index/brands/infineon"
  },
  "isPartOf": {
    "@id": "https://www.hyperize.ai/en/dax40-index",
    "name": "DAX 40 Agent Success Index"
  },
  "lanes": [
    {
      "id": "commerce",
      "name": "Commerce",
      "measured": true
    },
    {
      "id": "talent",
      "name": "Talent",
      "measured": false
    },
    {
      "id": "aftersales",
      "name": "After-sales",
      "measured": false
    },
    {
      "id": "procurement",
      "name": "Procurement",
      "measured": false
    },
    {
      "id": "investor_relations",
      "name": "Investor Relations",
      "measured": false
    },
    {
      "id": "press",
      "name": "Press",
      "measured": false
    }
  ],
  "commercialLane": {
    "visibility": {
      "question": "Will an agent find and recommend the brand?",
      "score": 39.15,
      "dimension": "Discoverability (D)",
      "methodVersion": "gate1/v1.1",
      "sampleSize": 18,
      "providers": [
        "openai",
        "perplexity",
        "anthropic"
      ],
      "provenance": "measured"
    },
    "usability": {
      "question": "Once an agent arrives — how far does it get toward the deal?",
      "score": 68,
      "scoreNote": "Derived from the access profile below + close state (usability-derivation/v1). NOT a hand-averaged number — a reproducible summary of observed agent behaviour.",
      "accessProfile": [
        {
          "agentClass": "text",
          "outcome": "success"
        },
        {
          "agentClass": "search",
          "outcome": "pending"
        },
        {
          "agentClass": "code",
          "outcome": "success"
        },
        {
          "agentClass": "browser",
          "outcome": "success"
        },
        {
          "agentClass": "full_automation",
          "outcome": "success"
        }
      ],
      "blockedClasses": [],
      "passClasses": [
        "text",
        "code",
        "browser",
        "full_automation"
      ],
      "closeState": "order_ready",
      "closeStateNote": "Reaches order-ready (product selection, prices, no login). The actual checkout sits behind a login wall and was NOT tested — the agentic purchase is unproven.",
      "methodVersion": "fleet/measured",
      "provenance": "measured"
    },
    "evidence": {
      "score": 70,
      "basis": "estimate — cross-method ground-truth consistency, not a separate measured run",
      "note": "A confidence layer on the two axes above, not a third sales axis."
    }
  },
  "score": {
    "compositeForIndexRanking": {
      "value": 62.43,
      "scale100": 62.43,
      "scale10": 6.2,
      "status": "computed",
      "formula": "Agent Success Score = (AI Visibility × 0.20) + (AI Usability × 0.70) + (Evidence × 0.10)",
      "methodVersion": "ars-methodology/v1.1",
      "usabilityDerivation": "usability-derivation/v1",
      "role": "index-ranking",
      "note": "Weighted composite, used for ranking the index. Read the two commercialLane axes (visibility + usability) for the standalone verdict — this single number blends them and is not the headline."
    },
    "dimensions": {
      "aiVisibility": {
        "name": "AI Visibility (Discoverability)",
        "weight": 0.2,
        "value": 39.15,
        "methodVersion": "gate1/v1.1",
        "sampleSize": 18,
        "providers": [
          "openai",
          "perplexity",
          "anthropic"
        ],
        "queryVariants": 3,
        "runsPerVariant": 2,
        "taskCount": 1
      },
      "aiUsability": {
        "name": "AI Usability (reach + completion)",
        "weight": 0.7,
        "value": 68,
        "derivation": "usability-derivation/v1",
        "basis": "derived from the access profile (per-class outcomes) + close state"
      },
      "evidence": {
        "name": "Evidence",
        "weight": 0.1,
        "value": 70,
        "methodVersion": "estimate/v1"
      }
    }
  },
  "thirdPartyInterception": {
    "classification": "none",
    "classificationLabel": "None",
    "directShare": 1,
    "intermediaryShare": 0,
    "intermediaryCaptureExamples": [],
    "narrative": {
      "en": "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.",
      "de": "Kein Marktplatz verdrängt Infineon für diese Bauteilklasse strukturell. Autorisierte Distributoren (Mouser, Digi-Key, Arrow) sind der markeneigene Where-to-buy-Kanal, direkt von der Produktseite erreicht, kein Intermediär, der die Nachfrage abfängt."
