That is the distinction we had in mind when building Westlaw Brief Builder, a new agentic capability in CoCounsel Legal designed specifically for litigation brief writing. As part of the enhanced CoCounsel Legal experience announced this week, Westlaw Brief Builder transforms research and drafting with AI agents that use Westlaw and Practical Law iteratively with the litigator to produce stronger briefs. AI agents conduct extensive research on the facts, arguments, and authority using Westlaw, Practical Law, and material from the case identified by the litigator. With each iteration, the litigator benefits from that research while remaining in control of the arguments, language, and overall structure of the brief.

Generating polished legal prose is becoming the easy part. AI can produce something that looks like a sophisticated brief in seconds. But the appearance of legal reasoning is not the same as legal reasoning, and in litigation, confusing the two can be dangerous. A brief has to do more than sound persuasive. Its arguments need to be grounded in the record, supported by authoritative law, tested against contrary authority, and strong enough for lawyers to put their names behind.

That is where the real opportunity for AI lies. Not in producing more text, but in helping lawyers do the substantive work required to build defensible arguments more efficiently, while preserving the strategy, judgment, and scrutiny that litigation demands.

The harder question is whether that brief is actually good. That goes far beyond checking whether the cited cases are real. If a lawyer has to reconstruct the research and reasoning behind an AI-generated draft before deciding whether to trust it, much of the promised efficiency disappears.

That is why we built Westlaw Brief Builder to work iteratively with the litigator rather than simply generate a finished document. Its AI agents conduct research at each stage using Westlaw, Practical Law, and matter materials identified by the litigator. The lawyer reviews the arguments, facts, and legal authority surfaced by the system, decides what belongs in the brief, and shapes the work as it develops. The result is not a brief handed to the lawyer for inspection at the end. It is a brief the lawyer has actively built with AI agents throughout the process.

Brief writing starts long before the first draft

Strong briefs are built through a series of interconnected decisions. Litigators need to understand the record, identify the issues that matter, determine which arguments are worth pursuing, research the applicable law, and continually reassess those choices as new facts or authority emerge.

Westlaw Brief Builder is designed around that reality. Its structured, multi-step workflow takes the litigator through intake, argument identification, supporting legal research, argument development, and drafting. At key points, the lawyer reviews what the system has surfaced and makes the strategic decisions about what comes next.

For example, Westlaw Brief Builder can propose potential arguments based on the matter and its initial research, but the lawyer decides which ones to pursue. From there, AI agents can investigate the relevant authority and supporting facts, while the lawyer can add information, refine the reasoning, and determine what ultimately belongs in the brief.

That iterative process becomes particularly important when research begins shaping the argument itself.

Research and drafting should work together

The quality of a legal argument depends on what sits behind it. That is why Westlaw Brief Builder integrates Westlaw Deep Research into the drafting workflow and draws on authoritative Westlaw and Practical Law content.

Once a lawyer determines which arguments to develop, the system can research relevant authority based on those arguments, the facts of the matter, and the applicable jurisdiction. The lawyer can review the authorities surfaced through that research, understand how they support an argument, and decide what should be incorporated into the brief.

Bringing those steps together means research can inform the argument as it develops rather than becoming a separate task before or after drafting. For litigators, that is a more natural reflection of how the work actually happens: research changes arguments, facts change research, and the two evolve together until the lawyer is prepared to stand behind the result.

The bar for AI-assisted drafting should be higher than speed

We are going to see continued innovation around AI-assisted legal drafting, and that is a positive development for the profession. Brief writing is demanding and time-intensive work, and there is enormous potential for technology to help lawyers complete it more efficiently.

But as the market evolves, we should be precise about what meaningful progress looks like. The goal is not autonomous brief generation or removing lawyers from legal reasoning. It is helping lawyers spend less time on unnecessary process while giving them better support for the substantive work that requires their expertise.

