was��built for��that��purpose.��

Introducing��CoCounsel��Legal Canada��

​​CoCounsel��Legal Canada is the only comprehensive AI solution for Canadian legal professionals that combines advanced AI capabilities with the authoritative depth of Westlaw content and the applied guidance of Practical Law, in a single integrated solution built for the way legal professionals work. Where other tools address parts of the legal workflow,��CoCounsel��Legal Canada is built to handle the full span of it. The result is faster, more��confident��legal work across research, document analysis, drafting, and organizational��know-how.​��

Here is what that looks like in practice:��

• Research that produces work��product.��Canadian legal professionals have had access to Deep Research on Westlaw Advantage, grounded in authoritative Westlaw content. CoCounsel Legal Canada takes that further. Through CoCounsel Legal Canada, Westlaw and Practical Law now are combined into a single query and response, surfacing answers for the user from both premium content sources. Westlaw’s legal authority and Practical Law’s applied, expert-created guidance surfaces the law and how to use it, moving from question to strategy to execution in a single workflow.�� ��
• Document analysis at��genuine��scale.��Tabular analysis allows legal teams to work through large volumes of documents in ways that weren’t previously feasible without significant resource commitment. Whether the task is due diligence, disclosure review, compliance assessment, or privilege review, CoCounsel Legal Canada surfaces risks across multiple issues simultaneously, links findings to source documents, and generates draft reports. The results are designed to be reviewed and challenged, because that is how legal work functions.��
• Drafting within existing environments.��Enhanced drafting within Microsoft Word allows lawyers to produce high-quality first drafts without leaving the tools they already use, drawing on Practical Law content and their own organizational precedents. The goal is not to replace professional judgment. It is to compress the distance between instruction and a verified, defensible final draft.��
• An expert library.��Access expert-created prompts and create custom prompts designed to help legal professionals get started faster and work with greater confidence. The library accelerates AI adoption across an organization while codifying best practices, so teams can build capability consistently rather than starting from scratch on every matter.��

​​​CoCounsel��Legal Canada integrates with Microsoft 365, leading document management systems, and HighQ, working within the infrastructure Canadian legal practices have already built rather than requiring parallel workflows or new platforms.��​​��

​​​Because the work of legal professionals doesn’t stand still, neither does CoCounsel Legal Canada. Looking further ahead, �������� will continue to build on its foundation, introducing additional agentic drafting capabilities, ways to enable more efficient lawyer verification of outputs, and next-gen capabilities that respond to a plain-language question by forming a theory and executing a plan at the level of a senior associate, drawing on Westlaw, Practical Law, and firm content throughout the workflow.​​��

“Lawyers don’t want to just operate software, and that’s not what��great��AI should do.��CoCounsel��keeps them in the analytical mindset they were trained for: going back and forth, challenging answers, and steering the work. With sourcing directly from Westlaw and Practical Law,��they’re��not wasting time second-guessing the results.��We’re��seeing adoption from associates to partners across every practice area. When it spreads that quickly, the experience just works.”
— Andrew M. Medeiros, Managing Director of Innovation, Troutman Pepper Locke LLP��

CoCounsel��Legal Canada is built to the standard legal work demands��

Powerful capabilities matter only if professionals can trust the results they produce. Legal work carries liability. Outputs inform advice. Advice affects outcomes. In that environment, “almost right” is not a workable standard.��

​​�������� uses the term Fiduciary-Grade AI��to describe what AI must be��in order to��function reliably in high-stakes professional environments, and it is the architectural foundation of��CoCounsel��Legal Canada.��​��

​​​​It means outputs grounded in authoritative, curated content, not the open internet. It means privacy and security built into the system’s architecture, not layered on as policy. It means transparent, traceable reasoning that a lawyer, client, court, or regulator can examine and challenge. And it means the continuous involvement of credentialed subject-matter experts. �������� employs thousands of lawyer editors whose work is not incidental to the product’s reliability. It is the product’s reliability.​​​��

“The reality is from what��we’re��seeing out��there,��it’s��not a fair fight right now.��CoCounsel��nailed it in terms of the user interface and making it easy for even non-technical people like me to use.”
— Ian Hull, Co-Founding Partner, Hull & Hull LLP��

The practices built today define the profession tomorrow��

The decisions being made now (the tools adopted, the workflows built, the institutional knowledge developed around how to deploy AI effectively) are the foundations of what Canadian legal practice looks like on the other side of this transition. Getting there successfully means choosing AI built for professional work, not just productivity, and investing in the workflow integration that turns capability into��a competitive��advantage.��

Canada has something valuable to contribute to the global conversation about what responsible AI adoption in regulated professions should look like. A professional culture built on precision, accountability, and trust is not an obstacle to AI adoption. It is the foundation for doing it right. The legal profession has always been defined by the trust placed in it. The practices that move deliberately now will be the ones defining what excellent Canadian legal work looks like in the years ahead.��

CoCounsel��Legal Canada is available now, and��we’re��proud to bring it to the professionals who set that standard.��

Ready to see��CoCounsel��Legal Canada in action?��.��

A �������� customer, Crowe is one of the largest public accounting and consulting firms in the United States. The firm’s decision to add Additive to its technology stack reflects both an immediate opportunity to enhance K-1 processing and a larger commitment to building a more connected, data-driven tax operation supported by modern AI tools.

