Harvey, Legora, Claude, or &AI: Which AI Should You Use for Patent Work?

Key takeaways

• General-purpose AI (ChatGPT, Claude) and horizontal legal AI (Harvey, Legora) are genuinely useful, but they're built for breadth. Patent litigation is a narrow, high-stakes specialty with needs they don't directly serve.
• The gaps that matter for patent work are concrete: access to patent, non-patent, and product data; claim-aware search; sourced, verifiable citations; and litigation-grade output like claim charts.
• Using a general model for legal work also carries a well-known risk of fabricated citations, which is a serious problem when your work product goes to a court.
• &AI is purpose-built for patent litigation, with agentic prior art and infringement search across the right data, defensible sourced results, and trial-ready claim charts. For patent work specifically, that focus is the point.

Can you use ChatGPT, Claude, Harvey, or Legora for patent work?

You can use them for parts of it, but not as your system of record for the work that matters most. ChatGPT and Claude are general-purpose assistants that are excellent at drafting, summarizing, and reasoning over text you give them. Harvey and Legora are horizontal legal AI platforms built to help across many practice areas. All four can help a patent professional with general tasks. None of them is built specifically for the patent litigation workflow, which is prior art search across the right corpora, invalidity and infringement analysis, and defensible claim charts.

The honest answer is that the right tool depends on the task. For a quick summary or a first draft of routine text, a general model is fine. For the searches and work product that decide a matter, the specialized requirements below are exactly where a purpose-built patent platform pulls ahead.

Where does general-purpose AI fall short for patent work?

Four gaps come up again and again, and they're the difference between a helpful assistant and a tool you can build a case on.

• The right data. Patent work depends on searching patents, non-patent literature, and real-world products. A general chatbot only knows what's in its training data and what you paste in. It isn't connected to comprehensive patent corpora or product documentation, so it can't actually run a prior art or infringement search.
• Claim-aware search and output. Patent analysis turns on claim limitations. Specialized tools search against a specific limitation and produce claim charts that map evidence to each element. General tools have no native concept of a limitation or a chart.
• Sourced, verifiable results. In litigation, an assertion you can't trace to a dated, authenticated source is unusable. General models tend to produce fluent answers without reliable sourcing, and they can fabricate citations that look real. Courts have sanctioned lawyers for filing exactly that kind of invented authority.
• The litigation workflow. A patent matter runs from search to invalidity to infringement to charting, with context carried across each step. A general assistant handles isolated tasks; it doesn't hold the matter together.

None of this means general AI is bad. It means it's general, and patent litigation is not.

Generic legal AI vs. purpose-built patent AI

ChatGPT and Claude — general-purpose assistants

ChatGPT (OpenAI) and Claude (Anthropic) are powerful general models that excel at drafting, summarizing, and reasoning over text you provide. For a patent professional, they're handy for a first draft of an email, a plain-language explanation, or a quick summary of a document you paste in. They are not connected to patent or product databases, have no claim-aware search or charting, and shouldn't be relied on for sourced legal citations.

Harvey and Legora — horizontal legal AI

Harvey and Legora are legal AI platforms designed to work across many practice areas, from contracts to research to general document work. That breadth is the appeal for a full-service firm. For patent litigation specifically, the question to ask is how deeply they cover the patent workflow: prior art search across patents, NPL, and products; invalidity and infringement analysis; and submission-ready claim charts. Confirm what each does for patent matters before assuming general legal coverage extends to them.

&AI — purpose-built for patent litigation

&AI is built only for patent work, and for litigation in particular. Its agentic Search Agent runs prior art and infringement search across patents, non-patent literature, products, and more, the way a senior searcher would, and shows its steps so the result is defensible. That feeds directly into invalidity analysis, infringement detection, and trial-ready claim charts. The narrow focus is deliberate: depth in one specialty rather than breadth across many.

When is a general AI tool good enough for patent work?

It helps to be specific about where general tools shine. Reach for ChatGPT, Claude, Harvey, or Legora when the task is general-purpose: drafting routine correspondence, summarizing a document you already have, explaining a concept in plain language, or general legal research outside the patent specialty. These are real, daily time-savers, and there's no reason to avoid them for that work.

Switch to a purpose-built patent tool when the task is the specialized core of patent litigation: running a prior art or infringement search, building an invalidity position, or producing a claim chart that has to be sourced and filed. The dividing line is whether the work needs patent data, claim-aware analysis, and defensible output. When it does, breadth stops being an advantage.

Why &AI is built for patent work

The case for a purpose-built tool comes down to depth where it counts. &AI connects to the data patent work actually requires and searches it agentically, rather than relying on a model's training memory. Every result is sourced and auditable, so it holds up in an IPR petition or an expert report instead of needing to be re-verified from scratch. And the output is litigation-grade: invalidity analysis and claim charts you can file, not prose you then have to convert into work product. For the searches and documents that decide a matter, that specialization is exactly what general tools can't offer.

See where purpose-built makes the difference on your own matter. Explore prior art search, claim charts, and invalidity analysis, review pricing, or book a demo.