Protect Your Innovations with PatentFlow
Our AI Solutions
Neural Networks trained on Patent Claims and Drawings
Semantic search and similarity comparison with prior art databases are central to every stage of the patent workflow. PatentFlow extracts claims and drawings from complete patent documents and trains neural networks on them, enabling semantic search and comparison of drawings that go far beyond simple keyword matching.
Patent Vacancy Detection and Claim Generation
Most AI patent tools rely on language models that mimic prior claims, but PatentFlow instead uses neural networks to identify unclaimed patent spaces. Its pipeline applies embeddings, VAE-based dimensionality reduction, and density estimation to locate gaps, then reconstructs them into draft claims.
Inner Feedback Loop to Safeguard Output Quality
Whenever a patent draft or office action document is updated, it is automatically reviewed by the Examiner Agent, which simulates USPTO examiners and flags issues based on the Manual of Patent Examining Procedure (MPEP). This ensures quality and compliance, even if the document was edited outside the PatentFlow system.
Coming Soon
We're currently prototyping PatentFlow system and will soon update the full project roadmap.
Stay tuned for more update!