For tax professionals, the challenge of ingesting and processing K-1 documents is often highly manual, time-intensive, and dependent on spreadsheet-based workflows that can slow down downstream processes during compressed compliance cycles. Additive addresses that challenge by using a GenAI-native platform to ingest and structure data from complex K-1 documents efficiently and at scale. That structured output then feeds into Crowe’s downstream partnership calculation engines and connects with other solutions across the firm’s technology ecosystem, including .

Before making its decision, Crowe conducted a rigorous cross-functional pilot of Additive across its tax practice, bringing in specialists from international, private equity, state and local, and global and high-net-worth individual tax services. The pilot helped validate not only the platform’s ability to automate complex data extraction, but also its potential to improve the quality, speed, and consistency of service delivery across multiple tax disciplines.

“The biggest advantage of Additive is how it helps us better support our clients,” said Jeffrey Mull, Partner, Crowe. “By turning complex, unstructured K-1 data into usable information more efficiently, our teams can spend less time on manual aggregation and more time focused on analysis, insights, and getting clients the answers they need, especially during compressed compliance timelines.”

For Crowe, the value of Additive extends beyond solving a single workflow issue. As tax practices become more digital and data-intensive, firms need technology that fits into real professional workflows, works across systems, and helps experienced practitioners spend more of their time where expertise matters most. The firm sees modern AI tools as an important part of how it will continue to innovate and deliver strong client outcomes in an increasingly complex environment.

“Having access to the latest technology is essential to how we continue to innovate and deliver value to our clients,” Mull added. “From an AI transformation perspective, modern tools like Additive help us unlock the value of our data in new ways, improving how we analyze information and generate insights. It also reinforces our commitment to innovation, ensuring that we are not only keeping pace with change but actively shaping how technology is used to improve the client experience.”

For ��������, Crowe’s adoption of Additive reflects a broader shift underway in the profession. Firms are increasingly looking for AI solutions that move beyond experimentation and solve practical operational challenges while strengthening the quality of professional work.

“Leading firms are looking for AI solutions that fit into real workflows and deliver measurable impact,” said Erica Butcher, General Manager of Tax, Audit & Accounting Professionals at ��������. “Crowe’s adoption of Additive shows how firms can take a focused, practical approach to using AI to improve how work gets done and strengthen client outcomes.”

Nowhere is that truer than in Section 101 patent eligibility, one of the most consequential and frustrating challenges in patent practice today, and the problem that brought and �������� together to build something new inside CoCounsel Legal.��

Why��Section��101? Why Now?��

Section 101 patent eligibility is a question at the center of most��utility��patent disputes today. It is often a decisive factor in patent litigation, and one of the quickest ways to win or lose a case. The legal test asks whether a��technical��invention is the kind of subject matter the patent system protects, meaning it must be more than a general idea and must��represent��a concrete, technical improvement.��

��In theory, the framework is clear. In practice, it is anything but:��

• Key concepts lack precise definitions, leaving��wide��room��for interpretation.����
• The analysis is deeply precedent-dependent, and��outcomes hinge on finding the right prior cases among hundreds of fact-specific��decisions.��Missing a key precedent can mean the difference between��a strong argument��and a weak one.��

And all of this unfolds under constant pressure. Clients need answers��fast;��matters are often fixed-fee, and the uncertainty is genuinely difficult to explain.��

For patent owners seeking to assert a patent, understanding its vulnerability under Section 101 is essential before litigation begins.��For defendants, a fast, reliable eligibility assessment can reveal a path to an early win.��For both sides, the current reality often looks the same: assign a��junior associate to research similar cases, spend hours or sometimes days finding the right precedents, and still wonder whether something important was missed.��

This is the kind of problem that demands a fiduciary-grade solution:��one built not��for the average task, but��for the specific, high-stakes reality of patent practice.��

Unmatched IP Expertise, Delivered at Scale��

The��Patent Claim Eligibility Analyzer��was not built by technologists who then consulted practitioners. It was built with practitioners at the center of every decision — and with a caliber of technical��expertise��on both sides that distinction shapes everything about what the��Patent Claim Eligibility Analyzer��can do.��

�������� engaged Sterne Kessler through a��forward deployed engineering motion, a model that pairs engineers who combine strong legal backgrounds with deep AI and technical��expertise��and��embeds them directly alongside practitioners.��The Thomson��Reuters��engineering team worked side by side with Sterne Kessler’s IP litigators to deeply understand their workflows, co-build the solution in rapid iterations, and move with��speed and flexibility.����

The result is a��tool��shaped by the kind of tight, trust-based collaboration that only happens when both sides bring genuine depth to the table.��

Sterne Kessler brings decades of litigation-tested intellectual property��expertise��to this partnership. The firm worked alongside ��������’ engineers and editorial teams to translate the way experienced IP��practitioners��approach Section 101 — their analytical frameworks, their precedent instincts, their litigation-proven methodologies — into a repeatable, scalable workflow now inside��CoCounsel��Legal.��

That meant curating��an initial��corpus of approximately 200 highly relevant Federal Circuit Section 101��decisions,��cases selected not by keyword, but by their factual and analytical relevance to the kinds of claims practitioners��encounter��in real matters. �������� editorial teams then reviewed and augmented that corpus, applying the same editorial rigor that underpins Westlaw.��

The result is a workflow grounded in practitioner intelligence, trusted legal content,��and engineering��— combined at a depth that general-purpose AI��tools simply cannot replicate.��

Built��for Real IP Work

The��Patent Claim Eligibility Analyzer��reflects how IP work is��actually done.

