Solve Intelligence’s partnership with Thomson Reuters brings together Solve’s patent and IP platform and practitioner-led support with Thomson Reuters’ longstanding experience helping global law firms adopt professional technology.
Page White Farrer Adopts Solve Intelligence and Solve's AI Templates Page White Farrer ("PWF"), a specialist intellectual property firm with a longstanding focus on technology-driven innovation, has selected Solve Intelligence to support patent application drafting following an extensive evaluation of available AI tools. The firm has initially deployed the platform within its technology-focused patent teams, supporting work across sectors such as AI, software, telecommunications, electronics, semiconductors and engineering. The firm's objective was not to automate legal judgement or replace attorney expertise, but to accelerate the preparation of high-quality first drafts of patent applications. By combining AI-assisted drafting with custom templates tailored to the firm's preferred drafting approaches, Solve Intelligence helps attorneys move from an initial claim set to a reviewable first draft more efficiently while maintaining consistency and technical accuracy. For this partnership, PWF's primary focus was on configuring the platform around the firm's own drafting conventions, client preferences and established best practices, ensuring that the technology supports the way its attorneys already work.
Solve Intelligence is proud to share that Maiwald, one of Germany’s largest and most progressive intellectual property firms, works with Solve Intelligence on selected AI-supported workflows in its patent and legal practice groups. Following an evaluation period during which selected functionalities were assessed for approved internal use cases, Maiwald and Solve have formed an enterprise partnership for 2026. The rollout reflects the same careful approach Maiwald brings to its client work. Solve enables customers in Europe to process data on servers located within Europe and holds recognized information-security certifications. In addition, Solve offers contractual commitments designed to protect confidential professional information in line with applicable statutory confidentiality obligations and professional conduct requirements. Against that background, any use of AI-supported tools took place only within approved governance structures and under applicable professional, contractual, confidentiality and data-protection requirements. That balance of innovation and professional judgment is characteristic of Maiwald. The firm has spent decades setting a standard for IP work in Europe: rigorous prosecution, a formidable contentious practice, and interdisciplinary teams of patent attorneys and attorneys-at-law working side by side. The firm approached AI the same way, methodically, with a clear sense of where it adds leverage and where an experienced attorney’s judgment remains irreplaceable.
This article is the second of a series of Patent Trial & Appeal Board (PTAB) case studies (see Part I ), which aims to inform applicants’ approach to satisfying the written description and enablement requirements for patenting artificial intelligence (AI) and machine learning technologies.
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
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. Key takeaways • AI has raised the payoff for codifying patent practice. Codification now guides AI-assisted drafting and review directly, not just junior training. • A purpose-built patent platform can encode a large body of best practice out of the box, so a team can begin with that foundation rather than write its own. • Solve Intelligence maintains its shared foundation across more than 700 IP teams, keeping it current far more efficiently than any single team could alone. • The strategic choice is how much of your own practice to codify on top; scarce expert time should go to the standards and judgment that differentiate your work. • A named professional still signs off on every filing, so accountability for the result never shifts to the AI.
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 Intelligence is pleased to announce a strategic partnership with HGF , one of Europe’s leading intellectual property firms. The collaboration is focused on a clear objective: customising AI-driven drafting workflows to meet the specific needs of HGF and some of its clients. Rather than adopting a one-size-fits-all approach, HGF is working closely with Solve Intelligence to shape how the drafting platform behaves across different technologies, client preferences, and drafting styles. The built-in, customisable features available in Solve’s platform are what makes this possible. "We evaluated the field carefully before committing. Solve Intelligence delivered the drafting quality our attorneys demand and integrated seamlessly into how they already work. We are investing in the foundation for HGF's future practice." Richard Hodkinson, Chief Technology Officer at HGF
Put your time into more strategic codification and judgment that sets your work apart, and lets a specialist carry and maintain the shared foundation for your patent work. AI is changing how in-house teams and outside counsel approach patent work. One reason is that it has raised the payoff for turning a practice into AI templates, instructions, and review criteria that run at scale. Let’s call that codification. A purpose-built platform already encodes a great deal of best practice out of the box, and a team can layer its own on top with custom AI templates and instructions. So the real question is not whether to codify, but how much to do yourself and how much to leave to a platform built for the work. There is no fixed formula, only a sensible division of labor. Key Takeaways: • AI has raised the payoff for codifying patent practice: a written standard now guides AI-assisted drafting and review directly, not just junior training. • A purpose-built patent platform encodes a large body of best practice out of the box, so a team can run on that foundation without writing its own. • Solve Intelligence maintains its shared foundation across more than 700 IP teams, keeping it current far more efficiently than any single team could alone. • The strategic choice is how much of your own practice to codify on top; scarce expert time belongs on the standards and judgment that differentiate your work. • A named professional still signs off on every filing regardless of the tools used, so accountability for the result never moves to the AI.
Solve Intelligence participated as a sponsor of FICPI’s ABC Meeting 2026 in Nashville, with CEO and Co-founder Chris Parsonson , demonstrating the practical application of a purpose-built patent AI platform. Patent attorneys and litigators convened for a key session addressing a central question: what is required for AI to be ready for patent practice? Key Takeaways: Solve Intelligence supports the full patent lifecycle across 700+ IP firms, from invention disclosure through litigation. One firm that adopted Solve Intelligence mid-fiscal year exceeded its billing targets by $1 million by reallocating AI-saved time to higher-value work. In-house teams now require outside counsel to use AI tools, making AI fluency a firm selection criterion rather than a differentiator. Attorneys report that ROI is not simply about increasing speed, but about reallocating the time saved to higher-value strategies, cross-sell analysis, and client insights.
