Confidential AI for patent and IP analysis
Patent work is confidential before filing. Prior art searches, claim drafting, and freedom-to-operate analyses involve sensitive technical details that cannot be exposed to cloud AI providers. Morden keeps your IP analysis entirely offline.
Pre-filing confidentiality in the AI era
Patent attorneys and IP analysts work with prior art documents, technical papers, standards, and draft claims that are confidential until filing. They need to cross-reference claims across documents, identify component relationships, and trace provenance chains — all without exposing the work to cloud processing. Vector search finds similar text, but misses the structural relationships between patent claims, cited prior art, and dependent specifications.
Example: Freedom-to-operate analysis
An IP analyst is assessing freedom-to-operate for a new product feature. Their corpus includes competitor patents, the client’s own patent portfolio, relevant technical standards, and product specifications. Morden’s knowledge graph captures claim dependencies, cited prior art relationships, and the structural connections between patent claims and product features. The analyst can ask ‘Which active patents in this portfolio have claims that could be read onto our proposed sensor configuration?’ and get cited answers tracing the specific claim elements.
Where the market stands
IP-specific AI tools exist but are cloud-based, creating confidentiality concerns for pre-filing work. Generic offline RAG tools can search patent text but lack the structural understanding of claim dependencies and prior art relationships. Morden brings knowledge graph capabilities to offline patent analysis.
Want to see Morden work with IP and patent documentation? Get in touch at [email protected].