That principle is central to how we think about Fiduciary-Grade AI at ��������. In high-stakes professional work, the goal cannot simply be an impressive output. Professionals need authoritative information, transparency into the work supporting the result, and the ability to exercise their own judgment before standing behind it.

Westlaw Brief Builder is one part of the broader CoCounsel Legal experience we are building around that idea. The enhanced CoCounsel Legal brings together research, drafting, firm knowledge, and matter-centric workflows within a single AI-powered environment, helping professionals move from a legal question toward defensible work product without treating each stage of work as a disconnected interaction.

Westlaw Brief Builder takes that approach deeper into one of litigation’s most consequential workflows. It is designed to help lawyers develop arguments, find and evaluate relevant authority, create a stronger draft, and shape the work as it develops, while preserving the professional judgment that makes a brief more than simply AI-generated text.

AI can make drafting faster. The standard we should be aiming for is whether it helps lawyers produce better, more defensible work they are prepared to stand behind.

Now we are beginning to see what happens when that standard is applied. In one recent evaluation, experienced attorneys reviewed CoCounsel Legal’s performance across 50 complex CoCoBench tasks. Each task was estimated to require a lawyer an average of six hours to complete.

CoCounsel Legal completed each task in less than eight minutes.

More significantly, attorneys determined that CoCounsel Legal produced a stronger response than the original expert-written reference answer on nearly 40% of the tasks. The speed is remarkable. But speed is not the most important finding.

The more consequential result is that an agentic legal system, evaluated by experienced lawyers against realistic legal work, can do more than produce a plausible response. It can produce work that attorneys judge to be complete, accurate, well-supported, and usable in practice. That is a materially different standard from performing well on a public benchmark or delivering an impressive product demonstration.

And it changes how legal AI performance should be understood.

From benchmark performance to professional performance

Traditional AI evaluation often begins with a predefined answer and asks whether the system reproduced the expected elements.

That can be useful for testing a discrete capability. But legal work is rarely a matter of locating one answer or checking one box.

A lawyer may need to review an unfamiliar complaint, identify the relevant claims, research the governing law, assess potential defenses, and translate the analysis into a memo appropriate for a client. The value of the final product depends on how well all of those steps work together.

A response can identify the right doctrine but apply it incorrectly. It can reach a defensible conclusion while omitting a material issue. It can cite a real authority that does not actually support the proposition attached to it.

Those failures can disappear inside a benchmark score reliant solely on binary criteria. They are much harder to hide from an experienced attorney reviewing the output as actual work product.

That is the shift CoCoBench is designed to make: from measuring whether data is present to determining whether the work is professionally usable.

What a realistic legal AI test looks like

Consider one of the tasks included in CoCoBench. The scenario begins when a client receives an antitrust complaint naming it as a defendant. The client asks counsel to assess the claims and identify potential defenses.

The agent receives the complaint as its sole source document. It must identify the salient facts, research the applicable law for each claim and defense, evaluate which defenses may be viable, and prepare a memo written for the client.

This is the type of assignment litigators routinely face at the beginning of a matter. The available information may be incomplete. The issues may be ambiguous. The relevant law is not packaged neatly inside the source materials.

The task was authored by Jon Faria, a Senior Specialist Legal Editor at Practical Law who previously practiced as an antitrust litigation and investigations partner at Kirkland & Ellis.

That background matters.

Jon is not constructing a test that merely resembles legal work. He is reconstructing a problem he encountered in practice and applying the expectations he would have brought to an associate’s work product.

That is fundamentally different from generating a synthetic scenario and using another model’s answer as the standard of correctness.

The difference attorney judgment makes

CoCoBench combines automated evaluation with direct review by experienced attorneys.

The automated layer allows every run to be evaluated consistently and at scale. It identifies regressions, isolates specific failures, examines citation support, and helps engineering and data science teams understand where performance is improving.