Solve Intelligence cuts the time attorneys spend on patent work by half . This lets a solo practitioner or small patent firm widen their offering without widening headcount. Work that a small practice once had to outsource can now be brought in-house, including creating patent drawings and prior art searching. The results are faster turnaround and higher margins for small firms. These time savings also free up capacity to offer ancillary services like landscaping, freedom-to-operate analysis, and infringement detection, work that was historically hard to do for small firms because of the manual effort involved. Key Takeaways: AI lets small firms bring outsourced work back in-house, including patent drawings and prior art search, improving margins and shortening turnaround. AI makes patent attorneys more productive , freeing capacity for landscaping, FTO, and infringement detection work. Patent work is structurally complex, so purpose-built patent AI, not a general chatbot, is what delivers reliable output.
Founded in Malmö over three decades ago, Hansson Thyresson has built its reputation on close client relationships paired with deep technical and legal expertise. When the firm decided to integrate AI into its practice, it looked for a platform that could deliver enterprise-grade capability. They chose Solve Intelligence. Key Takeaways: Hansson Thyresson has adopted Solve Intelligence for patent application drafting, bringing enterprise-grade AI into the firm's workflows. The firm pairs Solve Intelligence with its hands-on, attorney-led service model, keeping practitioners in control of every output. For Hansson Thyresson, Solve Intelligence amplifies attorney expertise, improving work quality and focus on strategic work that matters most to clients.
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R&D teams use patent landscape analysis to locate uncharted areas of a technology field, assess freedom-to-operate (FTO), and focus development resources on the areas of highest commercial value and broadest potential claim coverage. Key Takeaways: A patent landscape search locates whitespace; a novelty search locates prior art blockers. Patent landscape outputs require contextual analysis; volume alone does not determine opportunity or density. Solve’s Charts tool scans millions of patents from a single file upload and leverages agentic searching, replacing manual iterative keyword & semantic search.
At IPBC Global 2026, Solve Intelligence was proud to be a sponsor of the conversations shaping the future of intellectual property. At the conference, we demonstrated how our platform amplifies end-to-end patent workflows, including licensing, litigation, and IP-backed finance. Key Takeaways: Generic LLMs cannot perform the structured legal reasoning and claim analysis that patent licensing and litigation require. AI lowers the cost of analysing portfolios, from claim-to-product mappings to validity analyses, accelerating both sides of licensing negotiations. IP-backed finance, insurance, and M&A due diligence are growing in sophistication and volume. The profession faces a capacity gap that generic AI tools are not designed to close.
A freedom to operate (FTO) analysis is a claim-by-claim assessment of whether a commercial activity would infringe any third-party patents in the markets where it will take place. AI speeds it up by handling the parts that scale badly by hand: surfacing relevant patents, mapping product features against claims element by element, pulling legal status by jurisdiction, and producing a cited, structured draft for the attorney to review and refine. Key takeaways • FTO analysis determines whether a product infringes third-party patents. • A valid patent on your own invention doesn’t guarantee freedom to operate. • AI compresses the slowest stages of FTO, including search, triage, and element-by-element claim mapping, while the attorney retains the legal judgment and owns the opinion. • Generalist AI and purpose-built patent tools share a surface format; but FTO reliability depends on integration, not interface.
An invalidity claim chart is a structured document that maps, for example, each limitation of a patent claim against prior art to show the patent should never have been granted. If you’re defending against infringement allegations, preparing an IPR petition, opposing a European patent, or advising a client on patent risk, knowing how to build one correctly is non-negotiable. Key Takeaways: • A well-built invalidity chart maps every claim limitation to prior art, element by element, with pinpoint citations to the exact column, line, page, or figure. • When IPRs reach a final written decision, the PTAB now finds every challenged claim unpatentable around 70% of the time; and the chart is a key component of getting a petition instituted in the first place. • Solve Intelligence’s Charts generates fully cited, limitation-by-limitation invalidity charts in minutes rather than days, flags weak limitation coverage candidly, and lets attorneys inspect the reasoning behind every mapping.
Generic and biosimilar IP teams are already using AI for prosecution history and FTO work. The live debate is not about adoption, but internal framing of quality and coverage extension without reducing headcount. The teams furthest along chose the former. Key Takeaways: Generic and biosimilar IP teams use AI primarily for prosecution history summaries, invalidity analysis and FTO claim charting. Viewing AI as a quality and coverage extension drives durable internal adoption. General-purpose AI cannot reliably interpret claim scope from prosecution history; patent-specific tools are required.