How the��Patent Claim Eligibility Analyzer��Works

1. Enter a patent claim: Select the��Patent Claim Eligibility Analyzer in��CoCounsel��Legal and paste a claim directly into the chat.
2. CoCounsel applies the same Step 1 / Step 2 logic that courts use:��The��Patent Claim Eligibility Analyzer��structures the analysis the way judges do, first asking whether the claim is directed to a general or abstract idea, then whether it adds a meaningful technical improvement.
3. CoCounsel finds the most relevant court decisions for that specific claim: Using semantic analysis rather than keyword search,��the��Patent Claim Eligibility Analyzer��matches the claim to prior Section 101 cases with similar fact patterns, so practitioners surface the right cases, not just the most��frequently��cited ones.
4. It draws from a curated corpus built by Sterne Kessler and �������� editors: The workflow leverages an initial set of approximately 200 highly relevant Section 101 cases, curated by Sterne Kessler and reviewed and augmented by �������� editorial teams.
5. It explains why each cited case matters: Rather than listing citations, CoCounsel provides reasoning that connects the claim’s language to the reasoning and outcomes in those cases, giving practitioners a litigation-ready foundation, not just a list of results.
6. Citations link directly to Westlaw: Every source is verifiable. Practitioners can validate citations and continue deeper research as needed, maintaining full accountability for the final work product.

The��Patent Claim Eligibility Analyzer��surfaces both binding and persuasive authority when factually relevant, reflecting how Section 101 arguments are��actually made��in practice.��The goal is not to replace attorney judgment. It is to give attorneys a faster, more consistent, more defensible foundation from which to exercise it, so less time is spent on the research��phase��and more time is spent on strategy, client counsel, and the work that requires human��expertise.��

For patent owners, that means a stronger, faster assessment of a patent’s eligibility risk before litigation begins.��For defendants, it means a rapid, precedent-backed read on Section 101 positions from the outset of a case.��

For both, it means a head start on brief writing, a more consistent work product across matters and experience levels, and greater confidence that no key precedent has been missed.��

A New Model��for Legal Product Innovation��

Beyond the��Patent Claim Eligibility Analyzer��itself, this partnership��represents��something worth examining at a higher level: a fundamentally different model for how legal AI products can and should be built.��

While��building useful legal technology has always required thinking like a lawyer,��the traditional approach to legal technology development��across the industry��follows a familiar pattern. Technologists��identify��a problem, build a solution, and bring it to��market. Practitioners are consulted��but they are��largely recipients��of the finished product.��Expertise��flows in one direction.��

This partnership inverts that model. Sterne Kessler did not simply advise on the��Patent Claim Eligibility Analyzer, they co-developed it, inspired by the firm’s practical methodologies for Section 101.

What began as a co-development initiative has evolved into a scalable market offering available to patent practitioners across CoCounsel Legal. In doing so, it has demonstrated what is possible when practitioners and technologists collaborate.��

That model also opens new possibilities��for how law firms think about their own��expertise. Firms are��evolving��the ways they create value from their knowledge, and this partnership is an example of what it looks like when a firm’s internal intelligence becomes a repeatable, scalable offering.��

CoCounsel��Legal’s architecture��is��designed to enable exactly this kind of��forward-deployed, domain-specific innovation, making it possible to translate specialized��expertise��into scalable, trusted AI experiences. The��Patent Claim Eligibility Analyzer��is the first proof point.��

Additional co-developed workflows are already in development, with the ambition of bringing the same practitioner-built, precedent-grounded approach to other complex areas of patent law, signaling what is possible across specialized legal domains where expertise is the differentiator and where the stakes are��too��high��for approximation.��

The Standard the Profession Deserves��

What makes the��Patent Claim Eligibility Analyzer��meaningful is not just what it does. It is the standard it was built to. Every output is grounded in a curated, editorially reviewed body of case law. Every citation links to a verifiable Westlaw source.��The analytical structure mirrors the reasoning courts��actually apply.��And the workflow is explicitly designed to support attorney judgment, not substitute for it.��

That is��fiduciary-grade AI. It is��not a general-purpose��tool��adapted��for legal work, but a purpose-built solution grounded in authoritative content, shaped by the��expertise��of practitioners who��perform��this work at the highest level, and accountable to the professional standards that patent practice demands.��

The �������� and Sterne Kessler partnership was built on that standard. And as the collaboration deepens and expands, it is the standard we��will��keep.��

Womble Bond Dickinson UK’s early adoption of CoCounsel Legal, �������� advanced fiduciary-grade AI platform for legal professionals, has become a case study in what firmwide AI integration looks like. It required vision, discipline, creative leadership, and a partnership built on radical candor.��

Setting the Stage��

CoCounsel��Legal integrates advanced AI with Westlaw and Practical Law content, as well as a firm’s own knowledge and tools, to support the full breadth of legal work—including research, document analysis, and drafting—in a single platform. When Womble Bond Dickinson��committed��to��early adoption, the platform was still in development.��Which��was precisely the point.��

What began as an evaluation of the original��CoCounsel��product evolved into a sweeping, full-scale early adoption initiative, spanning 7 of Womble Bond Dickinson’s UK offices and all 650��timekeepers (including 457 qualified lawyers)��working in��them. The goal was not simply to make the tool available. It was to make it indispensable, transforming AI use from an occasional experiment into a daily professional habit.��

Sam Dixon, Chief Innovation Officer and Partner, led the charge. His vision was anchored in a clear strategic ambition��the firm already had in place: a self-service innovation model in which every lawyer across the business has innovation as part of their role.��CoCounsel��Legal, with its intuitive interface and enterprise-wide applicability, was the right tool at the right moment to��help��make that vision real.��

A Partnership Built on Candor��

What set this initiative apart from a conventional technology rollout was the nature of the relationship between Womble Bond Dickinson and ��������. It was a co-development partnership defined by openness, mutual accountability, and a shared commitment to getting it right.��

From the outset, both teams committed to saying the quiet parts out loud. When something wasn’t working, they said so. When feedback was uncomfortable, it was shared anyway. Womble Bond Dickinson stress-tested CoCounsel Legal’s capabilities, challenged its assumptions, and provided structured, direct feedback throughout the development process. �������� listened, iterated, and acted. As a result, the firm’s input directly shaped the product before launch, a level of influence that reflects genuine partnership, not merely consultation.��

That bidirectional feedback loop ran throughout the project. The joint team, spanning Womble Bond Dickinson’s innovation and legal technology functions and �������� sales, customer success, and product teams, built in multiple touchpoints for sharing insights, surfacing issues, and refining both the product and the rollout approach. Challenges became collaborative problem-solving moments rather than blockers.��

The pilot group itself was carefully constructed to reflect the full diversity of the firm: across practice areas, job roles, seniority levels, technology comfort levels, and demographic backgrounds. This��wasn’t��a pilot of the��willing. It was a deliberate, representative sample designed to surface real-world adoption challenges before the firmwide launch.��

Bringing the Whole Firm Along��

Rather than relying on emails, slide decks, and vendor-led training sessions, Womble Bond Dickinson took a different approach. Sam Dixon travelled to��each of the firm’s 7��staffed��UK offices��and personally led 35��introduction��and training sessions for��CoCounsel��Legal, a campaign that became affectionately known as “Cocoa with��CoCo.” In the middle of a British summer, he served hot chocolate, sat down with colleagues, and walked them through the platform himself.����

It’s��the��kind of visible, lead-by-example��behavior��that research shows��makes��a real difference.��According to the��2025 �������� Future of Professionals Report,��professionals who agree that leaders in their��organization��consistently lead by example are 1.7x more likely to be experiencing benefits from AI than those who disagree.��

The sessions were part of a broader, multimodal training program that included use-case specific meetings, pre-recorded leadership conversations reinforcing responsible use, and one-to-one engagement on the floor. Sam didn’t wait for questions to come to him. He walked the offices, asked people directly whether they had used CoCounsel Legal, and if they hadn’t, asked why not. That kind of visible, personal commitment created a ripple effect across the firm.��

The training program also served as a real-time risk management mechanism. Face-to-face conversations surfaced misconceptions early, allowing the team to refine their messaging on the spot. One recurring insight was around Deep Research in Westlaw Advantage, a key capability of CoCounsel Legal that delivers comprehensive legal research in 10 to 15 minutes, the kind of work that might otherwise occupy a lawyer for an entire day.��

Results That Speak for Themselves��

The impact on the quality and efficiency of legal work��at Womble Bond Dickinson��has been significant.��CoCounsel��Legal is now used regularly across practice areas, supporting work that spans��almost the��full breadth of what lawyers do, from legal research to document analysis to drafting.����

The platform delivers up to 80% efficiency gains on specific tasks, enables junior lawyers to contribute more meaningfully at an earlier career stage, and accelerates client turnaround across the firm.��

A Model for the Industry��

This initiative has not gone unnoticed. Womble Bond Dickinson and �������� were recently��recognized��with the��.��

As Sam��Dixon reflected on the decision to commit to early adoption of a product still in development: “It was the vision for the product and where I thought it would go and what I thought its advantages were over competitors. If I didn’t believe in��the���������� vision for the product, I couldn’t��have believed��it fit into our vision for the firm’s AI adoption ambitions.”��

“Womble Bond Dickinson exemplifies what it means to lead in the AI era. Sam Dixon and his team didn’t just deploy fiduciary-grade AI, they embedded it into the culture of the firm, making it a natural part of how every lawyer works. That kind of leadership is what separates firms that experiment with AI from those that truly use it to transform how they work,” said Raghu Ramanathan, President of Legal Professionals, ��������.��

The��trust��between Womble Bond Dickinson and ��������, and trust in the product, has been��earned through transparency, delivered through partnership, and validated through results. That is the real story here. Womble Bond Dickinson didn’t wait for AI to be perfect before committing. They helped make it better. And in doing so, they built something more valuable than a technology deployment: a firm-wide culture in which AI is not a novelty, but a natural part of how every lawyer works.��

Lawyers have always been accountable for their work. That was true before AI, and it is just as true now. A brief carries your name. An argument carries your judgment. A citation carries your reputation. None of that changes because an AI tool helped you produce it faster.��

That’s��why when firms talk about adopting AI for legal work, the first question��shouldn’t��be about speed or cost savings. It should be: can I��actually verify��what this produces? If you��can’t��trace an output back to its source, check whether that source is still good law, and inspect the reasoning that connected the two, you��don’t��have work product. You have a draft you��can’t��stand behind.��

That standard is not new.��What’s��new is how many lawyers are finding out the hard way that the AI tools they adopted��weren’t��built with it in mind.��

Courts across the United States have now sanctioned attorneys for��submitting��briefs with fabricated citations, false quotes, and mischaracterized precedent — all generated by AI and not verified by the attorneys. When those tools are built on content scraped from the web rather than authoritative legal sources��maintained��by practicing attorneys, the risk of error is structural. The AI has no way to know whether a case is still good law, whether a statute has been amended, or whether a citation��actually supports��the argument��it’s��being used to make. Verification becomes difficult not because the tools��don’t��show their work, but because the underlying sources��can’t��be trusted in the first place.��

At��Thomson��Reuters,��we��understand��that lawyers��don’t��just need to find the law — they need to be able to stand behind what they find.��We’ve��always built Westlaw��and Practical Law��with that in mind, and��it’s��the same principle we carried into CoCounsel Legal from the very beginning.��

Built for Verification at Every Stage��

When we designed CoCounsel Legal, we started from a simple premise: a lawyer should be able to verify everything the AI produces before putting their name on it. That meant building��tools that give attorneys everything they need to do that��verification��themselves,��at every stage of the workflow.��

As the research unfolds,��Deep Research��shows you its work in real time, step by step. You can follow the reasoning as it develops,��explore��findings as they��emerge, and��refine��the research with more specificity��by answering��additional��questions.����

As citations are built, two things work in parallel.��KeyCite��is woven into every stage of the research workflow, flagging cases overruled in part, warning of proposed amendments to statutes, and surfacing cases that are��frequently��cited together even when they��don’t��cite each other. Alongside it,��CoCounsel Legal’s patent-pending citation ledger��tracks every source the AI draws on throughout the research process and confirms that each source was��actually read��and reviewed — not just referenced.��Together, they give attorneys what they need to��answer the question��that��should��precede every citation��they rely on: does this hold up?��

Before anything goes out, two more layers of review engage.��The Verify function, launched in February 2026, surfaces every assertion made in the research report alongside the relevant source passages and pointers for��additional��research — giving attorneys everything they need to��verify��before anything goes out the door.��Litigation Document Analyzer��goes further��by��identifying��potential misrepresentations of law throughout an entire brief, your own or opposing counsel’s. Because in litigation, what a document implies about the law matters just as much as what it explicitly says.��

Every one of these capabilities exists for the same reason: because when you use AI to do legal work, you are still the one responsible for it.����

The Question Every Lawyer Should Be Asking��

Not all legal AI is built the same way.��Some tools are little more than general-purpose foundation models with a legal label applied — with little ability to confirm whether the underlying sources are current, authoritative, or accurately represented in the answer.��They can be fast. They can be impressive in a demo. But when a client’s matter is on the line and a judge is asking questions, impressive in a demo is not the standard that matters.��

At ��������,��fiduciary‑grade��AI is our standard for how AI should work in��high‑stakes professions.����It’s AI designed for professionals – built on our authoritative content; protected by rigorous privacy and security safeguards; shaped and validated by subject‑matter��experts; and designed to produce transparent outputs that can be verified.����

We’ve spent decades earning the trust of the legal profession. That history shaped how we built CoCounsel Legal. When your firm is evaluating which AI tools to adopt, the conversation about speed and efficiency matters. But it shouldn’t be the only conversation. Ask how the system handles accuracy. Ask what happens when you need to trace an output back to its source. Ask whether you can actually verify what it produces before your name goes on it. Those questions will tell you everything you need to know about whether a tool was built for legal work or just marketed to it.��

Lawyers have always been accountable for what they put their names on. The right AI gives you the tools to meet that accountability — and the confidence to know you have.

Additionally,��Rawia Ashraf, Head of Product,��CoCounsel��Transactional & GCOs,��was named��one of ILTA’s 2026 Influential Women in Legal Tech honorees, recognition that reflects her contributions at the intersection of AI and legal work.��Samantha Delaney, Senior Solution Consultant, AI Specialist��was also recognized, winning��the Young Professionals to Watch Award.��

Solution Provider of the Year��

The Solution Provider of the Year Award recognizes technology providers that have demonstrated exceptional partnership and transformational impact within the legal industry. �������� earned this recognition for CoCounsel Legal, which has redefined what fiduciary-grade AI looks like in legal practice.��

CoCounsel��Legal brings together legal research from Westlaw, practical guidance from Practical Law, and AI-powered document analysis and drafting, all within a single platform. One million professionals across 107 countries and territories have access to��CoCounsel, the foundational technology underpinning��CoCounsel��Legal.����

The impact CoCounsel Legal is having across the legal industry speaks for itself. Legal professionals report dramatic efficiency gains, with tasks that once took eight or nine hours now completed in one to two hours.��The quality of work has improved too, with lawyers gaining confidence in the thoroughness and accuracy of��its��outputs.��

There have been��big benefits, given CoCounsel Legal can complete full workflows.��

Firms are taking on more clients, expanding into new practice areas, and competing more effectively against larger, better-resourced competitors.��Across the board,��CoCounsel��Legal is not just saving time; it is fundamentally changing what legal teams are capable of.��

Trailblazer Award��

The Trailblazer Award, shared by �������� and��, recognized the two organizations’ early adoption initiative as a model for responsible, enterprise-scale AI deployment.��

Womble Bond Dickinson is a full-service��international��law firm, and in��2025, they��partnered with �������� to roll out��CoCounsel��Legal��to 650��timekeepers (including 457��qualified lawyers)��across all 7 of its��staffed��UK offices, ahead��of its launch to the UK market.��The initiative spanned a rigorous evaluation phase, a strategically constructed pilot group, and a rollout anchored by an executive-led training initiative.��

The firm notes that its lawyers are consistently choosing to use��CoCounsel��Legal every month, and that it is delivering real value across the organization.��

Rawia Ashraf, Head of Product,��CoCounsel��Transactional & GCOs,��named one of ILTA’s 2026 Influential Women in Legal Tech Honorees��

Rawia Ashraf was named one of ILTA’s 2026 Influential Women in Legal Tech honorees, recognition that reflects her broader contributions��to��legal technology.��Rawia��has��been instrumental in accelerating responsible AI adoption and driving��measurable outcomes across the legal industry, and her work on CoCounsel��Legal exemplifies the kind of product innovation the honor is designed to celebrate.��

Formerly an��antitrust attorney focusing on civil and criminal antitrust litigation��at Simpson Thacher & Bartlett,��Rawia��joined �������� in 2013.��She��was responsible for��leading the integration of��the��$650 million acquisition of��Casetext��into ��������. Additionally, she led the build and launch of��CoCounsel��Drafting as well as the development of the next generation of��CoCounsel��Legal, now in beta.��

Samantha Delaney, Senior Solution Consultant, AI Specialist wins��Young Professionals to Watch Award��

Samantha Delaney��won��the Young Professionals��to Watch��Award, which��recognizes��rising young professionals in the legal technology industry.��Her inclusion on this list��is��due��to her��demonstrated��steady growth, strong technical capability, and an insightful approach to supporting her colleagues and customers.��

Samantha is currently also��Adjunct Professor of AI and Technology��at��Osgoode��Hall Law School, and prior to joining ����������was a Senior Innovation Advisor at Norton Rose Fulbright, driving strategic adoption of emerging technologies across the��firm.��

These��awards��reflect Thomson��Reuters��continued commitment to building AI that meets the��highest standards of the legal profession and the people��leading��that work.��This work will continue with the launch of��the��next generation of��CoCounsel��Legal��in September.������

��

Agentic AI, Grounded in Expertise

Help us shape the next generation of CoCounsel Legal

Earlier in April we announced the next generation of CoCounsel Legal, now available in Beta. Built from the ground up, it��delivers on��the vision we set out from the start: an AI companion that works alongside lawyers through every task and every stage of a matter, grounded in the trusted sources of knowledge they rely on.

We’re��inviting customers to help shape what CoCounsel Legal becomes – an AI that works at the level of a senior associate, built with Anthropic��cutting-edge��technology, engineered for legal work with authority and verification at its core.

We are excited to put the next generation of CoCounsel Legal in the hands of more customers as the year progresses.��!

Additional Sources in Deep Research��

Deep Research reports��in Canada��now include��additional��sources that help further explore the legal question and provide logical pathways to continue the research process. A new section provides sources that, although not cited directly in the report, may provide further, helpful context��to��your question. This added material provides greater depth and perspective to support research, giving users more pathways to��validate��findings and expand their understanding of complex legal issues.

(click on image to expand)

Built for How You Work

Contract Policy Compliance Enhancement: Obligation Extraction

Contract Policy Compliance��now��enables��uploading regulations and documents for a quick compliance check. Customers can now skip the manual entry of their policies by uploading a file, accelerating the compliance review��process��and reducing the time spent on repetitive data entry tasks.��

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Westlaw Content Source Added to Knowledge Search ��

Now, users��have the ability��to��search��U.S.��Westlaw cases inside Knowledge Search and use them instantly in CoCounsel��Legal��workflows—no tool-switching��required. Users can search��U.S.��Westlaw cases alongside their DMS content, intranet��content, Practical Law, or other sources.��Upload cases��directly��into chat or��your��databases for further case analysis or to continue a workflow, making legal research more efficient and comprehensive.��

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Tabular Analysis Enhancements

Manually edit cell values and add your own custom columns directly within a table to apply your own judgment, add context, and shape the output so it’s ready for the next step in your workflow. Review flags help you prioritize your focus by automatically highlighting extracted answers in the table that require a closer look due to ambiguity or nuance in the source document. It helps you prioritize the responses that require your human expertise review while trusting your final results. Download a table with applied filters directly into Excel, preserving your work in CoCounsel Legal��without resetting those filters in a separate spreadsheet. Filter table results by data type to quickly narrow down and focus on the most critical information within the table. These tabular analysis enhancements offer the user more control over their tables, streamlining their workflow from analysis to action.��

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Companies Search����

A new search form on the Westlaw UK cases page searches for company-specific content across Cases,��Dockets, and��Pending Actions��that��helps��users��uncover company-related litigation more efficiently��and from��one place. This gives users a broader and more connected view of a company’s dispute landscape, improving research speed, confidence, and decision-making.��

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Concise Answer ��

Now, users��in Canada��have the��option for a concise answer��when using��Deep Research on Westlaw Advantage��that��will run in 2 minutes or less.��This provides users��with��more flexibility in how they use Deep Research��and can opt for a��concise answer��in��instances where a quick, straightforward answer is needed over an entire report.��

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Sharing and Saving Deep Research Reports (Canada)

Within a Deep Research report,��users can now copy a link to share the report with colleagues or save it to a folder in Westlaw for easy access later.��Quickly and seamlessly share��Deep Research to streamline��knowledge sharing with��your��teams.����

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Explore These New CoCounsel Legal Features Today

Sign in to CoCounsel Legal today to enhance the speed and effectiveness of your research, analysis, and document review workflows. Or explore training options at the����site.

