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What AI Changes for In-House Teams and Outside Counsel

Both in-house teams and outside counsel can let a purpose-built platform carry the shared foundation for their patent work. They can then focus their limited time on the standards and judgment that set their work apart. AI has made this division of labor more valuable by raising the payoff for turning a practice into templates, instructions, and review criteria that run at scale. Let’s call that codification. The platform can encode a great deal of best practice out of the box, and a team can add its own custom templates and instructions on top. The real question is how much to add and how much to leave to the platform. There is no fixed formula because the right balance changes as the team’s practice, the law, and the technology evolve.

The most effective patent practitioners are already using AI patent drafting to draft faster, catch claim inconsistencies earlier, and free up hours for the strategic work that actually wins allowances.

Key takeaways

• AI patent drafting tools can reduce application drafting time by up to 80 percent, with Solve Intelligence customers consistently reporting 50 percent or greater efficiency gains across drafting and prosecution 
• Roughly 9 out of 10 utility patent applications receive at least one office action rejection, so prosecution efficiency matters as much as drafting speed 
• Solo attorneys use AI to match larger law firms on turnaround speed and client capacity
• The strongest reported results come from iterative AI–attorney collaboration, with practitioners directing the process and owning the final work product

Solve Intelligence works with over 700+ patent teams as they bring AI into daily practice, and the same pattern shows up again and again: recognising that AI helps is easy, but building consistent, team-wide use is not. Adoption tends to stall for a handful of reasons, from informal early experiments to unclear decision making, and a promising trial can fade out without anyone establishing whether the tool or the rollout was at fault. This playbook lays out the process that gets a team from first experiment to settled habit, with the attorney's judgment in control at every step.

AI makes it practical to rerun patent intelligence as products and patent rights develop. For example, at concept stage, broad freedom-to-operate screening identifies the rights that merit attention. As the design matures, selected patents are escalated for feature-by-feature claim charts, while scheduled monitoring refreshes the analysis when claims are amended or an application proceeds to grant.

This contrasts with the traditional approach, in which landscapes, FTO reviews, and portfolio analyses were commissioned as separate projects at fixed stages. Each took substantial time to complete and was rarely repeated.

The final review before a U.S. patent filing should not be another linear read-through. Rather, it should be a controlled quality-assurance step: a systematic check of the relationships among the claims, specification, and drawings while the full range of corrective options is still available.

Done well, pre-filing QA catches errors that are inexpensive to fix at the drafting desk but costly after filing. Done poorly, it can leave the applicant facing an avoidable rejection, a narrowing amendment, a priority problem, or a validity challenge years later.

Key Takeaways:

• Pre-filing is the best time to correct disclosure, claim, and drawing defects without creating new-matter or priority complications.
• Antecedent basis gaps, contradictory claim dependencies, and terminology drift are the most common pre-filing defects, and all are correctable before filing.
• Section 112(a) review is substantive, not clerical: a broad range or functional limitation may warrant scrutiny even when the claim reads cleanly.
• Automated patent proofreading identifies candidate defects for attorney review but does not substitute for legal judgment on claim scope, support, or strategy.

Patent attorneys can now directly connect with iManage into Solve Intelligence’s platform, further streamlining your patent workflows.

The best patent applications are built from deep context. Claim sets that hold up, specifications that anticipate rejections and objections, arguments that resonate with examiners and legal and IP decisions that align with business and client needs. All of this depends on the attorney having the right materials at the right time. That's why we integrated Solve Intelligence directly with iManage.

iManage is where IP practices and firm intelligence lives. It's the document management platform trusted by thousands of legal organizations globally, where client disclosures land, where prosecution histories are stored, where the institutional knowledge of a firm accumulates over years. Now, that knowledge is directly accessible inside Solve.

Solve’s Figure Builder is the integrated environment within the Solve platform where you can generate, edit, label and refine figures. It brings figures into the drafting process, alongside claim and specification drafting so consistency, and compliance with 37 CFR §1.84, is maintained across your application from the very first sketch to the version you file.

Key Takeaways:

• Create, edit and finalize figures for your patent filings, both manually and with AI assistance.
• Bring figure management into the heart of the drafting process to ensure you have the figures you need, when you need them.
• Propagate changes in terminology and reference numerals across your whole application with ease.
• Convert disclosure documents or claims into labelled line drawings in a single session, and then use them as the basis for your detailed description.

We're delighted to welcome Bree Vculek to Solve Intelligence as our newest Legal and Product Engineer.