At Solve Intelligence , we build AI tools purpose-built for patent prosecution and opposition workflows. European teams, including cross-Atlantic firms like HG , use Solve Intelligence to stay ahead of EPO doctrine shifts as they happen. In this article, we cover the three referred questions in G 1/26, the practical implications for prosecution and opposition teams, and what to do before the decision lands. Key takeaways G 1/26 asks whether G 1/24's rule to consult the description extends from patentability assessment to Article 123(2) added matter. The underlying case (T 873/24) turns on whether "ratio of titanium to nitrogen in excess of 3.42" means a weight ratio or a molar ratio. The referral poses three sets of questions: admissibility under Article 112(1), the reach of the description in claim interpretation, and the consequences for Article 123(2). If the Enlarged Board extends G 1/24 to Article 123(2), description-based narrowing applies to added-matter assessment across all European proceedings.
The 8th UCL Patents and Standards conference brought together all the key standard essential patent (SEP) players on both the holder and implementer sides. By the end of day two, one technical question kept resurfacing across panels that were nominally discussing other topics. How does anyone actually assess essentiality and validity at the scale modern declared portfolios now reach? At Solve Intelligence , this is the question we have built our platform to answer. Key takeaways At today's portfolio scales, AI is a precondition for SEP essentiality and validity assessment, not an enhancement of human review. Streaming standards are fully in SEP territory, bringing implementers with no licensing history into the same mapping problems as in cellular standards. SEP disputes default to parallel multi-jurisdiction proceedings, requiring position alignment across every forum before the first filing.
Anthropic's Code with Claude convened the global community of developers, founders, and researchers building applied AI on Claude. Solve Intelligence was invited to speak from the stage on what we have learned building AI for patent professionals, and the conference was a useful reminder of why domain-specific software matters in high-stakes legal work.
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Three years in, the Unified Patent Court is no longer just a faster route through European patent litigation. It is becoming a single venue capable of resolving infringement across the UK, Switzerland, Turkey and Spain in one action. That shift has one source: the CJEU's BSH v Electrolux ruling, and what UPC divisions have done with it since February 2025. The court has issued more than 1,800 decisions, with around 700 new actions a year and 31 already citing BSH. For teams navigating that volume across multiple jurisdictions, AI-assisted research platforms like Solve Intelligence exist for exactly this kind of work.
Solve Intelligence partnered with AmLaw 100 firm Haynes Boone to bring together 100+ senior IP leaders in Silicon Valley for a candid discussion on how AI is being used in patent practice today, and how that's shifting over the next 12 months. The evening was led by Leah Poynter Waterland (Sr. Director, Cisco), Jeff Draeger (Chief Patent Counsel, Intel), David McCombs (Partner and Board Member, Haynes Boone), Tony Capecci (Director of Practice Innovation, Haynes Boone), and Mallun Yen (Founder, Operator Collective; IP leader and Ex-Cisco). The room was 70% in-house, drawing Heads of IP and senior IP leaders from across enterprise software and cloud (Microsoft, IBM, Snowflake), semiconductors (Intel, Applied Materials), life sciences (Johnson & Johnson, Pfizer, Gilead), mobility and autonomy (Tesla, Waymo), connected devices and networks (Cisco, Samsung Research America), and AI labs (Mistral AI). The remaining 30% were outside counsel from firms including BCLP, Finnegan, Perkins Coie, Procopio, and Skadden. Key Insights Today, Solve supports global IP teams deploying AI agents for large-scale tasks including search across millions of patent and non-patent literature, portfolio analysis on thousands of assets, and claim charting, focussed on transparent source-backed and auditable outputs. Every IP leader in the room had either rolled out an AI patent platform or was in active procurement. Successful AI implementation requires collaboration and trusted long-term partnerships between IP teams, vendors, and outside counsel. Solve CEO Chris Parsonson expects per-user token usage to grow more than 1000x over the next 12 months.
AI inventorship is now settled law across major jurisdictions, and inventive step is the new battleground for AI patents. These were some of the central conclusions of the 2nd AI & IP Forum in Munich. The full-day programme tackled the most pressing questions at the intersection of artificial intelligence and intellectual property. Our CEO, Chris Parsonson , joined a panel on Technology and Security Considerations for AI Systems. Chris leads Solve Intelligence, the purpose-built AI platform for patent professionals, so the panel's themes around sovereign AI, confidentiality , and human-in-the-loop control sit at the centre of our daily work.
INTA's 148th Annual Meeting brought nearly 10,000 IP professionals from over 145 jurisdictions to London May 2 to 6. The question at the conference was no longer whether AI belongs in IP practice. Here are three key observations from the week that we think matter for where the profession is heading.
The Federal Circuit Panel's April 16, 2026 decision in Teva v. Eli Lilly reinstates a $176.5M verdict and draws a clear distinction under §112 between method-of-treatment and composition claims. The decision highlights the importance of drafting choices, like those made by Teva 2006. Teva shows how much §112 outcomes turn on drafting choices rather than the volume of disclosure. From a specification describing a single humanized antibody, the patentee framed the invention as a method of treatment, anchored the genus to a known biological target, and relied on humanization as routine art within the POSA's knowledge. These are structural choices, made years before litigation, that shape how a patent reads in enforcement decades later. These choices are exactly what purpose-built tools like Solve Intelligence are designed to surface early on, during drafting, when they can be considered consciously and proactively. The alternative may be that issues only become apparent during litigation, when it is often too late to change a decision that was made previously, whether intentionally or not. Key takeaways Teva v. Eli Lilly (Fed. Cir. Apr. 16, 2026) marks the first clear limit on Amgen v. Sanofi. Amgen's §112 calculus does not extend to method-of-treatment claims reciting an antibody genus. Same specification, same genus, yet the antibody claims failed in IPR while the headache claims won at trial. One humanized antibody, a known biological target, and routine humanization techniques were enough to satisfy §112. Four drafting choices won the case: claim category, functional anchoring, routine art, one embodiment. Teva is a re-opening event for life sciences portfolios with genus claims.
