Thomson began as an internal project, built to solve a problem we had ourselves.听

抖阴成年 holds 175 years of authoritative data across legal, news, tax and accounting: Westlaw, Practical Law, Checkpoint and Reuters. We also employ thousands of subject-matter experts whose working lives are spent deciding what is correct. For three years we watched general-purpose models improve rapidly while both assets sat outside the training loop. We also faced the questions our customers were asking us: what dependency are we accepting on someone else鈥檚 architecture and pricing, and what do we do when the capability we need most is on nobody鈥檚 roadmap?听

Our answer to that was the Thomson LLM, and it worked well enough that we now want to share it with the rest of the world wrestling with these same questions.听

Where the argument came from听

The team that built Thomson did not arrive at 抖阴成年 with just a view about legal AI, but with a view about reliability.听

Safe Sign Technologies was founded in 2022 by lawyers and researchers whose background was in model safety, robustness and reliability, several coming out of applied AI in medicine and law, from Harvard and Cambridge. Medicine and law share a property most application domains do not: being nearly right is still wrong, and the cost of a confident error is borne by someone other than the person who made it. Both have long and demanding traditions of rigorous verification as a result, and those shaped how we approached the problem.听

The argument we made from that starting point was, at the time and until recently, unfashionable. In 2022 and 2023 the field was watching capability curves. The consensus was that frontier models would absorb professional work as a by-product of getting cleverer and that any attempt to keep pace with the 鈥渟caling laws鈥� of AI was futile. On that view the sensible move for a small company was to build a layer on top and wait.听

We believed the binding constraint was different. Capability, we argued, would become abundant; it was the object of enormous and well-funded competition, and there was no reason to expect it to stay scarce. What would remain scarce was trust and reliability: being right in a way that can be checked, in a domain where someone whose career depends on it. Trust is not a by-product of capability. It is a separate research problem requiring different evidence, and nobody was going to solve it for law as a side effect of solving it for everything.听

Very few people agreed. Making that case repeatedly, to investors and to ourselves, through pivots and long stretches with nothing to point at, was most of the job.听

抖阴成年 acquired Safe Sign in August 2024, in the company鈥檚 first pre-revenue acquisition. The team became 抖阴成年鈥� Foundational Research team, and crucially, the research posture that pre-dated the acquisition survived the transition. We continued to treat the work as a research problem rather than solely a product problem, which is why so much of the effort below went into measurement.听

Starting from open weights听

I said previously that our starting hypothesis was that capability would be abundant. The rate of progress of open-source AI has continued to prove this thesis over the last several years. Thomson benefits from this directly, with a leading open-weight foundation model as its starting point. We鈥檝e changed the root model of Thomson many times over the last several years, and will continue to do so as the frontier of open-weight models evolves. 听This is a tide that Thomson moves with, not one that washes it away. 听听

At the time of writing, the base model for Thomson is the Imperial College London Snowdon model. This model was developed by the FAIR Lab at Imperial, which 抖阴成年 and Imperial founded jointly, as an academic by-product of the acquisition of Safe Sign. 听

That choice is usually framed as a trade-off, and there is something to it: open-weight models can lag the closed frontier, and published analyses generally put that lag at a few months [1]. The conventional choice is, therefore, between capability and control.听

We did not think this was an acceptable dilemma for professional work. The frontier is measured on general capability, but our customers are judged on something narrower: whether a citation holds up, whether an answer is complete, whether the reasoning survives a partner鈥檚 review. There is no rule that a model strong on the second must concede the first. As we reported at launch, Thomson performs competitively with the strongest frontier models on the market, including Claude Opus 4.8, and ahead of GPT-5.5, Claude Sonnet 5 and Gemini 3.1 Pro. It also leads them on the measure this post is concerned with: whether the citations in a research report survive being checked.听

Turning the archive into training data听

抖阴成年 content is the deepest asset in this field and the reason a model of this kind was possible at all. It is also, as any archive of this scale would be, material that has to be prepared before a model can learn from it well.听

