academic-commercialization-agent

Why we included this project

Judging whether a research paper is worth commercializing is usually a messy, subjective call, and this project turns it into something closer to a repeatable process. You hand it a research direction or paper topic, and six agents pull evidence from academic literature, patent databases, and market sources before returning a scored report with citations you can check. The TRL/MRL scoring and patent landscape sections give a concrete read on technical and market readiness instead of a vague thumbs-up, and the optional decision context makes clear whether the output is orientation or actual GO/NO_GO advice. It runs on CrewAI and works with DeepSeek, OpenAI, or Claude, so you can use the model you already pay for. For teams that want an evidence-backed first pass at commercialization screening without building the pipeline themselves, it is a solid starting point.