Attorney review asks a more demanding question: would this work hold up in practice? Attorneys assess outputs across four dimensions:��

• Correctness: Are the factual and legal claims accurate, and are the citations used properly?��

• Completeness: Does the response address the full assignment, including the analysis that materially affects the conclusion?��

• Readability: Is the output organized and clear enough for a practitioner to use without reconstructing it?��

• Overall judgment: Taken as a whole, is the work fit for professional use?��

This review can reveal distinctions that a conventional benchmark may flatten. Two systems might both mention the relevant legal standard. One simply states it. The other explains its elements, applies them to the facts, addresses competing interpretations, and reaches a conclusion that a lawyer could defend.

A presence-based benchmark may reward both. A practicing attorney will not treat them as equivalent.

The hardest failures are often the ones that look right

One of the most important findings from our evaluation work is that legal AI failures are not always obvious.

A fabricated case is serious, but it is also relatively easy to recognize once someone attempts to verify it.

Misattribution can be more dangerous. A system may make a legally accurate statement and cite a real case, yet the cited passage does not actually support the claim. Everything appears credible: the authority exists, the proposition sounds plausible, and the citation is formatted correctly.

The failure lies in the connection between the claim and the authority. CoCoBench evaluates that relationship directly. It distinguishes among claims that are properly supported, claims that lack citations, claims based on incorrect reasoning, fabricated authorities, and propositions attributed to the wrong source.

It also differentiates between levels of misattribution. A passage that partially supports a reasonable inference is not the same as a claim whose real support appears only in an entirely different authority.

Those distinctions matter because they point to different technical problems and different levels of professional risk. A single accuracy score cannot show that.

Why the results matter

The initial results demonstrate what becomes possible when an advanced agentic system is paired with authoritative legal content, realistic evaluation, citation verification, and continuous attorney involvement. But they also expose a broader problem in the legal AI market.

Systems are often compared using measures that reward fluency, isolated task completion, or performance against synthetic reference answers. Those measures can create the appearance that several products perform at roughly the same level. When the evaluation moves closer to real legal work, the differences become clearer.

Can the system sustain accuracy across a six-hour assignment rather than a single turn prompt? Can it recognize which issues require deeper research? Can it connect each legal proposition to the authority that actually supports it? Can it produce a deliverable that an experienced lawyer would use as a credible starting point without redoing the core work? Those are much harder questions. They also require far more than access to a frontier model.

They require realistic legal tasks authored by practitioners. They require gold-standard responses grounded in substantive expertise. They require evaluation systems capable of testing both the final deliverable and the sources behind it. They require attorneys who can distinguish between an answer that sounds right and work that is right.

�������� can bring those elements together because legal expertise is not being added to the system at the end. It exists throughout the process.

It is embedded in Westlaw and Practical Law content authored, reviewed, and continuously maintained by attorney-editors. It guides the agents. It shapes the tasks used to evaluate the system. It informs the criteria against which outputs are judged. And it provides the continuous feedback used by our product, engineering, and data science teams to improve CoCounsel Legal.

That combination is difficult to build and even harder to sustain at scale.

A higher bar for legal AI

The question facing the legal industry is no longer whether AI can generate legal language.

It can. The question is whether an AI system can complete complex legal work accurately enough, thoroughly enough, and transparently enough for a professional to rely on it.

As agents take on longer workflows, involvement in evaluation becomes more important, not less. Errors introduced early can carry through research, analysis, drafting, and revision. A polished final answer can conceal weaknesses in the work that produced it. That is why the standard cannot be how intelligent the output sounds.

The standard must be whether the work can be examined, verified, explained, and defended.

The early CoCoBench results show that this standard is achievable. They also show why the way legal AI is evaluated will increasingly determine which systems are truly ready for professional work.

Because once legal AI is evaluated like legal work, the leaderboard changes.

Read the for a deeper look at CoCoBench’s attorney-authored tasks, automated evaluation framework, citation analysis, and attorney review methodology.��

After relying for years on an alliance-based audit solution, Isler CPA began evaluating new audit technology to determine what would best support its audit team going forward. As a small to mid-sized accounting firm, Isler CPA approached the process as more than a platform replacement, viewing it instead as an opportunity to invest in connected technology that could improve consistency, reduce manual effort, and better support its professionals across the audit lifecycle.