Solve Intelligence has acquired ClaimWise, an AI start-up for European patent attorneys. With the acquisition of ClaimWise, Solve Intelligence is bolstering its support for European prosecution, opposition and litigation workflows, cementing its place as the go-to AI platform for European patent practice. ClaimWise is our second acquisition this year, following Palito earlier in 2026 . With this acquisition, Solve Intelligence now serves over 600 firms and in-house teams.
Last week, we shared how Solve Intelligence is powered by Claude across our platform, from patent application drafting to office action responses and claim chart generation. We’re now taking the next step: making a selection of Solve Intelligence’s capabilities accessible inside Claude through our new MCP server , available from today. This MCP connection means that users who have both a Solve Intelligence subscription and a Claude subscription can use some basic Solve features directly within Claude, so long as the connection is enabled. Claude gains access to global patent literature across every major jurisdiction; non-patent literature including scientific papers, books, theses, datasets, and journals; patent legal texts and case law across key jurisdictions including the US, Europe, Japan, and Australia; and SEP technical standard documentation. A Solve subscription is still required to use this integration.
The leading in-house and outside counsel life sciences patent teams have voted Solve Intelligence as the winner of the Technology Solution of the Year Award at the 2026 Life Sciences Patent Network (LSPN) Spring Meeting in Boston, recognising our impact on the way life sciences and chemistry IP teams draft, prosecute, and analyse patents.
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The American Bar Association’s Intellectual Property Law Section Spring Conference (ABA-IPL) remains one of the premier annual gatherings for IP professionals, bringing together practitioners, in-house counsel, academics, and policymakers to explore the latest developments shaping the field. Solve Intelligence was invited not only to attend, but to share their expertise on the concluding panel as leaders in AI.
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Sughrue Mion has always set the standard for what patent prosecution looks like. Founded in 1957, the firm has obtained more U.S. patents than any other law firm in the world. That record is built on deep technical expertise, disciplined prosecution strategy, and a culture that takes the quality of every work product seriously. When Sughrue decided to integrate AI into patent workflows for select clients, their approach reflected that culture. Sughrue thoughtfully structured its implementation, and demonstrated a clear vision of where technology and AI adds value and where attorney judgment remains irreplaceable. Key Insights Sughrue adopted Solve Intelligence's platform for certain clients across Drafting, Prosecution, and Charts following firm-wide testing, culminating in an enterprise partnership. The rollout was driven by Firm leadership prioritising practitioner education and a structured implementation framework from day one. Solve Intelligence is now integrated into numerous preparation and prosecution workflows, helping Sughrue's attorneys work faster, think more expansively, and deliver higher-quality outcomes for a global client base.
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At Solve Intelligence, we believe the future of intellectual property belongs to professionals who can combine deep legal expertise with the most capable AI available. That's why our platform is powered by Claude, and why we're expanding what's possible for patent professionals and inventors worldwide.
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Preliminary injunctions, or “provisional measures” in Unified Patent Court (UPC) terminology, have become the most consequential procedural tool in European patent litigation. In under three years, the UPC has issued 63 decisions across 88 cases , with filings accelerating year on year. The analytical rigour courts demand has increased at precisely the moment timelines have compressed. For patent teams on both sides, the procedural reality is stark: court-ready claim analysis that once took months must now be produced in days, at a depth that no longer rewards manual workflows. Tools like Solve Intelligence’s Charts are emerging as a response to that structural pressure, compressing the mechanical phases of claim charting while preserving the practitioner-led judgment that courts expect.
Solve Intelligence is co-hosting a live webinar with Patenza on Thursday, 30 April 2026 at 11:00 AM CEST . The session is a hands-on masterclass on prompt engineering, tailored specifically to the workflows, drafting conventions, and procedural realities of German patent practice. Interested attendees are encouraged to register in advance to secure their spot and to submit questions ahead of the live Q&A. Register here.
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Shumaker is reinforcing its commitment to innovation and client service with Solve Intelligence. By integrating Solve Intelligence, Shumaker is strengthening its ability to help clients move from invention to protection faster while maintaining the precision required for successful patent prosecution. Solve Intelligence allows Shumaker’s IP lawyers to focus more on crafting strong claims, identifying potential risks, and aligning patent strategy with each client’s broader business objectives. As innovation accelerates across industries, companies are under increasing pressure to protect their IP quickly and effectively. Patrick Horne, Partner and Intellectual Property National Service Line Leader at Shumaker, describes the value of Solve Intelligence. “Solve Intelligence provides our team with powerful tools that enhance the patent drafting process. This technology allows us to focus even more of our time on strategy, claim development, and protecting our clients’ innovations, while improving efficiency in the preparation of high-caliber patent applications.”
