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Solve Intelligence is deployed at Potter Clarkson as a practitioner-led platform, designed to enhance - not replace - the expertise of experienced patent attorneys. The firm uses the technology primarily at a senior level, where skilled practitioners are able to prompt and interrogate the system effectively to guide high-quality outputs.

By combining advanced AI capability with deep technical and legal experience, the platform enables senior attorneys to work more efficiently while focusing their time and judgement on strategic advice, complex analysis and client value. This reflects the firm’s long-standing philosophy that technology should strengthen the role of the practitioner, not substitute professional expertise.

“At Potter Clarkson, our priority is delivering technically rigorous and strategically sound advice to our clients. We use Solve Intelligence as a tool in the hands of experienced patent attorneys - professionals who understand how to guide, challenge and refine AI-generated outputs. It allows our senior teams to concentrate on the aspects of drafting and prosecution where their judgement adds the greatest value, while maintaining full control over quality and client strategy.”

Peter Finnie, Partner, Potter Clarkson

Since rolling out Solve Intelligence’s Patent Copilot, the firm has tailored the platform to reflect its established house styles and drafting standards. This customisation reduces administrative burden and supports consistency across teams, enabling practitioners to engage with AI efficiently without compromising on quality, client-specific requirements, or the firm’s distinctive approach.

We are excited to welcome Peter Finnie, Partner at Potter Clarkson, to Solve Intelligence’s Customer Advisory Board.

On February 5, 2026, Solve Intelligence hosted a masterclass with IPWatchdog on AI prompt engineering for patent workflows. Nearly 750 practitioners registered from across the world.

The level of experience in the room was striking: 75% of attendees had more than 11 years of patent experience, and over 40% had more than 20 years. A clear indication that decision-makers are staying on top of the latest trends and educational content on AI.

Key insights

• Senior patent decision-makers are actively learning AI with 750 registrants and deep experience
• AI is broadly permitted with most respondents reporting approval or active policy evaluation
• Prompt engineering drives ROI with templates and structured instructions improving output quality

Watch the recording and download the slides

The recording covers the full prompt engineering framework for patent workflows, a live demonstration of prompting in action within Solve Intelligence across drafting, prosecution, and claim charting workflows, and a Q&A with the panel.

Download the slides here.

AI can improve the quality and efficiency of patent work - but it can also create new confidentiality and privilege risks if you don’t control what data is shared, where it’s stored, and who can access it. The good news: you can turn “AI risk” into a repeatable review process that your leadership, IT/security, and risk teams can sign off on with confidence.

This guide gives you a practical framework and a due diligence checklist, that you can use to evaluate AI tools for patent workflows without compromising client confidentiality.

Key takeaways

• In patent work, confidentiality failures can jeopardise patent rights—treat inputs as high-risk.
• Risk is more than training: retention, access, logs, human review, and subprocessors matter.
• Use data tiers: Tier 0–1 OK; Tier 3 ‘default no’ unless explicitly approved and controlled.
• Make it auditable: approved use cases, human review, matter separation, and vendor diligence.

For further information, read the full guidance below.

Solve Intelligence will be presenting a live product demo at the upcoming private workshop hosted by HG Law and organised by Cosmonauts.

📅 Wednesday, 4 March 2026:

Workshop: 2:30 PM - 6:00 PM | COMO Metropolitan London Hotel, London, UK

Dinner: 6:00 PM - 9:00 PM | COYA Mayfair, London, UK

This session is designed for Heads of IP, Patent Directors, and innovation leaders who want to level up their IP strategy by seeing AI applied in patent drafting, preparation, and prosecution.

Register Here.

Artificial intelligence is no longer a theoretical issue in patent drafting, and many firms are already using AI-assisted workflows in some form. The harder question now isn’t whether to use AI, but how to talk to clients about using it.

Key insights

• Focus on better drafting quality, enforceability, and fewer avoidable downstream problems.
• Walk through data handling so confidentiality and retention protections are easy to trust.
• Explain inventorship stays human and the attorney remains responsible for every word.
• Keep the process clear and documented so expectations stay aligned from day one.

For some clients, AI usage signals efficiency and modernisation. For others, it raises immediate concerns about confidentiality, inventorship, and quality control. Those concerns are legitimate, so the key is to approach conversations about AI in a way that is structured, transparent, and grounded in professional responsibility.

In practice, the most effective discussions with clients will focus on outcomes rather than technology.

This article provides a structured framework to use when talking to clients about using AI, such as Solve Intelligence’s Patent Drafting Copilot^TM, in patent drafting.

As Artificial Intelligence (AI) and large language models (LLMs) increasingly integrate into legal practices, the U.S. Patent and Trademark Office (USPTO) issued guidance to assist patent attorneys with adopting AI tools in patent drafting, prosecution, and other areas of patent law.

In this article, we summarize the key compliance requirements from the USPTO's guidance and explain how Patent Copilot™ helps practitioners meet these obligations while leveraging AI's benefits.

The UK Supreme Court’s Emotional Perception decision moves UK practice closer to the EPO for computer implemented inventions, including AI. Claims with ordinary hardware will usually avoid the “computer program as such” exclusion, but only technical features can support inventive step. In practice, applicants should focus arguments and evidence on technical contribution and inventive step.

Key takeaways

1. UK moves closer to EPO, inventive step becomes the main battleground.
2. Ordinary hardware avoids exclusion, but may not support inventiveness.
3. Only technical features count at inventive step, not business aims.
4. Neural networks are treated as software, no special treatment either way.
5. Draft around technical contribution, measurable effects, and system level impact.