In evaluating providers, the firm wanted confidence the technology was mature, practical, and ready to support audit work in real-world engagements. �������� stood out for the strength of its audit solutions, the demonstrated investment in innovation, and the responsiveness of its team throughout the evaluation and implementation process.

Cody Savey, the lead partner of Isler CPA’s audit department, said: “We’re a small firm, and we rely on bigger providers to design our audit methodology. �������� impressed us with their advancement in technology and exceptional customer service.”

Among the solutions adopted, CoCounsel Audit has already delivered meaningful value by helping reduce time spent researching audit topics. The tool’s ability to provide sourced responses has been especially valuable in an audit environment where speed and verification matter.

CoCounsel has been a game-changer for the firm, saving hours of research time and enabling auditors to focus on high-value tasks. “I love CoCounsel,” said Savey. “It has saved me a ton of time. The amount of time CoCounsel is saving me in researching topics is hours at this point.”

For Isler CPA, the value of �������� audit solutions extends beyond research efficiency. The firm was also looking for a more connected audit process — one that could better link planning, identified risks, fieldwork, and conclusion. Guided Assurance and Engagement Manager help support that continuity, reducing the inefficiencies that can arise when key parts of the audit process become disconnected and helping teams stay aligned throughout the engagement.

“As a small firm, we need audit technology that connects planning, risk assessment, fieldwork, and conclusion,” Savey added. “That kind of automation helps the audit flow more effectively, supports consistency across the engagement, and gives us greater confidence that we are addressing the right risks throughout the process.”

For the firm, access to modern audit technology also supports a broader strategic goal. As competition and consolidation continue across the profession, Isler CPA sees advanced technology as an important part of maintaining its independence and preserving the culture it has built.

“We’re proud of the culture we’ve built at Isler,” Savey said. “Having access to modern technology helps us stay current, work more effectively, and continue growing without losing what makes our firm unique.”

“Firms of all sizes are looking for practical ways to make audit work more connected, efficient, and scalable,” said Corey Wells, General Manager of Audit at ��������. “Isler CPA’s adoption of CoCounsel Audit, Guided Assurance, and Engagement Manager reflects how firms are focused on innovation and using automation in a focused way — reducing time spent on manual tasks, improving workflow continuity, and enabling professionals to spend more time on judgment, analysis, and client service.”

She’s brought to life by comedic actor Beth Dover, and she’s about to be hard to miss. The CoCo arrives in a fully integrated campaign spanning TV, social, streaming radio, out-of-home and trade events, rolling out across our core professional markets. It’s also the most ambitious brand campaign we have mounted in more than a decade.

Why a character, and why now

Most technology gets explained. We wanted CoCounsel to be felt. Professional audiences have heard every AI promise by now, and most of it sounds the same. A feature list doesn’t cut through that. A personality does. The CoCo is how people meet CoCounsel — not through a spec sheet, but through presence, authority and the kind of confidence that only comes from actually knowing the answer. She’s memorable on purpose, because the point we’re making deserves to be remembered.

There has been a lot of talk about what AI might do someday. The CoCo is here to talk about what CoCounsel already does, for the professionals who can’t afford to be wrong.

“Professionals in law, tax and compliance don’t have the luxury of being wrong. That’s why CoCounsel exists. It combines the trusted content, technology and expertise �������� has spent more than 175 years building and puts it to work in moments that matter most. The CoCo gives that story a voice. She’s confident, authoritative and impossible to ignore—just like the professionals we serve. This campaign is about more than introducing a character. It’s a statement about what �������� is today: a technology company powered by trusted intelligence, helping professionals navigate a world that grows more complex every day,” said Amy Messano, Chief Communications and Marketing Officer at ��������.