The Unified Patent Court (UPC) has been open since June 2023, but how far claim scope extends beyond literal wording is only now taking shape. The UPC Agreement says nothing about equivalents; Article 2 of the Protocol on Article 69 EPC provides the only legal hook, and what it means in practice is being written case by case, across local divisions with no binding Court of Appeal ruling to anchor them. For practitioners drafting claims today, this is not abstract: it shapes claim structure, functional language choices, and whether your description helps or hurts at enforcement. Solve Intelligence helps practitioners navigate this uncertainty before cases reach court.
If you've been drafting patents for any length of time, you know the real bottleneck is often not the drafting itself. It's the messy inputs that precede it: partial forms, internal review decks, or email threads where the inventive aspects are buried. Getting from that to a coherent starting point for a draft consumes time most practices simply can't afford. AI can perform much of that translation work: extracting what matters, flagging what's missing, and generating the necessary follow-up questions based on holes and shortcomings. But it must operate inside proper confidentiality controls, and its output requires attorney review before going near a draft. This guide covers how that works in practice in Solve Intelligence's platform . Key takeaways The disclosure bottleneck is upstream; AI structures messy inputs before the drafting phase begins. AI extracts features, normalises terminology, surfaces gaps, and generates inventor questions, but attorney review is mandatory. The danger is plausible but fabricated detail, not obvious errors. Watch for AI-generated parameters or 'helpful' specifics. Disclosures contain trade secrets and unpublished IP. Use only tools with verified zero-training, zero-retention policies and enterprise-grade security. A sensible pilot, without client approval, uses anonymised or historical disclosures to define 'good' output and track key metrics over limited timeframe.
Nielsen, a global leader in media audience measurement operating in over 50 countries, manages an industry-leading patent portfolio protecting innovations across a variety of fields, including data science, media measurement technology, and viewer analytics. Operating at the intersection of data science and an ever-changing media landscape requires constant innovation to keep pace. Supporting this innovation velocity requires IP operations that can scale without compromising quality. Nielsen's in-house team adopted Solve Intelligence as their AI patent platform following a comprehensive evaluation process in Q4 2025. The partnership between Nielsen and Solve Intelligence reflects a shared commitment to precision and enabling practitioners to do their best work more efficiently.
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Solve Intelligence has acquired Palito.ai, a Munich-based startup specialising in AI-powered patent litigation and prior art analysis. The acquisition deepens Solve’s investment in patent litigation, adding Palito's strengths in validity analysis, case law research, and European patent workflows to Solve’s existing Charts product. The result is a single platform where IP professionals can handle invalidity claim charts, SEP claim charts, freedom-to-operate and clearance analyses, infringement mappings, claim construction analyses, portfolio analyses, and more. Solve Intelligence is an AI platform for IP professionals, covering patent drafting, prosecution, and litigation. Palito.ai is a Munich-based startup specialising in AI-powered validity analysis and European patent litigation workflows. At a glance: Solve Intelligence acquires Munich-based Palito.ai Adds validity analysis, prior art research, EPO/UPC/German court workflows New Munich office established Existing Charts users get expanded litigation capabilities
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Two years ago, the dominant argument in the legal industry was whether AI had any place in the profession at all. That debate is over. Analysts are now calling 2026 the year AI moves from an “interesting tool” to “operational infrastructure” . The speed at which that narrative has changed tells you everything about where the industry is heading. Key takeaways The legal profession's central question has moved from "can we trust this?" to "how do we integrate this properly?" AI adoption across IP practice has risen from 57% in 2023 to 85% in 2025. Firms are not just trialling AI tools, they are expanding its use across full workflows. Practitioners using Solve Intelligence grew ~560% in 2025 alone. Clearer regulatory guidance has removed one of the most significant psychological barriers to adoption. The profile of firms now adopting AI has changed: these are not early experimenters, but some of the most demanding legal professionals in the world.
Solve Intelligence has been ranked the number one intellectual property platform in the latest Legal AI survey published by SKILLS (the Strategic Knowledge & Innovation Legal Leaders Summit). The study surveyed 130 leaders at the world's top law firms about their legal AI product usage across every major practice area, scoring platforms based on live deployments, active pilots, and tools under consideration. In the Patents/IP category, Solve Intelligence placed first with a weighted score of 67, making it the most widely-used platform in the category. See the full report here .
As patent practitioners, the choice to “do nothing” about AI is not a neutral act. Law firms or in-house counsel that delay the adoption of AI may believe they are minimizing risk, but oftentimes they are taking on a different set of less visible, long-term risks. These hidden costs can accumulate quickly, from compounding inefficiencies in traditional patent drafting workflows to missed revenue opportunities that remain untapped without leveraging AI-driven capabilities. So, what can patent practitioners do to stay ahead of the game? Here is what the Solve Intelligence team has seen speaking with thousands of practitioners. Key takeaways Waiting to adopt AI is itself a strategic decision with compounding costs. Manual patent workflows create time, quality, and knowledge bottlenecks that grow over time. Firms already experimenting with AI gain operational insight that late adopters cannot shortcut. Low-risk entry points let practitioners build confidence without compromising legal judgment.
