v1.0
SPARK reads your institution's research and patent archives, then uses a large language model to surface the gaps, trends, and directions most worth pursuing. Drop in CSV exports or PDF research and patent documents — no fixed schema required. SPARK parses full text and structures every record: titles, authors, keywords, year, and source. A configurable LLM finds research gaps, trend keywords, similarity to prior art, and an innovation score. Opportunities land on an interactive dashboard, ranked and filterable by year, source, and score. SPARK was created using bootstrap5, vanilla js, django and postgresql.
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17 Aug, 2026
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1.0
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