Through �������� expanding partner ecosystem of legal technology companies and law firm partners, CoCounsel Legal is connected to the tools legal professionals already rely on, from transaction management and case intelligence platforms to enterprise search and specialized practice workflows. This works in both directions: bringing more capabilities into CoCounsel Legal, and embedding CoCounsel Legal capabilities into other solutions, so firms can move faster, work smarter, and deliver better results with connected workflows.��

The outcome is a legal practice that runs the way the practice of law demands: greater speed, sharper insight, and the confidence to deliver.��

A Partner Ecosystem Built on��Shared High��Standards��

Law firms face an overwhelming market of solutions with few reliable ways to evaluate what is trustworthy, what is secure, and what actually belongs in a legal tech stack. �������� has done that work. Every partner goes through a rigorous vetting process that evaluates their technology, security controls, commitment to data protection, and alignment with the standards legal professionals rely on.��

The outcome is a shared partner ecosystem where legal professionals have seamless access to the intelligence, tools, and connected workflows they need, without the friction of switching between disconnected systems, and without compromising the standards their profession demands.��

“The partnerships��we’re��building around��CoCounsel��Legal reflect how the practice of law��actually works: interconnected,��time‑sensitive, and��outcome‑driven. By integrating intelligence directly into workflows, we help firms move faster and��operate��with greater precision.”

-Steve Assie, General Manager, Global & Large Law Firms, Thomson Reuters

The��Partner Ecosystem��in Action��

��Document Review Inside the Deal Workflow����

Legal teams rely on transaction management platforms to coordinate the work that moves deals forward: collaboration, transparency, checklists, document organization and version control, deal status monitoring, signature page creation and collection, and generating final closing sets. When document review and analysis happen outside that workflow, teams must move files into separate tools and then bring the results back into the platform. This��adds��friction, delays, and the potential for lost context at the moments when speed and accuracy matter most, particularly in time-sensitive transactions.

DealCloser is a transaction management platform used by law firms and in-house legal teams across a broad range of transaction types, including mergers and acquisitions, banking and finance, real estate, venture capital, private equity, restructuring, and other complex transactions. Through its partnership with ��������, CoCounsel Legal’s document review capabilities are now embedded directly within DealCloser, bringing AI-powered review to the full transaction lifecycle. Teams can analyze contracts, amendments, exhibits, and diligence materials without leaving the platform where the deal is being executed — no manual uploads, no version uncertainty, and no need to reconcile findings across tools.��

: Bringing Firm Knowledge into��CoCounsel��Legal����

Law firms store years of work product across document management systems, intranets, email archives, and other repositories. Their briefs, memos, negotiated agreements, and templates��contain��valuable institutional knowledge that differentiates them. Yet that information can be difficult to surface and apply quickly, particularly when content is spread across multiple systems.����

DeepJudge��helps firms realize the full value of that collective knowledge through enterprise search, AI agents and workflows, and governed access controls. Lawyers can rapidly find, analyze, and apply the most relevant information across millions of documents in��iManage, NetDocuments, SharePoint, HighQ, network drives, and many other sources.����

The partnership between DeepJudge and �������� connects this institutional intelligence to CoCounsel Legal. Whether attorneys are working in Microsoft Word, CoCounsel, Westlaw, or Practical Law, they can use DeepJudge to rapidly retrieve and synthesize key language, facts, and precedent from internal documents and work product, making firm knowledge available in CoCounsel Legal for research, analysis, and drafting workflows. Firm precedents and external legal authority are accessible and actionable in the same workflow, with existing permissions and ethical walls carrying through.��

: Practice Management and Legal AI in One Ecosystem����

Small and mid-sized law firms often have too many disconnected tools. When practice management, document storage, legal research, drafting, billing, and document analysis live in separate systems, lawyers spend time on administrative friction instead of legal work, and lean teams with tight margins feel that cost acutely.����

Smokeball is a cloud-based practice management platform built for small to mid-sized firms, covering intake, matter management, automatic time capture, billing, and client communications. The combination of��CoCounsel��Legal and Smokeball unites deep legal content and advanced AI with comprehensive practice management, powered by technology that understands both the substance of legal work and the mechanics of running a firm.����

Smokeball matter documents can now be brought directly into��CoCounsel��Legal in bulk,��eliminating��manual uploads and the��version��confusion that comes with moving files between disconnected systems.����

The result is a more continuous workflow from matter management to substantive legal work. Attorneys can use CoCounsel Legal to rapidly analyze, draft, and research with their actual matter documents at hand, grounded in authoritative Westlaw and Practical Law content. This is just step one in a joint roadmap creating a unified ecosystem for small to mid-sized firms.

A Law Firm as Co-Developer

The partnership with Sterne, Kessler, Goldstein & Fox, one of the leading intellectual property law firms in the United States, takes a different form. Rather than a product integration, this is a co-development relationship in which the firm’s practitioners worked directly alongside Thomson��Reuters��engineers and editorial teams to build a specialized workflow inside��CoCounsel��Legal.��

The focus is Section��101��patent eligibility, a question central to most utility patent disputes, deeply precedent-dependent, and historically requiring significant associate time with no guarantee the research was complete.��

The resulting Patent Claim Eligibility Analyzer inverts the traditional model of legal technology development: instead of practitioners receiving a finished product built by technologists, Sterne Kessler co-developed it from the start, translating the firm’s own Section 101 methodologies into a scalable workflow now available to patent practitioners across��CoCounsel��Legal.��

: Connecting Case Intelligence to Legal��Strategy����

Personal injury cases are won or lost on facts, and facts live in unstructured records that take too long to organize and are too easy to get wrong. Medical records, treatment timelines, damages calculations, liens, deposition summaries: plaintiff firms are managing all of it, under pressure, against better-resourced opponents.��

Supio Agent changes the equation at every level. At the case level, it ingests every file, every system, every data source the firm runs on and executes the work: medical chronologies, damages summaries, causation analysis, and case-specific drafts grounded in verified facts. At the portfolio level, it surfaces what’s urgent, what’s behind, and what needs to move. At the firm level, it gives leadership real-time visibility into case quality, intake patterns, and institutional knowledge that previously lived only in attorneys’ heads.��

Deep Research with Westlaw Advantage is available natively inside��Supio��Agent, invoked when legal research is needed, running in parallel, and surfacing findings directly in the workflow.��

The result:��Supio��builds the record, compounds the knowledge, and works with Westlaw to verify the law, delivering defensible work product at a scale no case-level tool can touch.��

A Growing Partner Ecosystem��

Thanks to �������� partner Anita, German legal research content is now part of the CoCounsel Legal experience, providing authoritative guidance for Germany-based and international teams. A recent document connector integration with practice management solution Litify creates a fast track from matter files to substantive legal work product. ��

Document storage integrations launched early this year with Box and Dropbox extend that reach further, making it easier for firms to work with their documents wherever they live. And with Outlook search now enabled within CoCounsel Legal, users can simultaneously surface and apply relevant information from their email, Westlaw, Practical Law, and other connected sources, all without leaving the platform.��

The��practice��of law looks different depending on where you sit, from solo and small firm practitioners managing tight margins and lean teams, to large global firms and corporations navigating complex,��high-stakes��matters. The��partner��ecosystem is built to serve that full spectrum, meeting legal professionals where they work with the connected intelligence and seamless��workflows��their practice demands.��

As the��legal��profession’s needs evolve, so��will��the��partner��ecosystem.��For lawyers, that means more capability, more connectivity, and more of the intelligence they need,��wherever their work happens.��

Learn more about CoCounsel Legal

Earlier this month, I watched that shift play out on two stages. First, at Snowflake Summit, I talked about the data foundation powering enterprise AI. Then, at Fortune Brainstorm Tech, I sat with tech-forward leaders from Salesforce, Amgen, Optum, SentinelOne, TrustGuard, and May Mobility, debating where these systems break when the stakes are real.��

Different rooms, different framings. Same conversation.��

The AI market is starting to agree trust is what separates AI that demos well from AI that survives contact with production. Traceable, governed, explainable: the words are everywhere. Trust has become the thing we all nod along to.