Legal AI platforms are valuable productivity tools, powered by large language models and enriched with legal data sources, firm-specific knowledge, and purpose-built workflows, they perform well on tasks like legal research, document summarisation, and contract or email drafting. But their workflows are optimised for breadth across practice areas, not for the structural, technical, and jurisdictional depth that patent work requires. For IP teams that already have access to a generalist platform, or are trying one out, the natural follow-up question is whether a vertical solution adds enough to justify the investment. At Solve Intelligence, we build AI specifically for patent practitioners. In our experience scaling the platform to over 700+ IP teams , there is no question that patent-specific tooling delivers ROI that generalist platforms alone cannot. This article sets out why. Key takeaways Generalist legal AI tools weren't trained for the structural depth patent work demands. Solve Intelligence is shaped by in-house patent attorneys who joined Solve from firms like Carpmaels & Ransford and Fish & Richardson. Custom templating lets attorneys match output to house style, client/technology area, or jurisdiction. Generalist and patent-specific AI are complementary investments, not competing ones.
When we sat down with Bob Hansen for this conversation, we knew it would be grounded in both legal depth and real-world business experience. Bob is a founding partner of The Marbury Law Group and has extensive experience across patent prosecution, litigation, licensing, portfolio strategy, and complex IP transactions. But what makes his perspective particularly compelling is that he also brings 20 years of real-world experience as an engineer, program manager, and business executive in Fortune 50 companies and start-ups. He understands firsthand how innovation moves from idea to product, and how intellectual property law fits into that journey. That dual lens is exactly why we wanted to have this discussion. Bob evaluates technology not just as a patent attorney, but as someone who has managed engineering teams, navigated acquisitions and divestitures, raised capital, and built businesses. When someone with that background says AI has been transformative and backs it up with measurable 3 to 4x efficiency gains, it’s worth listening. Key Insights AI adoption requires proof. Bob and his team tested multiple tools before committing, and only moved forward once they saw quantifiable results. 3 to 4x efficiency gains changed the business case. By tracking his own drafting time, Bob demonstrated that AI-enabled workflows made fixed-fee work viable at partner rates. Demonstration drives adoption. Live drafting sessions, client transparency, and side-by-side cost comparisons created full buy-in from both clients and colleagues. Integrated chat removes friction. Keeping research, drafting, and revisions inside one contextual workspace eliminated copy-paste workflows and saved significant time. Context is a force multiplier. AI performs best when it understands the full invention disclosure, file history, and drafting materials in one place. Speed expands strategic value. Faster drafting didn’t just save time - it enabled better coverage, stronger enablement, and real-time responsiveness to client needs. About Marbury Law The Marbury Law Group is a premier mid-size, full-service intellectual property and technology law firm in the Washington, D.C. area, with additional strength in commercial law, litigation, and trademark litigation. Recognized by Juristat as a top 35 law firm nationwide and holding Martindale-Hubbell’s AV® Preeminent™ Peer Review Rating, Marbury serves clients ranging from Fortune 500 companies and mid-size technology businesses to high-tech startups and inventors. Its practitioners bring unusually wide-ranging experience, including former technology executives, government R&D managers, startup founders, in-house counsel, “big-law” attorneys, USPTO patent examiners, and judicial clerks. Marbury delivers “big-law” service with the flexibility and personal attention of a smaller firm, pairing high-quality work with efficient, budget-aware billing. Based near the USPTO, the firm has drafted and prosecuted thousands of U.S. and foreign patent applications and trademarks, and advises on IP strategy, diligence, and licensing. Formed in 2009 through the merger of two established practices (with roots dating back to 1994), the firm takes its name from Marbury v. Madison (1803), the landmark Supreme Court case that established judicial review.
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Patent drafting doesn’t end when the first draft is complete. In many ways, the most important work begins at review. Jurisdictional compliance, internal style alignment, claim clarity, sufficiency of disclosure, and formal requirements. Each aspect of drafting applications must be carefully checked before filing. Yet a thorough review is time-intensive, difficult to standardize, and hard to scale across teams and large portfolios, especially when up against a tight deadline. Enter Solve Review With Solve Review, practitioners can run structured, customizable AI-powered reviews in minutes rather than hours, while maintaining transparency, collaboration, and full control over the output. Teams using Solve Review report dramatically, with multi-pass manual reviews that previously took three to four hours completing in a fraction of the time Key benefits AI-powered patent reviews in minutes Each review is fully customizable Save your reviews as templates, run multiple reviews per application Full transparency of working out and results Resolve issues detected by Solve Review with AI
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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.
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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 .
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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 UK moves closer to EPO, inventive step becomes the main battleground. Ordinary hardware avoids exclusion, but may not support inventiveness. Only technical features count at inventive step, not business aims. Neural networks are treated as software, no special treatment either way. Draft around technical contribution, measurable effects, and system level impact.
A lot has happened in the last two months. We wanted to take a moment to share what we've been building, who's joined us, and where we're headed next. Since we started Solve, the goal has been simple: help IP teams do their best work by combining real-world patent expertise with deep AI research, intuitive UX, and state-of-the-art security. The momentum we're seeing across the business tells us the market agrees as 400+ IP teams across 6 continents now use Solve . Here's what's new.
Last week, my colleagues and I attended the annual meeting of AUTM, the global association for technology transfer professionals. For anyone building in the intellectual property (IP) space, it’s one of the most important rooms you can be in. The three-day conference brings together higher education decision-makers from around the world who are shaping how intellectual property is evaluated, protected, and commercialized. This year’s conversations revealed something important: the question is no longer if AI will influence tech transfer, but instead about how institutions will integrate it.
