A global consumer-appliance company sought to identify technology whitespace in a corpus of over 10,000 patents within the home-climate domain. Traditional keyword-based searches were noisy and cross-functional alignment was slow, often requiring multiple two-hour meetings.
By deploying TechScaper LLM’s language-model-driven tagging, custom taxonomy, and collaborative prioritization tools, the company found a low-competition sub-segment aligned with its capabilities and approved a new product line with an estimated $80–100M revenue potential.
Built a multi-level “Home-Climate” taxonomy reflecting how the business
plans (airflow, filtration, irradiation, sensing, controls).
Tagged ~200 exemplar patents to teach boundary cases and ensure
accurate classification of edge topics.
Cleaned and de-duplicated ~10k internal and external patents, then used
TechScaper LLM to assign each to taxonomy nodes with confidence scores,
eliminating keyword noise.
Computed, for each node, density (normalized publications per year),
velocity (year-over-year growth), freshness (share of filings in last 24
months), assignee concentration (HHI) and client fit (overlap with the
client’s own portfolio).
Nodes were cross-checked against adjacent, active nodes to avoid “dead
zones.”
Engineering added feasibility notes (materials, safety, regulatory path),
and IP added claim-overlap risk comments – directly on the node’s
representative records.
A Categories-vs-Assignee treemap showed where rivals clustered and
where they were absent or light.
Nodes with low rival presence but high client fit rose to the top.
Shortlisted nodes became shared buckets with: value hypothesis, IP
defensibility, feasibility, and timing.
Buckets were ranked via a simple Opportunity Score formula:
With the heat-map, treemap, and scored buckets in one view, the cross-functional team aligned on Now / Next / Later in 90 minutes.
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