Patent Embedding Radar 2D: Spotting Competitor Encroachment

Filing Stream

New filings 1.2 / s

Encroachment Detection

Similarity threshold 0.90

Filers

Competitor A0

Competitor B0

Competitor C0

Your portfolio0

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Live Readouts

Total filings

Encroachments

Closest threat

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Whitespace gap

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How it works

Every filing is embedded as a unit vector (an angle θ) on a similarity circle — a 2D stand-in for the hundreds-of-dimensions text embeddings a real NLP pipeline would produce from patent claims. Vectors from the same technology cluster point in similar directions:

sim(u, v) = u · v = cos(θu − θv)   (u, v unit vectors on the circle)

An encroachment is flagged whenever a competitor's filing direction has cosine similarity ≥ threshold to your nearest filing — geometrically, it lands inside the wedge around one of your patents:

encroached(c) = max_i sim(c, you_i)  ≥  threshold

The whitespace gap samples 180 probe directions spread evenly around the circle and finds the probe that is farthest — in angular terms — from every existing filing:

gap = max_p ( min_i  arccos(sim(p, filing_i)) ) × 2

That probe marks the largest unclaimed arc of the technology space — a candidate whitespace opportunity, shown as the gold marker. Real competitive-intelligence platforms run this exact nearest-neighbour logic over genuine text/patent embeddings (often 300–1500 dimensions) instead of 2 — the circle here makes the same math visible in a flat, pannable/zoomable view.

Filing stream — new patents arrive continuously from you and three competitors, each pulled toward one of six technology clusters with directional noise.
Threshold slider — tightens or loosens what counts as "too close" to your IP.
Filer toggles — hide a competitor to see how much of the detected threat comes from them specifically.
Drag / scroll — pan the circle and zoom in on a crowded cluster.

Your portfolio Encroaching filing Whitespace opportunity

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