Artificial intelligence (AI) is a fast-evolving field with new technical methods, systems, and products constantly being developed. This growth has also been reflected in the dramatic increase in patent filings for AI-related inventions. According to Patents and Artificial Intelligence: A Primer from the Center for Security and Emerging Technology, more than ten times as many AI-related patent applications were published worldwide in 2019 than in 2013, and the increasing trend has only continued since. Although AI-related patent applications have been on the rise, explicit guidance on patentability requirements have only recently begun to be published by patent offices around the world. Indeed, as a burgeoning field of technology, AI inventions have unique features, such as the importance of training data and the lack of explainability and predictability of trained AI models, that differentiate such innovations from traditional types of computer-implemented inventions (CII). These features raise questions about the interpretation of disclosure requirements, among other patentability requirements, for AI-related inventions. For example, how much information, such as source code, training data sets, or machine learning model architectures, should be provided to satisfy the written description and enablement requirements of Title 35 of the U.S. Code § 112(a) or analogs in other patent jurisdictions? As we await further official guidance from the U.S. Patent & Trademark Office (USPTO) on disclosure requirements for AI-related inventions, we can gather initial indications from recent patent prosecution decisions from the Patent Trial & Appeal Board (PTAB) on such issues. In this article, we study a selection of PTAB appeals decisions for applications for AI-related inventions rejected under § 112. To set the background, we first review a classification of AI inventions and USPTO guidelines on disclosure requirements for computer-implemented inventions. After analyzing three case studies, we conclude with general takeaways and best practices, which emphasize that applicants must disclose specific algorithms and implementation details, not just desired outcomes, to satisfy written description requirements.
In 2024, the Institute of Professional Representatives before the European Patent Office (epi) published its Guidelines on the Use of Generative AI in the Work of Patent Attorneys . These Guidelines provide practical guardrails for the responsible use of generative AI in patent practice, reaffirming that professional responsibility, confidentiality, and transparency remain central when AI tools are used. In our earlier blog post , we outlined the key principles set out in the epi Guidelines. Since then, the Guidelines themselves have not changed. However, the use of AI in patent workflows has continued to mature, and so has Solve Intelligence. This update highlights how Solve Intelligence supports compliance with the epi Guidelines in day-to-day practice, focusing on concrete product capabilities and supporting processes.
Artificial intelligence is already reshaping patent practice, but adopting it swiftly, efficiently and securely is where most firms get stuck. Patent professionals know the productivity upside to using gen AI tools, yet often get derailed when informal experiments run into real-world problems: client confidentiality concerns, inferior work-product quality, delayed internal approvals, and decision-fatigue. This guide lays out a practical, 30-day plan for adopting AI in patent work, moving from ad hoc trials to a controlled, firm-ready strategy. It shows how you can run a focused pilot, set clear guardrails, train attorneys, and document decisions in a way that satisfies partners, clients, and internal stakeholders.
The European Patent Office has published a preview of its Guidelines for Examination, effective April 2026. This update incorporates the landmark Enlarged Board decisions G 1/24 (claim interpretation) and G 1/23 (products on the market), alongside a significant change of practice for selection inventions, new rules on colour drawings, and the EPO's first formal guidance on artificial intelligence.
Hauptman Ham is redefining patent prosecution with Solve Intelligence. By integrating AI-driven workflows into their patent practice, Hauptman Ham attorneys and agents are delivering office action responses that set a new standard—precise, insightful, and creatively crafted. Their clients are gaining a strategic edge with more innovative outcomes that stand out in a competitive landscape. Firm leader Ron Embry describes the value of Solve Intelligence in Hauptman Ham’s patent practice. “The Patent Copilot system allows practitioners at Hauptman Ham to use more creative strategies in pursuit of broad, defensible patent claims for our clients. We use the advanced functionality of the Solve Intelligence system to explore multiple potential avenues in responding to rejections and prosecuting families of patent applications. We find the tool to be quite useful in integrating different legal strategies into one unified, comprehensive, and nuanced approach to obtaining patent protection for our clients.”
The EPO and IP Australia are launching a new PCT pilot programme on 1 March 2026 which will allow Australian applicants to designate the EPO as their International Searching and Preliminary Examining Authorities (ISA and IPEA). Given the EPO’s rigorous approach to clarity and support requirements, for this pilot programme to succeed, Australian applicants and patent practitioners will have to adapt to draft international applications with EPO-specific requirements in mind. The launch of this pilot programme will add a new layer of complexity — (and opportunity) for patent practitioners. In a landscape where jurisdictional nuance can shape international search and examination outcomes, AI‑augmented tools such as Solve Intelligence's Patent Copilot TM are becoming increasingly valuable.
AI is now a daily tool for many patent attorneys; from drafting assistance to prior art searches. But questions about inventorship and ethics persist. Courts and patent offices worldwide continue to grapple with whether AI can be considered an inventor, and the recent November 2025 USPTO guidance has brought fresh clarity to this evolving area. This article explores where the line is drawn between AI as a tool and AI as an inventor, and how attorneys can use AI responsibly while meeting their professional obligations.
As AI adoption in patent practice continues to accelerate, a critically important question emerges—How do you get AI to deliver the work product you need and the quality you want? Please join Solve Intelligence and IPWatchdog on Thursday, February 5, at 12 PM ET for a detailed examination of the practical application of AI prompting for patent practice. This webinar is designed for patent attorneys and in-house counsel who want to move beyond experimentation and understand how prompt engineering can be used as a repeatable skill, enabling more efficient, higher-quality patent work across AI-enabled workflows. Register here .
