Editorial team · Esgenix
Esgenix Team is the shared byline for articles produced by the Esgenix team. Each article is reviewed by the company founders before it is published.
The team writes about patent drafting, prior-art and state-of-the-art search, freedom to operate, and how AI changes the day-to-day work of patent attorneys and in-house IP teams.
Esgenix is the agentic AI patent workflow platform for prior-art search, invention disclosure, patent drafting, landscape search, freedom-to-operate search, and invalidity search.
Reviewed by C R Jacob, Leo Paul Johnson and Deepak Thomas.
LinkedIn21 articles
AI has raised invention volume and filing pressure. Patent capacity no longer requires headcount when attorneys direct decisions and AI-led services execute the production work between five gates.
The AI patent drafting tools patent teams actually use in 2026, compared on how each works, security, and fit, from explainable drafting to Word-native assistants.
Seven AI patent drafting tools compared on how they show their work: redline audit trails, claim-to-disclosure mapping, citations, and prior-art grounding.
Seven AI tools for drafting patent claims compared on scope control, disclosure grounding, and antecedent and clarity checks under 35 U.S.C. 112.
Seven AI patent tools for in-house and corporate IP teams compared on security certifications, lifecycle coverage, and governance fit.
How AI parses specification text to extract elements, assign numerals, plan views, and reconcile every numeral to its description under attorney review.
How drafting cost in a corporate filing program scales with filing volume rather than team size, where the spend accumulates, and what counsel controls.
Agentic state-of-the-art search turns a patent landscape into a directed investigation: higher recall, an approved taxonomy, and business questions answered.
· 5 min read
How to run a freedom-to-operate search inside the drafting workflow so findings shape claim language while the claims are still adjustable.
A patentability search that feeds drafting starts with the disclosure meeting transcript and yields both a search report and an invention disclosure document.
The eight stages of the patent workflow, the seams between them, and where the handoffs cost you time you never get billed back.
Three cost pools, only one of which gets measured. Why verification cost, not production time, decides AI patent drafting ROI for in-house teams.
Seven measures worth recording when you benchmark AI patent draft quality, the sample set to use, and the mistakes that invalidate the test.
One disclosure, three standards. What the USPTO, EPO and Indian Patent Office each require, and how to draft for all three without three drafts.
What actually changes for an in-house IP team when filings rise and headcount does not, and why assistance-shaped AI tools move the line less than expected.
Why the Indian priority document decides your US and EP outcomes, and what that means when evaluating AI patent drafting tools in India.
How to test an AI patent drafting tool for grounding before you buy: provenance per claim element, gap detection, and a held-back reference.
Pasting invention details into ChatGPT or Gemini can risk confidentiality and novelty. Learn the legal exposure and safer secure drafting workflows.
Patent attorneys must protect client IP before filing. See how secure AI patent drafting with redline audit trails reduces confidentiality and disclosure risk.
Opaque AI patent tools create hidden risks. Learn why visible claim-generation logic and audit trails are essential for compliance and defensibility.
An agentic council uses multiple LLMs to debate and draft patents with explainable redline trails, secure storage options, and attorney oversight.