NLPatent is an industry leading AI-based patent search and analytics platform trusted by Fortune 500 companies, Am Law 100 firms, and research universities around the world. The platform takes an AI-first approach to patent search; it's built from a proprietary Large Language Model trained on patent data to truly understand the language of patents and innovation.
PQAI stands for Patent Quality Artificial Intelligence. It is a free, open-source, natural language-based patent search platform developed by AT&T and the Georgia Intellectual Property Alliance. PQAI is designed as a collaborative initiative to build a shared AI-based tool for prior art searching.
Solve Intelligence is an AI-powered platform designed for intellectual property legal professionals, specializing in streamlining the patenting process. Founded in 2023 and based in San Francisco, the company develops AI tools specifically for patent attorneys, focusing on user-centric design and practical application.
Amplified AI is an intellectual property (IP) technology company offering AI-powered search and collaboration tools. It helps researchers and innovators research, document, and share technical intelligence within their teams by organizing and curating global patent and scientific information.
Ambercite AI is a patent search tool that utilizes artificial intelligence (AI) and network analytics to identify patents similar to a given set of starting patents. It differs from traditional patent searching methods that rely on keywords and patent class codes by using citation patterns, patent text, and metadata to find relevant patents and reduce false positives.
PatentPal is an AI-powered platform designed to streamline the patent drafting process for legal professionals. It utilizes generative AI to automate the creation of patent applications, including generating descriptions, figures, and supporting documents from a set of claims. PatentPal aims to save time for patent attorneys and agents, allowing them to focus on higher-value aspects of their work. It can export drafts into formats like Word, Visio, or PowerPoint.
This expert analysis from Dentons partners Jennifer Cass, Anna Copeman, Sam Caunt, and David Wagget examines the unresolved IP challenges arising from generative AI in 2024 and the legal “cliffhangers” heading into 2025. It highlights key issues like copyright infringement during AI training, ownership of AI-generated works and inventions, and emerging litigation—such as Getty Images v. Stability AI. Legal professionals will find value in its forward-looking take on 2025 reforms, including licensing trends, contractual risk strategies, and pending court rulings. Written with practical insight, this piece equips lawyers with proactive tools to guide clients through rapidly evolving AI‑IP terrain.
Using AI tools like Midjourney or DALL·E to create business content doesn’t guarantee ownership. IP laws hinge on tool terms, not just creation. Risks include licensing disputes, takedowns, and infringement claims. Companies must check terms of service, avoid style mimicry, and prove rights to use content. Using AI prompts for legal review is helpful, but always confirm with counsel. Treat AI content as real IP to safeguard your brand as it scales.
AI agents that mimic real people—digital replicas—raise major legal issues, including rights of publicity, copyright, and consent. U.S. laws vary by state, and consent alone isn’t enough to avoid risk. EU and global regulations are emerging, adding complexity. Brands must secure clear licenses, define usage, manage outputs, and ensure transparency. Legal strategy isn’t optional—it's essential to protect trust, reputation, and avoid costly liabilities in this fast-evolving space.
AI is transforming how businesses use data, raising new legal and licensing challenges. Traditional licenses often lack clarity on machine use, exposing risks. Companies must assess their data flows, clarify rights for machine learning, and implement use-based frameworks addressing AI training, output rights, ethics, and traceability. Updating data licenses is essential for responsible, scalable innovation in the AI era.
Explore how AI is reshaping innovation incentives and challenging traditional IP frameworks. WIPO's Economic Research Working Paper No. 77 offers an economic perspective on AI's impact on intellectual property. Essential reading for AI entrepreneurs and IP professionals.
Examines the increasing concern over deepfakes and the legislative efforts at both federal and state levels to address the challenges they pose. It discusses various proposed and enacted regulations aimed at mitigating the risks associated with deepfake technology which of course includes AI.