But we keep talking about it as a feature. Something you bolt on once the model works. A checkpoint before launch.

And there was one thing few people were willing to say out loud:

Trust is not a feature. It is a bill. And much of the industry is about to discover it never paid for it.

The tax nobody put on the slide

The part that often goes unsaid in the keynotes is that the governed data foundation that makes an AI system defensible takes years to build, costs real money, and produces almost nothing you can put on stage while you are building it. There is no demo for “we governed every layer underneath, so the same question never returns two different answers.” Nobody throws a launch event for a semantic layer.

So many companies did not build one. The last few years rewarded the opposite instinct, the one the consumer internet was built on: ship it, watch what breaks, patch it in the next release. Fail fast.��

That reflex produced extraordinary products. It is also precisely the wrong reflex to carry into law, tax, audit, and compliance, where the first failure is not a lesson. It is a brief filed with a citation that does not exist, in front of a judge.

At Snowflake Summit, my colleague Laura Safdie captured it well: you cannot bring AI to a profession you do not understand or transform a workflow you have never done.

For a consumer chatbot, a model that is fluent without being informed may be a tolerable trade. For the lawyer defending an antitrust case, the tax professional signing a multinational filing, or the compliance officer clearing a transaction, “mostly right” is not a trade-off. It is malpractice. And “the AI did it” has never worked as a defense in a courtroom.

The companies sprinting into agentic AI on top of fragmented data and governance bolted on at the end are not necessarily moving faster than everyone else. They are running up a debt that comes due the first time someone asks them to explain an output and they cannot.

The quiet work is about to pay off

In Aspen, in a room full of hands-on technology leaders, one idea kept coming through clearly: the quiet work is about to pay off.

The model is almost never the thing that breaks first in production. Ownership breaks first. Auditability breaks first. When nobody has defined who owns the output or what happens when it is wrong, the model turns out to be the easy part.

Everyone has access to good models now. The layer underneath is the hard part, and it cannot be acquired in a quarter.

At ��������, we made that investment before it was fashionable. The work may be unglamorous, but the results are exactly what enterprise AI now requires: a governed semantic model that turned five conflicting answers from five teams into a single source of truth; complex financial analysis that used to take weeks, now completed in seconds; data refresh cycles reduced from roughly a day to near real time; and AI agents that can explore data, surface patterns, and generate analysis because the foundation underneath them is trusted enough to reason on.

Just as important, every AI capability is assessed across regulatory, privacy, security, ethics, and performance risk before it ships. ISO 42001 certification is treated as a continuous discipline, not a press release. And our trusted data estate across tens of thousands of governed tables is why we could show up as a customer with proof, not just intent.

That is the quiet work. And it is the reason we can put AI into the highest-stakes professional work there is and stand behind the answer because it is traceable and auditable.

The next phase rewards a different kind of company

One line from a fellow panelist, Elena Kvochko of TrustGuard, stuck with me: you do not let AI grade its own work. As agents take on more, the volume of output to verify grows faster than any human team can check by hand, which means oversight must be engineered into the system, not promised in a policy after the fact.

That is the real shift underway: from AI that helps with a task to AI that completes an entire workflow inside an environment it can be trusted to operate in. Give it an objective, and it can plan, research, validate, and coordinate across the whole thing, not just answer a question.

The agent who can navigate proprietary knowledge, permissions, and genuine accountability is worth far more than the that writes a confident paragraph.

Enterprises do not run on models. They run on trusted systems. And the layer where work actually gets completed is where trust and accountability live.

So here is the prediction the demos are hiding: the next two years will not be won by whoever has the most impressive model. They will be won by whoever quietly paid the bill: traceability, security, governance, and explainability.

We paid that bill early, on purpose, because the highest-stakes professional work demands it. That is not where the work ends. It is where trusted AI begins.

