Perplexity’s New AI Tool Aims to Simplify Patent Research

TL;DR: Perplexity has launched an AI-powered patent research agent that allows natural language queries instead of keyword strings. The tool extends beyond exact matches to related terminology, searches academic papers for prior art, and is free during beta, with Pro and Max subscribers receiving additional usage quotas.

Patents are notoriously difficult to search for, requiring precise keyword matching and knowledge of technical terminology variations. Perplexity’s new patent research tool aims to solve this problem by accepting natural language queries instead of complex keyword strings.

Natural Language Patent Searches

The tool allows users to ask questions like “Are there any patents on AI language learning?” or “Key quantum computing patents since 2024,” and returns relevant results with AI-generated summaries for each patent. This approach eliminates the need to construct precise keyword strings—a significant barrier for researchers unfamiliar with patent search conventions.

Beyond Exact Matches

Perplexity’s tool extends beyond exact keyword matching by understanding related terminology. For example, searching for “fitness trackers” will also surface patents filed under related terms like “activity bands,” “step-counting watches,” and “health monitoring watches.” This semantic understanding helps researchers discover relevant patents they might otherwise miss using traditional keyword-based searches.

Prior Art Discovery

The tool’s capabilities extend beyond patent databases. It can search through academic papers, public software repositories, and other sources for prior art—existing work that might invalidate a patent claim or inform a new application. This comprehensive approach provides researchers with a more complete picture of the intellectual property landscape.

Accessibility and Pricing

Perplexity is making its patent research tool free for everyone to use whilst in beta. Pro and Max subscribers receive additional usage quotas and configuration options. Users can access the tool by entering a search for a patent directly in Perplexity’s main interface.

Context and Background

Patent search has historically required specialised knowledge and training. The United States Patent and Trademark Office’s own guidance acknowledges the complexity of effective patent searching, recommending strategies that involve multiple keyword variations, classification codes, and Boolean logic.

By applying large language model capabilities to this domain, Perplexity is attempting to democratise patent research—making it accessible to inventors, researchers, and small businesses who might not have access to expensive patent search services or trained patent professionals.

Looking Forward

The beta release suggests Perplexity is testing the tool’s accuracy and usefulness before wider deployment. Patent search accuracy is critical—missing a relevant patent during a prior art search can have significant legal and financial consequences for patent applicants and holders.

As AI tools increasingly handle specialised research tasks, the question becomes whether they can match the precision and comprehensiveness of human experts whilst providing the accessibility and speed advantages of automated systems.

The success of Perplexity’s patent tool will likely depend on its ability to balance these competing demands—making patent research more accessible without sacrificing the accuracy required for legal and business decision-making.

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