    }
  },
  "bottleneck": {
    "type": "visibility",
    "classification": {
      "en": "Discovery",
      "de": "Discovery"
    },
    "classificationNote": {
      "en": "Rarely found for the category.",
      "de": "Wird für die Kategorie selten gefunden."
    },
    "sentence": {
      "en": "A reference-grade agent surface that AI finds about four times in ten.",
      "de": "Eine referenz-grade Agent-Surface, die KI etwa vier von zehn Malen findet."
    },
    "executiveSummary": {
      "en": "The surface is reference-grade: every agent class reaches the distributor cart, only the final checkout asks for an account. The gap is discovery, not usability, an agent surfaces Infineon for the part about four times in ten.",
      "de": "Die Surface ist referenz-grade: jede Agent-Klasse erreicht den Distributor-Warenkorb, nur der finale Checkout verlangt ein Konto. Die Lücke ist Discovery, nicht Usability, ein Agent zeigt Infineon für das Bauteil etwa vier von zehn Malen."
    }
  },
  "testNarrative": {
    "verdict": {
      "en": "Every agent class reaches the cart. The checkout asks for an account.",
      "de": "Jede Agent-Klasse erreicht den Warenkorb. Der Checkout verlangt ein Konto."
    },
    "narrative": {
      "en": "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.",
      "de": "Wir haben fünf Typen von KI-Agenten auf infineon.com geschickt, um den Automotive-MOSFET AUIRFP4110 (TO-247) zu finden und zu bestellen. Die Spec-Treue hielt den ganzen Weg: ein simpler Abruf und ein Skript extrahierten das Bauteil vom Finder-Kontext bis zum Where-to-buy, der Browser-Agent schloss alle drei Läufe ab. Der Agent erreichte den Distributor-Warenkorb. Der einzige Stopp ist die finale Fortsetzung: Warenkorb und Checkout verlangen ein registriertes Konto."
    },
    "scopeShift": {
      "en": "This is one part in one portfolio. Infineon spans automotive, power and sensor systems, green industrial power, and connected secure systems.",
      "de": "Das ist ein Bauteil in einem Portfolio. Infineon umfasst Automotive, Power and Sensor Systems, Green Industrial Power und Connected Secure Systems."
    },
    "agentMatrix": [
      {
        "type": "text",
        "status": "success",
        "note": "Raw HTTP holds full spec fidelity from finder context to where-to-buy"
      },
      {
        "type": "search",
        "status": "pending",
        "note": "LLM runs pending"
      },
      {
        "type": "code",
        "status": "success",
        "note": "Part extraction + where-to-buy reachable from page anchors"
      },
      {
        "type": "browser",
        "status": "success",
        "note": "3/3 runs, full spec fidelity, distributor cart reached"
      },
      {
        "type": "full_automation",
        "status": "success",
        "note": "Cart reached; checkout continuation requires a registered account (login)"
      }
    ]
  },
  "fairnessDeclaration": {
    "reviewPassed": false,
    "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.",
    "methodologyUrl": "https://www.hyperize.ai/en/methodology/task-selection",
    "sectorGridRef": null
  },
  "activeTasks": [
    {
      "title": {
        "en": "Infineon AUIRFP4110 Automotive MOSFET",
        "de": "Infineon AUIRFP4110 Automotive-MOSFET"
      },
      "closeState": "order_ready",
      "intermediaryMode": "none",
      "businessRelevance": null,
      "difficultyBand": null,
      "engpass": {
        "en": "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.",
        "de": "Spec-treu vom Finder bis Where-to-buy über alle Klassen; nur die Warenkorb/Checkout-Fortsetzung ist durch ein registriertes Konto abgeriegelt. Die frühere Lücke ist Discovery, nicht die Surface."
