Integration with the USPTO’s Open Data Portal (April 2025)

ClaimMaster’s form/shell generation and downloading tools now seamlessly integrate with the USPTO’s Open Data Portal (“ODP”). The ODP is a recently launched data platform that allows programmatic access to bibliographic data and file wrapper documents

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It seems that the latest GPT models and other LLMs are getting better at deeper patent analysis or, at a minimum, are becoming more willing to take on such analytical tasks. It’s worth trying out

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ClaimMaster v. 2025 addresses recent changes in USPTO fees and forms, as well as issues with bibliographic data scraping caused by the latest Chromium update. If you use ClaimMaster to fill out IDS or other USPTO forms, or need to populate documents with bibliographic data, please continue reading for more information about this update.

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ClaimMaster 2024.5 adds several new features and improvements to our Office Action shell automation tools.

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The 2024.5 release of ClaimMaster adds several new features and improvements to our IDS tracking and generation and downloading tools. Prior Art Groups for IDS Cross-Citation (+Shells subscribers) We now added the capability to track

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ClaimMaster 2024.5 improves our patent proofreading tools with enhancements to core antecedent basis and part #/name checking tools.

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ClaimMaster release v. 2024.5 features significant improvements to our patent application drafting tools that use GenAI.

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ClaimMaster’s patent drafting tools let you store and invoke helpful GPT prompts enriched with the text from your document to generate, paraphrase, and summarize text.

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ClaimMaster version 2024.5 is now available. This release adds the ability to use local document workspaces for improving GPT/LLM output, tracking of IDS cross-citations, improvements to our core patent proofreading tools, all-in-out PDF and HTML reports, and much more

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ClaimMaster’s patent application drafting tools use a local database of selected document sections (i.e., “document workspaces”) to perform Retrieval Augmented Generation (RAG) when creating text with GPT/LLM models.

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