Now, we’ve got the answer – by the numbers. �������� recently commissioned Forrester Consulting to conduct a study to examine the potential return on investment (ROI)law firms can realize by deploying CoCounsel Legal, our AI solution, which brings together legal research, essential workflow automation, intelligent document search and AI-powered legal assistance in a single platform.

Real-World Scenarios, Concrete Results

To produce the analysis, researchers conducted detailed interviews with senior law firm decision-makers who’ve been using CoCounsel Legal for the past several months to understand exactly how they are working with AI inside their firms, what the real-world impacts have been on their business, and the bottom-line costs and benefits linked to their investments in AI. The results of those interviews were then combined to create a single composite organization – a multi-practice law firm with 500 attorneys – and financial impacts were extrapolated over a three-year period.

The research puts some hard numbers behind a value proposition that, until now, has been hard to quantify. It answers the critical question: How exactly are AI-driven efficiency gains creating new growth opportunities for law firms?

Following are some of the key findings for the composite organization:

• Return on investment: 400%
  The headline finding of the analysis is that the total ROI of the composite law firm investment in CoCounsel was 400%, meaning the return after three years, minus costs involved with acquiring the technology, onboarding, and training staff, is five times greater than the initial investment. In this example, that translates to a total of $18.3 million in total value over three years.
• Incremental revenue from increased matter capacity: $20.3 million
  Contrary to much of the recent rhetoric around professional AI adoption, the lion’s share of that value does not come from reduced headcount or productivity gains. While those are factors, the real value CoCounsel Legal delivers is the ability to take on a greater number of matters concurrently by reducing the time required for research, document review, and matter ramp-up. As a result, the composite organization increased attorney matter capacity by 25% without adding headcount, allowing the firm to accept additional work from existing clients and pursue new matters.
• Productivity gains within core legal workflows: $1.7M
  Productivity, of course, is improved with AI, but the interesting finding in the Forrester analysis is that those productivity gains are concentrated in specific law firm workflows. Based on the analysis, attorneys spend less time on repetitive, low-value tasks such as document review, legal research, and drafting, which means CoCounsel is reducing nonbillable time and lowering write-downs on existing matters.

In addition to the quantitative benefits, the research also found several qualitative examples where incorporating CoCounsel into day-to-day tasks helped to improve both the quality of work and quality of life for the firms’ attorneys, such as the following:

• Improved quality and consistency of legal work product
  Attorneys reported that AI-generated summaries, research, and drafts are more reliable and thorough than traditional manual approaches, boosting confidence in the work product, cutting down on partner oversight, and reducing the chance that critical facts or arguments slip through the cracks.
• Greater focus on high-value legal judgment and client strategy
  By reducing time spent searching for information and compiling relevant case law, CoCounsel Legal allows attorneys to devote more effort to strategic analysis, advocacy, and client advisory work, enhancing perceived client value.
• Improved attorney experience and reduced burnout
  The fact that CoCounsel Legal allows attorneys to complete lower-value, repetitive tasks more quickly, while freeing up time to focus on more strategic work, improves day-to-day attorney experience and work-life balance, particularly for junior attorneys handling document-heavy matters.

Reclaiming the Work That Matters in Law

While the intent of the analysis was to deliver a definitive, by-the-numbers calculation of what kind of financial return law firms can expect from their investments in AI, the results revealed much more detail about the role AI is already playing in law firms, today. Importantly, it shines a spotlight on the fact that AI is having an accretive effect on the firms that have embraced it. Put simply, it is helping firms do more work better, ultimately helping them create more capacity and new opportunities for growth.

That’s a fundamental shift from the mainstream narrative on AI, which has often been cast as a productivity and cost-reduction tool. That’s really only a small part of the story. When the right AI tools are deployed effectively, they are removing points of friction and helping attorneys reclaim the work that matters. Importantly, they are also creating significant new growth channels along the way.

to read the full analysis.

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.��