NEWS & UPDATES
The Data Moat: What One Legal Tech AI Partnership Teaches Us About IP Strategy
Algorithms are rapidly becoming a commodity. To build a defensible AI business, you need a "Data Moat." Using the recent Paximal and Juristat partnership as a case study, this post explores how connecting agentic AI workflows to proprietary data layers shifts the paradigm from simple imitation to evidence-based strategy.
The Company As “Trade Secret Office”
Most innovation strategies rely on the hope of government validation, but trade secrets flip the script. This time, our focus is on the “Internal Examiner” model, where the power to create legal certainty resides entirely within the enterprise. By utilizing internal “reasonable measures” to grant protected status to its own assets, a company eliminates the uncertainty of external backlogs and shifting administrative policies. Learn how to take control of the innovation pipeline and build an operational moat without waiting periods or maintenance fees.
Trade Secrets as Assets: Turning Intellectual Capital into a Legally Undeniable Moat
Most companies treat trade secrets as a passive legal status—something they “have” simply because they haven’t told anyone. In my latest post, I break down why this is a high-risk strategy and propose a more proactive approach. Learn what specific data points should be generated for every trade secret asset to transform vague know-how into a defensible “Innovation Ledger,” and how this documentation provides critical leverage during M&A due diligence, technical collaborations, and internal audits.
The Double-Duty Moat: How IP Strategy Unlocks R&D Tax Credits
Founders love R&D tax credits, but the IRS documentation requirements can be an administrative nightmare. This week, I explore how working with an IP attorney to secure your patents and trade secrets naturally generates the exact “contemporaneous proof” the IRS demands. Learn how to use a single strategic effort to build a legal moat and unlock non-dilutive capital.
USAA v. PNC Bank and the Definition of the Abstract Idea
The USAA v. PNC Bank petition for certiorari brings the Section 101 “abstract idea” exception back to the Supreme Court, highlighting the logical tension in labeling processes involving tangible objects as abstract. This post explores the fundamental difficulty of distinguishing between abstract concepts and their physical applications when every idea is, by its very nature, abstract.
A New Partnership Focused on Trade Secret Litigation Financing
Congratulations to Tangibly and SIM IP on their new partnership! This piece takes a look at what this could mean for companies that generate intellectual property and take protecting it seriously.
2026 Patent Fee Schedule: New Service for AI-Assisted Applications
We have updated our Patent Fee Schedule for 2026 with a new offering for early-stage companies: professional preparation assistance and filing of a US Provisional Patent Application for inventors who would like to generate their own application draft using a generative-AI tool like Idea Clerk.
AI and Energy Consumption
Construction scaffolding represents an expensive paradox: temporary metal frameworks that consume materials and labor, only to be dismantled once the permanent building stands complete. Today's large language models present a strikingly similar contradiction—computationally profligate systems whose greatest value may lie in designing their own elegant replacements.
A Measured Approach to Generative AI Tools For Intellectual Property Protection and Management
While there is no doubt that generative AI will change the manner in which almost all aspects of the law are practiced, reports of the death of jobs in the patent industry due to AI tools are greatly exaggerated.
Protecting the Data Advantage: Why Trade Secrets Programs Are Essential for Data-Driven Technology Companies
Data-driven technology companies face a critical risk shift as they mature—from proving market value to protecting their innovations from competitors—making trade secrets programs essential for safeguarding the proprietary data sources, AI methodologies, and analytical processes that drive their competitive advantage in the $14.4 billion data monetization market.
Navigating Intellectual Property Protection in the Evolving AI Landscape
The complex and fast-moving nature of AI development creates challenges for IP protection, particularly if legal advisors lack a solid understanding of the underlying technology.
Protecting Innovation With Trade Secrets And Patents, Simultaneously
Innovators don’t have to choose between patents and trade secrets—they can use both strategically to maximize protection. By carefully managing disclosure and timing, businesses can preserve trade secret value while keeping the door open to patent protection.
Why Trade Secrets May Be The Most Important Form Of IP For AI Innovation
AI innovations are often best protected as trade secrets, since their most valuable components—like proprietary algorithms and data—are hidden from users and competitors, offering long-lasting protection without public disclosure. While patents still play a role, the confidential nature and rapid evolution of AI make trade secret protection a more strategic choice for many technology companies.
TRADE SECRETS – Some Basic Considerations and Strategy
Recent high-profile trade secret cases show how seriously courts are taking protection of proprietary information. While the legal requirements are simple—identify secrets and take reasonable measures to protect them—companies must carefully balance security with day-to-day operations to safeguard their competitive edge.
Intellectual Property Capture
Forming a comprehensive intellectual property strategy includes capturing intellectual property rights for the company