Content has to be found, which in an organisation of this breadth and history is a substantial exercise in itself. It must be assessed for rights, selected for measurable impact on model performance rather than relevance in the abstract cleaned, structured, deduplicated, and finally deployed into a data mixture, which is where the most consequential decisions are made.听

To date we have used less than ten per cent of 抖阴成年 content in continued pre-training. Westlaw, Practical Law, Checkpoint and Reuters News have been drawn on selectively. The areas where the model is not yet best in class are not ceilings we have reached, but areas where the relevant content has not yet been brought to bear.听

The specialisation problem听

Data mixture matters so much because specialising a model can damage it. Fine-tuning on domain-specific data can cause catastrophic forgetting: the model overwrites capabilities acquired during pre-training and its general performance degrades [2]. The effect is well documented, and mitigations exist, including replay of general data and regularisation of parameter updates. None fully solve it.听

One finding matters more than the others for our purposes. Kotha, Springer and Raghunathan鈥檚 听2024 study [3] examining what degrades during domain fine-tuning identified instruction-following as the principal contributor to forgetting: what erodes first is not the model鈥檚 knowledge of the world but its ability to do as it is told. For professional work that is close to a worst case, since real legal work is never only legal reasoning but legal reasoning while adhering to a format, a jurisdiction, a house style, an exclusion, a client鈥檚 standing preference. Output that requires reworking has not saved anyone any time.听

We therefore treated general capability retention as a first-class training objective rather than an acceptable loss. Instruction following is among the capabilities specialisation is most likely to erode, and it is one of the categories in our published benchmark results where Thomson stands up best against the frontier models, scoring 0.914 ahead of Claude Opus 4.8, Gemini 3.1 Pro and GPT-5.5. That is the clearest evidence we have that the model was specialised without being narrowed.听

Where the expertise actually comes from听

Many organisations claim their AI systems are 鈥渢rained with expert input鈥�. The phrase carries little meaning without an answer to the real question: how does a lawyer鈥檚 judgement become a training signal? Experts do not produce training data, but a standard. We have had to work to ensure the collective edge in expertise held by 抖阴成年 domain experts is realised in the quality of our training data. This is how we did it.听

Rubrics at maximum complexity. Partner-level practitioners worked full-time for months constructing evaluation rubrics for the hardest legal research tasks we could specify: the kind of multi-jurisdictional question where a good answer has fifteen necessary components and a plausible-looking one has nine. Each rubric enumerates what a correct response must contain. This is slow, expensive, and cannot be crowdsourced or synthesised.听

Commercial judgement, not only legal judgement. We required lawyers fresh out of commercial practice to ground the training data in what clients actually care about, which is frequently not what a textbook would emphasise. Take an indemnity. In most commercial agreements, it is heavily negotiated and often enforced, and treating it as significant is correct. But in an NDA it is usually neither, and almost never the crux. A model trained only on doctrine cannot tell those situations apart, and one that flags an NDA indemnity as urgently as the confidentiality carve-outs has identified a legal issue and wasted a lawyer鈥檚 attention. Teaching that distinction requires people who have sat on the other side of the negotiation.听

Preference data at scale. Thousands of hours of qualified lawyer time selecting between model outputs against complex criteria. Not 鈥渨hich is better鈥� but which better serves a client with a particular posture, in a particular jurisdiction, at a particular stage of a matter.听

抖阴成年 employs around 1,500 attorney-editors whose day job is producing the analytical content lawyers rely on. The obvious move is to train on their published output. The harder and more valuable move is to capture what happens between the first draft and the published article: the judgement calls, the discarded framings, the reasons a proposition was narrowed, the authority considered and rejected. That intermediate work is where so much expertise lives, and it is almost never written down.听

This problem generalises directly to our customers. A firm鈥檚 advantage is not simply its precedent bank: precedents circulate, deals become public, documents get shared. The advantage is what years of doing the work have built in the minds of its lawyers, who eventually retire or move. Capturing the reasoning rather than the artefact is the same problem, and we have worked on it at scale on our own corpus first.听

