The Academic Commercialization Pipeline enables AI agents to identify promising academic research ripe for commercialization. By integrating and orchestrating data from eight key academic and patent sources—including OpenAlex, Semantic Scholar, ArXiv, USPTO, EPO, NIH Grants, Grants.gov, and ClinicalTrials.gov—it generates a comprehensive Commercialization Probability Score (0-100). This score is derived from four independent models assessing Research Momentum, Patent IP Strength, Funding Validation, and Technology Readiness Level (TRL), allowing technology scouts, corporate venture teams, and tech transfer offices to efficiently uncover spinout-ready research and make informed decisions significantly faster than traditional manual processes.
主要功能
010 GitHub stars
02Automates author-to-inventor cross-referencing for publication-to-patent conversion detection
03Provides 5-tier investment verdicts (e.g., INVEST_NOW, MONITOR) with an override rule
04Orchestrates 8 parallel academic and patent data sources concurrently
05Generates a Commercialization Probability Score from 4 independent scoring models
06Estimates Technology Readiness Level (TRL) from text analysis and clinical trial phases