      }
    }
  ],
  "scoreHistory": [
    {
      "date": "2026-05-22",
      "quarter": "Q2 2026",
      "waveId": "WAVE-Q2-2026-W2",
      "protocolVersion": "ars-methodology/v1.1",
      "summary": "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."
    }
  ],
  "methodology": {
    "formula": "Agent Success Score = (AI Visibility × 0.20) + (AI Usability × 0.70) + (Evidence × 0.10)",
    "usabilityDerivation": "usability-derivation/v1",
    "protocolVersion": "ars-methodology/v1.1",
    "taskSelection": "https://www.hyperize.ai/en/methodology/task-selection",
    "agentSurface": "https://www.hyperize.ai/en/methodology",
    "dimensions": {
      "aiVisibility": "AI Visibility (Discoverability) — audit-pipeline-derived. 3–4 providers × 3 query variants × 2 runs.",
      "aiUsability": "AI Usability — derived from the per-class access profile (which agent classes reach the close state) modulated by close-state depth. The profile is the truth; the score is a reproducible summary, not a hand-rating.",
      "evidence": "Evidence — cross-method ground-truth consistency. A confidence layer, not a sales axis."
    }
  },
  "consequenceClose": {
    "archetype": "discovery",
    "archetypeLabel": {
      "en": "discovery",
      "de": "Discovery"
    },
    "source": "brand",
    "diagnosis": {
      "en": "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.",
      "de": "In der Produkt-Discovery scheitert Infineon nicht an der Surface-Qualität, jede Agent-Klasse hielt die Spec-Treue vom Part-Finder bis zum Distributor-Warenkorb. Es verliert früher: auf breiten Bauteil-Auswahl-Prompts erreicht ein Agent Infineon nur etwa vier von zehn Malen. Die Reichweite ist die Lücke, nicht die Surface."
    },
    "evidence": {
      "en": "A reference-grade agent surface that AI finds about four times in ten.",
      "de": "Eine referenz-grade Agent-Surface, die KI etwa vier von zehn Malen findet."
    },
    "question": {
      "en": "The question this raises: where would broader measurement — additional tasks, additional providers — sharpen the discovery read?",
      "de": "Die Frage daraus: Wo würde breitere Messung — zusätzliche Tasks, zusätzliche Provider — die Discovery-Lesart schärfen?"
    },
    "confidenceHedge": {
      "en": "Based on the current pilot slate, this read is directional.",
      "de": "Basierend auf dem aktuellen Pilot-Slate ist diese Lesart direktional."
    },
    "closes": {
      "en": "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.",
      "de": "Discovery-Packaging, nicht Surface-Reparatur. Reference Pages, die die Bauteil-Auswahl-Autorität aus dem Produktbaum bündeln, Answer Pages für die Applikationsfragen, die ein Ingenieur stellt, bevor er einen Anbieter nennt, Concept Pages, die das parametrische Vokabular besetzen, damit Infineon das zitierte Bauteil ist, bevor die Shortlist entsteht."
    },
    "proof": {
      "en": "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.",
      "de": "Der Beweis ist nicht ein saubereres Datenblatt. Es ist, dass Agenten Infineon-Bauteile auf breiten Applikations-Prompts nennen, nicht nur wenn die Teilenummer schon bekannt ist, neu gemessen mit jeder Wave."
    },
    "ctas": [
      {
        "weight": "primary",
        "eyebrow": "Audit · €1,900",
        "title": {
          "en": "Commission an audit.",
          "de": "Audit beauftragen."
        },
        "body": {
          "en": "Where the BrandScore opens the question, an audit closes it. An interpretive engagement on your full surface, scored under the same methodology.",
          "de": "Wo die BrandScore die Frage öffnet, schließt sie ein Audit. Ein interpretatives Engagement auf der vollen Surface, gemessen unter derselben Methodologie."
        },
        "cta": {
          "en": "Get the audit",
          "de": "Audit anfragen"
        },
        "href": "mailto:hello@hyperize.ai?subject=Audit%20%C2%B7%20Infineon"
      },
      {
        "weight": "secondary",
        "eyebrow": "Founding · €4,500",
        "title": {
          "en": "Found with us.",
          "de": "Founding Program."