To keep up to date on CoCounsel��Legal��new enhancements, sign up for the����today.��

Today, we’re announcing the next generation of CoCounsel Legal, now available in Beta. Built from the ground up, it delivers on the vision we set out from the start: an AI companion that works alongside lawyers through every task and every stage of a matter, grounded in the trusted sources of knowledge they rely on.

Built on the most advanced AI, and engineered for how legal work actually gets done

Built on Anthropic’s Claude Agent SDK, the next generation of CoCounsel Legal is a unified agentic platform that plans, selects tools, retrieves authoritative content, and adapts mid-workflow just as a senior associate would, not a first-year waiting for the next instruction. Critically, the lawyer remains in control—able to see the agent’s reasoning as it unfolds, step in to redirect its approach, challenge its assumptions, and probe whether alternative angles have been considered.

CoCounsel Legal doesn’t reason from the web – it’s built with Westlaw and Practical Law content and tools natively embedded. Different by design, the technology and the sources are built as one system, making defensibility part of the architecture rather than a feature. As a result, when CoCounsel Legal produces a deal term sheet, contract, or litigation strategy memo, every step of its reasoning is grounded in authoritative legal sources, guided by 35 million West Key Number classifications and 3.9 million Precision Research attributes, and fully transparent through verifiable Practical Law resources and Westlaw citations. Developed and evaluated by practicing-attorney editors working alongside top AI data scientists, the breakthrough isn’t simply faster task completion – it’s the ability to produce complex work product across the many decision points of a legal matter, moving beyond task execution to true legal reasoning.

Our leading evaluation framework encodes quality at each step. This means before any capability ships; we measure it. Licensed attorneys, including our Practical Law editors, define what the correct output looks like for each task type. Every new capability must demonstrate measurable improvement against that benchmark before it reaches production. The framework evaluates not just final outputs, but the full chain of reasoning that produced them, because an agent that arrives at the right answer through flawed reasoning cannot be trusted to do so consistently.

And we’ve gone further to protect the integrity of that reasoning, with patent-pending tools for citation integrity and output verification:

• Verification and grounding as system primitives. Authoritative retrieval, explicit source handling, and verifiable citation flows are product infrastructure -not post-processing or marketing language.
• Patent-pending link integrity.��Our patent pending citation ledger architecture tracks every source the agent brings into context and the specific passages it reads.

This is ; outputs grounded in authoritative content and customer context – making verification part of the system’s architecture rather than an afterthought. In a profession where a single missed citation can cost a client their case, defensibility isn’t a nice-to-have. It’s the whole point. In a profession where a single missed citation can cost a client their case, defensibility isn’t a nice-to-have. It’s the whole point.

What our customers are telling us

The feedback we’re hearing from customers reflects this.

Brooke Conkle, partner in Consumer Financial Services at Troutman Pepper Locke, asked CoCounsel Legal a broad question about recent TCPA developments across two circuits and the solution “immediately zeroed in on the precise ascertainability nuances” between them, the kind of careful parsing that typically requires significant time and research. Her conclusion: “The underlying legal analysis genuinely blew me away and made me rethink what is possible with AI in complex litigation work.”

That’s not the response of someone who found a faster tool. That’s the response of someone who found a different kind of tool.

Andrew Medeiros, managing director of Innovation at Troutman Pepper Locke, captures something I think is fundamental to why this matters: “Lawyers don’t want to just operate software, and that’s not what great AI should do.” What he’s seeing is that CoCounsel Legal keeps lawyers in the analytical mindset they were trained for, going back and forth, challenging answers and steering the work.

He added: “The next generation of CoCounsel Legal seems to be a total game changer as��we’ve��introduced it to litigation and transactional attorneys. It’s meeting them within their workflows, allowing them to ask plain language questions and then see the step-by-step approach that CoCounsel [Legal] takes to help them draft the document relying upon Westlaw Deep Research and the Practical Law guidance.”

The AI Knowledge Management Department at Morgan Lewis, shared, “We were really impressed with the enhancements to the CoCounsel Legal platform. In our evaluation, it demonstrated strong capabilities in supporting efficient document drafting and in addressing gaps in information, such as filing party details, with both speed and accuracy when prompted. The outputs were well-structured and immediately usable, and the overall workflow was intuitive and easy to navigate. Performance was consistently fast. We are really looking forward to what’s next!”

Why we’re launching this as a beta, and building in public

Just as important as what we’re building is how we’re introducing it to customers.

We are deliberately launching the next generation of CoCounsel Legal as a beta, with a clear commitment to building in public and in partnership with our customers. This beta includes leading law firms such as Troutman Pepper Locke, Morgan Lewis, Carlton Fields, and Caplin & Drysdale, as well as four large enterprise customers. As we move through successive beta waves ahead of general availability later this year, we’re putting the solution in the hands of real lawyers working on real matters – listening closely to where it earns confidence, where it doesn’t, and incorporating that feedback directly into how the product evolves.

We’re inviting customers to help shape what CoCounsel Legal becomes – an AI that works at the level of a senior associate, built with Anthropic with cutting edge technology, engineers for legal work with authority and verification at its core.

This reflects a core belief I hold: the solution itself should be the argument. The strongest validation won’t come from launch announcements or benchmarks alone, but from sustained use – when lawyers choose to rely on the product because it holds up under real professional accountability.

Today’s beta is just the beginning. I’m excited to put the next generation of CoCounsel Legal in the hands of more customers as the year progresses.

I encourage you to explore how it works.