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We are delighted to announce that Khurana & Khurana (K&K) is deploying Solve Intelligence across their extensive global practice. Professionals at K&K leverage Solve Intelligence to analyze prior art, formulate response strategies, and draft patent applications more efficiently. The platform is designed to keep legal professionals firmly in control throughout the entire process, allowing them to use AI as an extension of their legal expertise.
SEP claim charting can be a bottleneck in patent licensing and portfolio management: too time-consuming and expensive to perform rigorously at scale, yet too important to skip. Solve Intelligence is changing this equation, allowing practitioners to generate high-quality claim charts in minutes rather than hours, while surfacing insights that might otherwise be missed.
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Solve Intelligence is proud to sponsor and attend the AUTM 2026 Annual Meeting in Seattle, February 8–11, 2026. AUTM's Annual Meeting is the premier gathering for technology transfer professionals, bringing together university tech transfer offices (TTOs), research institutions, industry partners, and IP professionals to connect, share insights, and develop partnerships that bring innovations to the marketplace. We're sponsoring AUTM 2026 because we believe AI has a critical role to play in accelerating tech transfer, and we're committed to supporting the professionals who make it happen.
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Artificial intelligence is becoming an everyday reality in intellectual property workflows. In a noteworthy development, the European Patent Office (EPO) has announced that it will expand the use of AI to assist in drafting minutes of oral proceedings in examination and opposition cases throughout 2026. This move follows a successful pilot phase involving approximately 150 oral proceedings since May 2025.
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As reported by Sifted, Tech Funding News, Artificial Lawyer, Law360 and Law.com, we are excited to announce that we have raised our $40M Series B, taking our total funding to $55M. This round comes just months after our $12M Series A. It’s a reflection of how quickly the IP industry is adopting Solve Intelligence. We are becoming the platform for in-house and outside counsel IP teams to collaborate across every part of the patent process. We’re hiring: https://www.ycombinator.com/companies/solve-intelligence/jobs
After working with hundreds of IP teams globally to roll out AI patent software, we have learned that the firms who build a deliberate onboarding process for firm-wide adoption have the quickest, highest rate of success. At Solve, we’ve seen that success and failure for proper AI adoption isn’t just about the technology. Rather, it’s the process, the support, and the people behind it.
The Professional Conduct Committee (PCC) of the The Institute of Professional Representatives before the European Patent Office (epi) recently published an opinion on the interpretation of the epi Guidelines on AI in the work of patent attorneys. In particular, the PCC responded to an enquiry regarding guideline 4 and what patent attorneys can do to establish client consent for using AI tools during the course of their practice.
In September 2025, we brought together our Customer Advisory Board (CAB) for an in-person meeting at the Hotel Del Coronado in San Diego, just ahead of the IPO Annual Meeting. Our CAB represents some of the most influential voices in IP. Collectively, the group manages over 160,000 active patents while prosecuting more than 20,000 applications annually. Our CAB members span the full spectrum of practice areas, from software and electrical to mechanical, life sciences, and pharmaceuticals. The composition is 80% private practice and 20% in-house IP teams, giving us a well-rounded perspective on the challenges and opportunities facing the profession when it comes to AI integration.
Artificial intelligence is no longer future-thinking for IP professionals. AI patent software is reshaping how teams draft, search, and manage patent portfolios today. At this year's Future IP UK conference , IP leaders from industry, law, and government shared what it actually takes to bring AI into established workflows. The conversation revealed that the approach in the UK, generally, has been measured and focused on long-term value over quick wins. At Solve Intelligence, we've been at the coalface of this transformation globally, working directly with private practice firms and in-house IP teams across multiple jurisdictions. The themes emerging from Future IP UK echo insights we've been exploring for the past two years.
AI adoption in patent law firms rarely stalls because partners doubt the technology. The real barrier is commercial justification. When evaluating any significant investment, partners ask the same fundamental questions: Does this software actually save us money? Will it create capacity we can monetize? Can it generate new revenue streams? Solve Intelligence’s Patent Copilot™ was built with these questions top of mind. This article provides a high-level overview of the business case and ROI breakdown of AI patent drafting and partnering with Solve Intelligence.
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After countless conversations with patent attorneys across 5 continents, it’s clear that patent practitioners want AI tools that work like a trusted colleague who is always available, incredibly thorough, and has a genuine understanding of patent law. At Solve Intelligence, we know what patent attorneys are dealing with because we've been there. Our team includes patent attorneys from firms like Dentons, Haley Guiliano, Quarles & Brady, and Reddie & Grose. We left private practice not to replace patent attorneys, but to build solutions to the problems we personally faced. In this post, we share the experiences of Solve Intelligence customers who explain how our AI patent platform helps them work faster, with greater accuracy, and create more time for strategic client work. Their stories highlight the real world benefits patent attorneys are seeing in practice.
“Solve Intelligence stands out for their genuine customer obsession, particularly in how they partner with users to co-create tailored templates.”
“Solve Intelligence stands out for their genuine customer obsession, particularly in how they partner with users to co-create tailored templates.”
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