Internal deployment as a research instrument. Thomson has been deployed widely inside 抖阴成年, with thousands of domain experts using it on their hardest problems, which gives us failure modes reported by people qualified to diagnose them. Our teams are not incentivised to use Thomson for Thomson鈥檚 sake; if they use it, it is because they have decided it can do something others can鈥檛.听

The consistency problem听

Expertise does not straightforwardly produce consistency. In some respects it produces the opposite: the more experienced the practitioner, the more nuanced their judgement, which is exactly what you want in a partner and exactly what creates noise in a training set. Two excellent lawyers can disagree on a scoring decision not because either is wrong but because each applies a refined intuition the other does not share.听

The literature bears this out. On the LEXam legal reasoning benchmark [4], three legal experts independently scoring the same answers on a ten-point scale reached a quadratic weighted kappa of 0.49, with a mean absolute deviation approaching two points. Work on implicit legal citations [5] reports similar or worse agreement. More troubling, Rehag鈥檚 survey of legal machine learning datasets found they systematically removed all traces of disagreement rather than treating conflicting expert annotations as informative [6].听

Take expert output at face value and train on it, and you teach the model an averaged version of several incompatible standards: vaguely acceptable to everyone rather than correct according to anyone.听

A large share of our effort therefore went into data quality: calibrating annotators against worked examples, measuring agreement continuously and treating drops as signals about the task specification rather than the annotator, and structuring rubrics tightly enough that disagreement surfaces as genuine ambiguity rather than noise. Where it persists, the question is usually contested, which is itself something the model should learn.听

Safety, values and red-teaming听

A dedicated team of lawyers worked on bias, political neutrality and toxic behaviour, with extensive human and automated red-teaming. We treat these as training objectives rather than output filters: a filter catches a bad answer on the way out, an objective changes what the model is disposed to produce.听

Political neutrality deserves particular mention given that Reuters sits inside this company. Realignment towards factuality and pluralism was an explicit part of the training programme rather than a compliance exercise appended to it, and it is measured rather than asserted: Thomson performs strongly against the frontier models on our internal neutrality evaluation, with detail to follow in the technical report. For a company that publishes news as well as legal analysis, that is not peripheral.听

Beyond legal data听

Not all of the training data is legal. We drew on domains rich in explicit chain-of-thought reasoning, where the reasoning must be set out rather than left implicit, on the view that a model reasoning well in structured non-legal settings reasons better in legal ones. Checkpoint and Reuters give depth in tax, accounting and world events, because legal work is rarely purely legal.听

Rigour and factuality听

Our own lawyers publish at leading AI conferences [7] the people building the evaluation apparatus treat it as research rather than quality assurance, which is what makes it rigorous enough to train against.听

We think that rigour produces the result we care most about. In our published deep research evaluation, Thomson working over Westlaw and Practical Law scored 0.83 on factuality against 0.65 and 0.68 for leading frontier models given unrestricted access to the open web. Completeness was close between all three. Factuality was not.听

Completeness is a capability measure: it asks whether the system covered the ground, and on it the three were nearly level, because frontier models with the open web and enough time will generally find the material. Factuality is a reliability measure: it asks whether the system can be checked and survive it, and on that they were not close at all.听

The metric is not a measure of whether an answer sounds authoritative or whether the conclusions are broadly sound. Every claim is extracted and matched against the source cited for it, and the score is the proportion of assertions whose own citations hold up when checked.听

That is the failure that has kept general-purpose AI in the assistant鈥檚 chair. A system reliably right about its own sources is a different category of instrument from one merely fluent about them. It is the difference between something an associate uses and something a partner signs.听

We call this Fiduciary-Grade AI: a standard for AI used where accuracy, accountability and trust are not optional, for professionals working under duties of care and regulatory oversight. Thomson demonstrates that it can be pursued at the model layer rather than bolted on above it.听