        },
        "body": {
          "en": "Strategic partnership for brands building agent success as a long-term capability, not a one-off engagement.",
          "de": "Strategische Partnerschaft für Marken, die Agent-Success als langfristige Capability aufbauen — nicht als Einmal-Engagement."
        },
        "cta": {
          "en": "Apply",
          "de": "Bewerben"
        },
        "href": "mailto:hello@hyperize.ai?subject=Founding%20Program%20%C2%B7%20Infineon"
      },
      {
        "weight": "secondary",
        "eyebrow": "Snapshot",
        "title": {
          "en": "Audit an adjacent property.",
          "de": "Eine angrenzende Property messen."
        },
        "body": {
          "en": "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.",
          "de": "Die BrandScore deckt die primäre Domain ab. Die gleiche Methodologie für eine angrenzende Property: eine Länderseite, eine Sub-Brand, eine Kategorie außerhalb des DAX-40-Slates."
        },
        "cta": {
          "en": "Get a Snapshot",
          "de": "Snapshot anfragen"
        },
        "href": "mailto:hello@hyperize.ai?subject=Snapshot%20%C2%B7%20adjacent%20property%20for%20Infineon"
      }
    ]
  },
  "sources": [
    {
      "id": "S1",
      "label": "Gate-1 audit run · Infineon Wave Q2 2026",
      "accessedAt": "2026-05-22",
      "supports": [
        "AI Visibility score (18/18 valid datapoints across 3 providers)",
        "the close state reached (order_ready)"
      ],
      "url": null,
      "kind": "internal",
      "internalLabel": "Internal · Hyperize audit pipeline"
    },
    {
      "id": "S2",
      "label": "Hyperize fleet · a fleet wave Industrials (access profile)",
      "accessedAt": "2026-05-22",
      "supports": [
        "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)"
      ],
      "url": null,
      "kind": "internal",
      "internalLabel": "Internal · Hyperize fleet (Giorgio)"
    },
    {
      "id": "S3",
      "label": "Task Selection Doctrine",
      "accessedAt": "2026-05-22",
      "supports": [
        "fairness declaration",
        "Third-Party Interception framing"
      ],
      "url": "https://www.hyperize.ai/en/methodology/task-selection",
      "kind": "public",
      "internalLabel": null
    }
  ],
  "crossLinks": {
    "index": "https://www.hyperize.ai/en/dax40-index",
    "taskSelection": "https://www.hyperize.ai/en/methodology/task-selection",
    "agentSurface": "https://www.hyperize.ai/en/methodology",
    "foundingProgram": "https://www.hyperize.ai/en/founding-program"
  },
  "scope": {
    "publishes": [
      "Brand identity (name, legal entity, DAX ticker, sector)",
      "Composite (index-ranking) + AI Visibility + AI Usability (as access profile + derived score) + Evidence, with weights",
      "Per-agent-class access profile (which agent classes reach the close state)",
      "Third-Party Interception classification, direct/intermediary share, narrative",
      "Hyperize-selected task titles, close state, intermediary mode, task score, bottleneck sentence",
      "Measurement timeline (date, wave, protocol version, summary)",
      "Sources with public URLs or internal-evidence pointers",
      "Confidence grade + Evidence tier + Next review date",
      "Bottleneck classification (Discovery / Interception / Usability / Multi-axis / No dominant gap)",
      "Bottleneck archetype + consequence-claim diagnosis + operator question",
      "Test narrative (verdict, narrative, agent matrix, scope shift) — scene-level prose, no prompts or formulas"
    ],
    "doesNotPublish": [
      "Task identifiers (internal)",
      "Raw and derived measurement artifact paths (internal repos)",
      "Per-phase outcome tables (ceiling / http / coding / browser_standard / act)",
      "Individual prompts and provider-specific transcripts",
      "Scoring derivation steps below the dimension level",
      "Sector task grid file references when still draft"
    ]
  }
}