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Patent analysis and insight
Analysis and insight to bring more predictability, transparency, and equity to your patent prosecution.
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Why stronger AI inputs lead to better patent decisions
Better patent data leads to better patent strategy because patent AI is only as useful as the patent-specific data behind it. When tools are grounded in a strong data foundation, they can produce better strategic outputs, stronger patent workflow support, and better patent decisions.
Why AI can’t replace attorney judgment
Patent practice depends on nuance, legal reasoning, client goals, and risk assessment. The most trustworthy AI in patent practice supports attorneys with better patent-specific data and stronger workflow fit, helping them make better strategic decisions without replacing professional judgment.
AI Meets Patent Analytics: What IP Teams Should Evaluate First
Generic AI is not enough for patent work. Patent-specific data makes AI more trustworthy, more useful in prosecution workflows, and easier for practitioners to defend to clients and partners.
How Patent Prosecution Strategies and Behaviors Are Evolving Amidst a Changing USPTO
The USPTO is not the same office it was two years ago. Since January 2025, shifts in leadership, policy emphasis, and internal guidance have changed how applications are examined and how prosecution outcomes are determined. Some of these changes have generated significant attention in the patent community, while others have been more subtle. All of them have real consequences for practitioners and applicants trying to build and protect patent portfolios today.
Being a change agent for AI in patent prosecution
AI can help patent teams reduce manual work and improve workflow efficiency. The challenge is adopting it in a way that supports attorneys, maintains quality, and aligns with real prosecution practice.
Why patent teams struggle to turn AI adoption into prosecution ROI
AI can speed up patent work. It cannot decide what is worth patenting, how much claim scope to give away, or which prosecution strategy actually supports the business. Learn why AI-first patent programs stall, where automation helps in prosecution workflows, and where patent professionals still need to own the judgment.
Why Data Quality Matters in AI Patent Tools
AI is great for patent prosecution, but it often creates new problems. When your model runs on weak data, the output may require multiple rounds of manual review and cleanup. Grounding AI in trusted USPTO data can turn your existing tools into a more useful teammate.
10 Best Conferences for Your IP Practice in 2026
If you work in patents, intellectual property, legal operations, or law firm leadership, 2026 offers no shortage of events competing for your time. The challenge is knowing which conferences are actually worth attending.
Top Outside Counsel: What the Metrics Reveal About Law Firm Performance
Evaluating outside counsel on reputation alone is no longer enough. Learn how in-house patent teams can use prosecution metrics like allowance rate, office actions, pendency, Section 112(b) rate, and response time to assess law firm performance and make better portfolio decisions.
5 Practical Ways to Implement AI in Your Patent Practice
AI doesn’t create savings in patent work by itself. Workflow does. Here are five practical ways patent teams are using generative AI today: defined-scope drafting support, faster first passes, turning calls into deliverables, building repeatable templates, and setting guardrails early.
Are you ready to transform your patent practice?
Patent prosecution is complex – we know. If you’re ready for simpler workflows and more predictable outcomes, give us a call.