Capability and sovereignty are not mutually exclusive听

The lesson is not just about law. Any organisation holding a deep proprietary corpus and real domain expertise has been told it must choose: either rent frontier capability and accept the dependency or own an open model and accept some distance from the frontier. The choice is false, provided you are willing to do the unglamorous work of preparing the data, converting expert judgement into consistent signal, and building the evaluations before you try to move the numbers. The reward is a model you own rather than rent, pointed at the problems you choose, improving on your schedule rather than somebody else鈥檚.听

The compute is not the binding constraint. The corpus and the people who know what correct looks like within it are, and those have never been concentrated in the frontier laboratories. They sit inside institutions that spent a century accumulating them without thinking of themselves as AI companies.听

We are one of those institutions. Thomson is what happened when a research team that had spent three years arguing trust and reliability were the scarce input finally got access to the data and the experts to prove it.听

Thomson enters production this month powering CoCounsel skills including high-volume structured document review, with integration across the legal and tax portfolio to follow. A full technical report is forthcoming. Thomson was built in collaboration with DatologyAI, Lambda, Together AI, Imperial College London and the 抖阴成年鈥揑mperial Frontier AI Research Lab.听

Sources for external claims听

[1] Epoch AI, open-weight capability lag analyses (October 2025; May 2026); Stanford AI Index 2026.听

[2] Luo et al., “An Empirical Study of Catastrophic Forgetting in Large Language Models” (2023); Song et al., arXiv:2501.13669.听

[3] Kotha, Springer and Raghunathan, arXiv:2406.12227.听

[4] LEXam, arXiv:2505.12864.听

[5] “Where Experts Disagree, Models Fail”, arXiv:2603.22973 (2026).听

[6] Rehaag, “I beg to differ”, Artificial Intelligence and Law (Springer, 2023).听

[7] Yejin Bang, Kirsty Fielding, Brandan Oliver, Brian Birke, Nabeel Seedat & Andrew M. Bean, ContractScrub: A Benchmark for Final Review of Legal Contracts (抖阴成年 Foundational Research, 2026) (in Proceedings of the AI for Law Workshop at the International Conference on Machine Learning (ICML 2026), available at ); and Samuel J. Vincent, Daniel Calloway, Fangyi Yu, Andrew M. Bean & Nabeel Seedat, InsufficiencyBench: Evaluating LLM Legal Advice on Underspecified User Queries (抖阴成年 Foundational Research, 2026) (in Proceedings of the AI for Law Workshop at the International Conference on Machine Learning (ICML 2026), available at ).听

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 抖阴成年. 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鈥檚 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.

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鈥攁ble to see the agent鈥檚 reasoning as it unfolds, step in to redirect its approach, challenge its assumptions, and probe whether alternative angles have been considered.

CoCounsel Legal doesn鈥檛 reason from the web 鈥� it鈥檚 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鈥檛 simply faster task completion 鈥� it鈥檚 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.听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鈥檚 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: 鈥淭he next generation of CoCounsel Legal seems to be a total game changer as听we’ve听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.鈥�

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鈥檚 next!”

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

Just as important as what we鈥檙e building is how we鈥檙e 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鈥檙e putting the solution in the hands of real lawyers working on real matters 鈥� listening closely to where it earns confidence, where it doesn鈥檛, and incorporating that feedback directly into how the product evolves.

We鈥檙e inviting customers to help shape what CoCounsel Legal becomes 鈥� 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鈥檛 come from launch announcements or benchmarks alone, but from sustained use 鈥� when lawyers choose to rely on the product because it holds up under real professional accountability.

Today鈥檚 beta is just the beginning. I鈥檓 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.

Rooted in Your Knowledge

Draft an Agreement Based on Your Precedent & Practical Law Content

Draft agreements faster without starting from scratch as CoCounsel鈥檚 drafting agent enables U.S. users to generate a comprehensive first draft in minutes using a trusted precedent or a Practical Law Standard Document. Simply upload source material, add key details and requirements, and CoCounsel analyzes the template, applies its structure and style, and produces a tailored multi鈥憄age draft aligned to the instructions provided. The result is a quicker path from blank page to a client-ready draft in a streamlined workflow with less manual assembly allowing users to spend more time reviewing, negotiating, and advising. Review and then export to Microsoft Word when ready.