After convening the first meeting of the Trust in AI Alliance, it is clear this mismatch is emerging as one of the biggest barriers to enterprise AI deployment.

As AI systems move from answering questions to taking action inside professional workflows, a fundamental mismatch is emerging. Execution shifts to the system. Responsibility still sits with the human.

In agentic systems, that model is being reconfigured, but there is still no clear answer to a critical question: how does a human maintain accountability as more of the work is executed by the system?����

That question was at the center of the inaugural convening of the Trust in AI Alliance, a group bringing together leaders across model development, infrastructure, and enterprise AI deployment, where participants from OpenAI, Google, Anthropic, AWS, and �������� discussed what trustworthy agentic systems require in practice.

A clear theme emerged: AI capability is accelerating faster than accountability.

Most systems today are not designed for that standard.

The Shift No One Is Talking About

In the first wave of AI, the defining question was whether a system could produce a correct answer. That is no longer enough.

As AI systems take on multi-step tasks across real workflows, the question is shifting from accuracy to accountability.

As Michael Gerstenhaber, Vice President of Product Management at Google, said during the discussion: “Delegating agency to a synthetic agent implies trust. The more you delegate, the more you need observability, tracing, and audit. It is not one feature. It is defense in depth.”

In traditional professional environments, accountability is clear. Humans determine relevance, review source material, verify outputs, and take responsibility for outcomes. In agentic systems, that model is evolving.

Retrieval is automated. Context is lost across steps. Outputs appear grounded in source material without preserving fidelity. Tools execute beyond the user’s visibility.

As Frank Schilder, Senior Principal Scientist at ��������, noted: “When we move to an agentic workflow, we automate steps that professionals used to perform manually and that introduces new risks: Context can be silently dropped. Source fidelity can become fragile. Maintaining clear accountability becomes more complex.”��

These are not edge cases. They are structural risks.��We are automating the work, but not accountability.

If You Can’t Inspect It, You Can’t Trust It

In regulated industries, trust has never meant blind confidence. It has always meant the ability to verify. That standard is now colliding with how many AI systems��operate.

Accuracy drives experimentation. Inspection determines adoption.

If a system cannot show its work, it cannot be trusted in high-stakes environments.

As Gayle McElvain, Head of TR Labs at ��������, put it: “Errors create liability. For many professionals, trust means ‘trust but verify.’ That means building AI systems where verification is built in.”

Across the discussion, several consistent priorities emerged around what trustworthy systems must provide:��

• • Step-by-step auditability��
  • Traceable reasoning and inspectable tool use��
  • Durable logs and process artifacts��
  • Clear, persistent provenance��

This is not a feature. It is��infrastructure.

Trust Breaks When Source Integrity Breaks

In knowledge-based professions, trust depends on the integrity of source material.

Agentic systems introduce new failure modes. They may paraphrase where precision is required. They may surface outdated information. They may blur the boundary between authoritative sources and generated reasoning.

These are not cosmetic issues. A single altered word in a statute can change its meaning. A misapplied version of a regulation can create real consequences.

As Zach Brock, Engineering Lead at OpenAI, described: “We are moving toward agents that share durable scratch spaces. Citations, version identifiers, and hashes of source material can travel through a workflow without being compressed away.”

That level of persistence is��not a technical��detail. It is what makes accountability possible.
Without it, professionals cannot trace how an answer was constructed or verify whether it reflects the correct source at the correct point in time. Without it, accountability breaks.

Accountability does not��emerge��automatically from more capable systems. It must be explicitly defined.

As Byron��Cook, Director of Automated Reasoning at AWS, said: “With AI, some of those socio-technical mechanisms go away. We��have to��define the dividing line between behaviors we��accept��and those we do not—and enforce that symbolically. Without that, accountability cannot be��maintained��as systems take on more of the work.”

This Is a Systems Problem

Much of today’s AI development is��optimized��for performance benchmarks. But in real-world environments, performance is only part of the equation.

As Scott��White, Head of Product, Enterprise at Anthropic, noted: “Benchmarks measure whether a model can do the task.��Enterprises are asking a bigger question: will the system around it hold up in the environments where the work��actually happens?��A trustworthy agent��requires��the model, the boundaries around it, and the record of what it did. Getting all three right is what turns AI from a powerful tool into a��system enterprises��can trust with important work.��That’s��what will drive the next wave of adoption.”

Trustworthy systems must be designed to operate safely under pressure, with clear boundaries and strong safeguards.

That requires:��

• • Clear separation between system instructions and external content��
  • Built-in safeguards against prompt injection and data leakage��
  • Continuous monitoring and testing��
  • Audit trails aligned with regulatory expectations��

Agentic AI is not just a model challenge. It is a governance challenge.

The Next Phase of AI

We are entering a new phase of AI adoption, one defined not by experimentation, but by deployment inside real workflows.

The industry is shifting from outputs to systems, from benchmarks to reliability, and from capability to accountability.

But this shift will not happen automatically. It requires new standards for auditability, clearer approaches to provenance, and systems designed to preserve truth and responsibility across every step of a workflow. These are solvable problems—but only if accountability is designed into the system from the start.

The organizations that solve this will define the next generation of AI.

In high-stakes domains, trust is not optional.

It is not a feature. It is the product.

The Trust in AI Alliance was announced in January to bring together leaders across the AI ecosystem to advance practical standards for accountability, transparency, and trust in AI systems. The group will continue to meet regularly, with��select��insights from those discussions shared publicly.��