Category…
Fewer than 30% of Google searches for this category use words matching AI’s description of it. If you own this category, buyers may not find what AI says about you. Open the category — the five-vantage panel shows AI’s words and buyers’ words side by side.
These are the brands AI most associates with this electronics category.
You’re viewing a broad category. AI vocabulary is loose here, so non-component entities may appear in the ranking. Cleaner signal often appears one level deeper.
Showing 79 brands AI ranks as component manufacturers. The other 14 of 93 brands AI mentions in this category appear as distributors or category-surface entities (paid evidence layer).
Share is each brand’s portion of AI’s total mentions for this category. Mention counts are cumulative across the consensus panel and tracking weeks. Not normalized for panel turnover or model outages — cross-category comparisons require the evidence layer.
VERIFIED = the brand’s own product catalog lists this category · AI-DISPUTED = AI places it here but its catalog does not · UNCONFIRMED = no own-catalog evidence captured yet. We publish what AI says and whether it checks out — we never fabricate a placement. Click a brand for its full footprint.
Threshold rule, panel breadth, observed week, and the per-brand statistics behind each row — plus the reality checks (vantage alignment, supply geography, buyer vocabulary) that tell you whether AI’s rank for Filters holds up off-screen.
Open the evidence layer →How AI talks about Filters, compared to how OEMs describe it on their own product pages, how buyers search for it, how distributors bucket it, and how aggregators classify it in their taxonomies. Each of those five viewpoints is a vantage. The cosine between each pair of vantages tells you whose vocabulary tracks whose — 1.0 means identical wording, near 0 means they don’t share a vocabulary at all.
OEM self-description and Buyer search use the most-different vocabulary for this category — cosine 0.89.
findchips #1 in 8 sources (338,352 parts listed) · 6 buyer searches per 1k parts listed
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How manufacturers describe this category on their own product pages.
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How electronic distributors bucket this category in their product hierarchies.
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How parts aggregators (Octopart, FindChips) classify this category in their taxonomies.
w = weight within this vantage’s vocabulary · n = source observations contributing to this vantage · vol = monthly buyer-search volume (DataForSEO, where applicable)
Lower triangle only — matrix is symmetric. Diagonal omitted (self-cosine = 1.0).
| AI | OEM | Buy | Dist | Agg | |
|---|---|---|---|---|---|
| AI | — | · | · | · | · |
| OEM | — | · | · | · | |
| Buy | 0.89 | — | · | · | |
| Dist | — | · | |||
| Agg | — |
See OEM-self, distributor, and aggregator vocabularies for Filters — plus the full 10-cosine distance matrix and where your brand sits inside the divergence.
Distinct parts listed on each channel’s category pages — catalog breadth, not units in stock. Poisoned pulses (lcsc, rs-online) shown when present but excluded from the leader call. Per-arm as-of stamped in the join.