My Clauses

Using the new My Clauses in CoCounsel (U.S.), transactional lawyers can build a personal, searchable library of preferred contract provisions saved from playbooks, draft and modify outputs, or added manually so the right language is always within reach. Find what is needed in seconds, tailor it to the specific matter, and reuse it instantly across new agreements. That means less time hunting through old files, fewer drafting interruptions, more consistency across matters, and faster turnaround from first draft to final.

Built for How You Work

Draft Editor

Draft Editor is an integrated editing environment available in the U.S., UK, Canada, and Australia that lets users refine AI-generated outputs directly in their browser 鈥� no need to export to Word or switch applications. Available across key skills including Review Documents, Draft, Summarize, and Timeline, simply click 鈥榦pen editor鈥� to start refining work. By enabling in-place editing, it keeps users focused on their work instead of managing workflow. The result: faster turnaround times, fewer interruptions, and a seamless path from AI assistance to polished work product.

Region Settings

Now available in the U.S., UK, Canada and Australia, lawyers can access a flexible, jurisdiction selection feature built directly into CoCounsel for Microsoft Word that enables seamless switching between region content and localization 鈥� regardless of regional subscription. Users also can access corresponding Westlaw and Practical Law content from existing subscriptions without purchasing separate regional entitlements or managing multiple logins. Additionally, an improved capability to switch between jurisdictions eliminates geographical limitations in the drafting workflow.

Citations Format Update

CoCounsel now delivers citations as endnotes (with hyperlinks) instead of footnotes in the U.S., UK, Canada and Australia 鈥� so your finished Word document reads cleanly from start to finish 鈥� a key preference often heard from customers. When exporting the output of any CoCounsel skill or workflow, citations appear at the end of the document, and each in-text citation links to the supporting source and back again. This creates less scrolling and fewer distractions while the work is reviewed, shared, and finalized, especially on longer drafts and research-heavy documents. The in-app experience stays the same; this update improves the readability of exported documents while keeping sources easy to verify.

Tabular Analysis

Tabular analysis is now available in Canadian French.听 Users can review up to 10,000 documents and 100 questions, viewing the results in a dynamic, filterable table format.听 This flexible capability enables users to add or remove files or questions mid-review, analyze results in a three-pane viewer, and run multiple tables simultaneously. The powerful solution significantly reduces document review time while enabling easy verification with clickable footnotes. This allows legal professionals to concentrate more on strategic, high-value tasks, and enhancing productivity while reducing valuable resource needs.

Explore These New CoCounsel Legal Features Today

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

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

* certain capabilities or integrations may require a subscription to other products

Building on the excitement of 抖阴成年 announcing that more than one million professionals have chosen CoCounsel, the company鈥檚 professional-grade AI, this month’s CoCounsel Legal release brings a wave of new capabilities to streamline research, drafting, and document review for legal professionals. These updates reflect the principles driving our roadmap: Agentic AI grounded in deep legal expertise, rooted in your own knowledge and workflows, and built to elevate the way modern legal teams operate.

Agentic AI Grounded in Deep Legal Expertise

Westlaw Advantage Canada with Deep Research

Westlaw Advantage applies agentic AI to trusted authoritative content, acting like an expert researcher to help you quickly move from research to strategy. At the heart of Westlaw Advantage is听Deep Research, the legal industry鈥檚 first professional-grade agentic AI research capability. By combining advanced AI with Westlaw鈥檚 unmatched content library, it streamlines complex research in English or French, delivering comprehensive coverage while significantly reducing manual research time. Westlaw Advantage Canada is more than just a research solution; it鈥檚 a strategic element of CoCounsel, our AI technology, available to every Canadian legal professional.

