What the USPTO Is Actually Asking For

The request for information (RFI) is specific. The USPTO wants a tool that can take images as direct queries, scale across a massive workload, and integrate with existing enterprise search systems — not replace them.
The core use case is prior art search: identifying existing patents and references that could affect whether a new application gets approved. As global IP filings grow, text-based search alone isn’t cutting it anymore, especially for design and utility applications that are inherently visual.
The tool must be FedRAMP authorized, highly configurable, and built for accuracy at scale. Responses are due June 19 at noon.
Why This RFI Matters Right Now

The timing isn’t accidental. The USPTO currently has nearly 774,000 unexamined patent applications sitting in its backlog. It takes roughly two and a half years for a single application to reach a final decision.
Fiscal year 2026 marks the first time in nearly a decade that the office’s output has surpassed incoming filings — a milestone USPTO Director John A. Squires called a “tipping point.” He’s publicly bullish on AI tools as a core part of the agency’s strategy to close the gap further.
This RFI is part of that push. It’s not exploratory — it’s directional.
The Technical Gap Driving This Search

Here’s the problem that makes this RFI interesting from a product standpoint: general-purpose large language models aren’t well-suited for patent figure analysis.
Aaron Capron, a partner at IP law firm Finnegan and a former patent examiner, put it plainly. Patent figures vary enormously in how they’re drafted — there’s no standardized visual language. That variability makes off-the-shelf multimodal AI models unreliable for this specific task.
The USPTO isn’t just looking for any AI image search tool. It needs something purpose-built for the patent examination workflow, with the kind of configurability that lets examiners adapt it to different application types.
That’s a meaningful product specification — and a real opportunity for vendors who can meet it.
What AI Vendors Need to Know

If you’re an AI company operating in the legal tech, document intelligence, or visual search space, this RFI is your entry point into a high-value federal contract.
A few things stand out from the requirements:
- FedRAMP authorization is non-negotiable. If you’re not already on that path, this procurement won’t be accessible to you — but it’s a signal to start.
- Image-as-query capability is the core differentiator. The USPTO wants examiners to search by uploading images directly, not by describing them in text. That’s a specific technical requirement that narrows the field considerably.
- Augmentation, not replacement, is the framing. The tool needs to work alongside existing USPTO systems. Vendors pitching a full platform overhaul will likely miss the mark.
- Transparency matters. Capron specifically noted that the more transparent the agency can be about its evaluation process, the better. Vendors should expect scrutiny on how their models make decisions — explainability isn’t optional in a legal context.
The Bigger Picture for Patent Tech

This move by the USPTO reflects a broader trend: government agencies are moving past the “AI exploration” phase and into active procurement. The question is no longer whether AI belongs in patent examination — it’s which tools are ready to operate at federal standards.
For the patent tech ecosystem, this creates a clear benchmark. Tools that can handle visual prior art search at scale, with FedRAMP compliance and audit-ready outputs, are going to define the next generation of IP search infrastructure.
The backlog problem is real. The political will to solve it is there. And the budget signal is now on paper.
The USPTO’s RFI is a small document with large implications. For AI vendors in the legal and government space, the window to respond — and to position — is open until June 19. Watch this space closely. Federal AI procurement is accelerating, and patent examination is just one of many workflows about to get rebuilt from the ground up.
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