Westlaw Advantage Canada Deep Research Report

Deep Research in Practical Law US

Deep Research in Practical Law brings a smarter, more intuitive approach to using all the know-how resources. It feels less like searching Practical Law and more like working alongside a Practical Law editor who has instant command of every resource and tool at your disposal. Powered by agentic AI and grounded in Practical Law鈥檚 trusted and up-to-date content, it automatically plans research steps, pulls the most relevant guidance and templates, and delivers a clear, well-supported research report. Deep Research reviews multiple Practical Law resources, synthesizing the key guidance, and iteratively exploring further until it has exhausted its work, eliminating manual tedious, multi-step workflows鈥攈elping you move from “how to?” to “here’s how” faster. And, with easy access to the underlying sources for verification, you can move confidently to the next phase of your matter.

Deep Research Verification Tools for US

Verifying AI generated research shouldn鈥檛 slow attorneys down鈥攁nd now it doesn鈥檛 have to. CoCounsel Legal鈥檚 built in verification tools surface clear statements alongside their supporting sources, use AI to assess how well those sources align, and apply adversarial review to highlight potential gaps or missing context. By bringing together supporting evidence, counter perspectives, and direct connections to Key Numbers and KeyCite, attorneys can quickly validate research, strengthen their arguments, and stay confidently in control鈥攚ithout losing momentum.

Rooted in Your Knowledge

Draft a New Agreement Using Your Precedent Document (Beta)

This AI-powered capability provides transactional attorneys the ability to create a comprehensive first drafts in minutes. Upload a trusted precedent document, describe specific needs, and receive a complete, multi-page draft that follows the firm’s structure and style. This transforms hours of drafting work into minutes, delivering relevant drafts that reflect firm standards allowing attorneys to focus more on strategy.

Draft a new agreement using your precedent document

Create a Lease Agreement Abstract

First released in the U.S. and now available in the UK, Canada, and Australia, this capability efficiently produces concise, tabular summaries of lease agreements using a user-specified template. Upload lease documents and receive structured summaries in Markdown or Microsoft Word format, complete with instant citations to relevant contract sections for enhanced accuracy and rapid verification.

Create a Lease Agreement Abstract

Benchmark Document Against Standard

Now live in the UK, Canada, and Australia, as well as the U.S., this tool lets users assess a negotiated document by comparing it against a user-uploaded 鈥渋deal contract鈥� to highlight missing clauses or key deviations. It enhances alignment and risk management by identifying gaps and offering practical recommendations that help streamline negotiations.

Benchmark Document Against Standard

Syncly Box and Dropbox Integrations

CoCounsel Legal now integrates with Dropbox and Box through Syncly, enabling secure document import. This simplifies workflows by bringing documents stored across systems into one continuous workflow for analysis, research, and drafting.

Customise a Practical Law Agreement

Now available in the UK, Canada, and Australia alongside the US, this workflow enables legal professionals to tailor a Practical Law standard document according to specified instructions and provisions of a term sheet. By incorporating deal-specific details into template agreements and utilizing expertly drafted Practical Law content as a foundation, it significantly streamlines the drafting process.

Customise a Practical Law Agreement

Built for how you work

Tabular Analysis

Now available in the U.S., with UK and Canada coming soon, transforms high-volume document review by allowing users to process up to 10,000 documents and 100 questions in a dynamic, filterable table. With the ability to modify reviews in progress and run multiple tables simultaneously, it offers unmatched scalability and efficiency, enabling legal professionals to focus on strategic, high-value tasks.

Tabular analysis

Find Practical Law Drafting Language – UK

Quickly find drafting language from trusted content using a simple prompt within Practical Law Search & Summarise or CoCounsel. This capability streamlines the drafting process by helping users locate specific, verifiable drafting language powered by Practical Law鈥檚 expert-written content.

Outline Case File

This litigation-focused skill for the US examines entire case records to identify relevant documents, extract key facts, and create an outline connecting facts to claims. It significantly reduces review time, helping professionals quickly get up to speed and identify strengths, weaknesses, and gaps in the factual record.

Outline Case File

Explore these new CoCounsel Legal features today听

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

To keep up to date on听听new enhancements, sign up for the听听today.

We鈥檙e starting 2026 with a powerful lineup of CoCounsel Legal releases that signal where the product is headed鈥攁nd what continues to set it apart. Each new capability reflects the principles driving our roadmap: agentic AI grounded in legal expertise, rooted in your knowledge, and built for how you work. Here鈥檚 what鈥檚 new to help you begin the year with clarity, speed, and confidence.

Agentic AI, Grounded in Expertise

Deep Research on Practical Law UK (US coming soon)

Deep research is an advanced agentic research capability inside Practical Law that plans multi鈥憇tep research, retrieves authoritative guidance and templates, and produces a supported research report. The new capability in CoCounsel Legal eliminates tedious research steps, connects insights across multiple sources, and helps make faster, more confident decisions with traceable authority.

Deep Research on Westlaw Advantage UK

Deep Research on Westlaw Advantage UK is a multi鈥憇tep, agentic research tool that builds, executes, and iteratively improves a research plan using trusted Westlaw content.听 It enables the ability to streamline complex research by easily gathering the right authorities with minimal effort and move from research to strategy with greater confidence and speed.

Smart Browse

Smart Browse automatically highlights the most relevant portions of case law and statutory materials based on your research purpose. Enabling faster case prep and reducing information overload, it cuts through noise and elevates what matters most, helping legal professionals save significant time scanning long documents while improving research precision.

Arguments and Counterarguments

Users can now quickly听identify听weaknesses in opposing arguments and develop stronger counter-positions with the new arguments and counterarguments skill. Leveraging Westlaw Advantage鈥檚 Litigation Document Analyzer, the new skill will summarize and extract the arguments, generate potential counterarguments, and provide legal insights grounded in Westlaw content for each counterargument, greatly reducing response preparation time.

Rooted in Your Knowledge

Custom Prompts & Sharing

You can now create, customize, save, and share prompts in empowering teams such as practice groups to standardize prompting for repeatable legal work and outputs.

Built For How You Work

Tabular Analysis

The tabular analysis capability, coming soon, lets users review up to 10,000 documents against 100 questions. Delivering results in an interactive, filterable table with source verification through clickable footnotes, users can add/remove files or questions mid-review and run multiple tables simultaneously. Tabular analysis helps relieve tedious document review delivering greater clarity more efficiently across thousands of documents.

UX/UI Refresh 鈥� CoCounsel Microsoft Word Add-in

dd-in offers a cleaner, more intuitive interface including simpler navigation, alphabetized skills, fast mode switching, and quick access to 鈥淲hat鈥檚 New?鈥� updates. The refresh helps speed up your workflow and find the right skills more quickly鈥攁llowing more time spent practicing law and less time navigating menus.

Why Agentic AI Matters

The distinction between AI copilots and agentic AI solutions isn’t just semantic 鈥� it’s fundamental to how legal work gets done. While copilots offer suggestions and assistance, agentic AI like CoCounsel Legal takes on complex, multi-step professional work with advanced reasoning, authoritative content integration, and deep subject matter expertise.

The UK launch of CoCounsel Legal represents more than geographic expansion. It’s the convergence of critical innovations: Deep Research capabilities on both Practical Law and Westlaw Advantage, and seamless integration with existing legal technology ecosystems including Microsoft 365, document management systems, and 抖阴成年 HighQ.

Sam Dixon, chief innovation officer at Womble Bond Dickinson, said: “We knew we needed to bring in a GenAI legal assistant to help us deliver the best possible service we can for clients. For us, the fact that CoCounsel had the ability to lean on the Westlaw content and the Practical Law content was really beneficial. And it already integrates with a lot of the rest of our legal tech stack, such as HighQ.”

CoCounsel Legal’s native integration with existing workflows means legal professionals don’t have to choose between innovation and productivity 鈥� they get both.

“We have found the working relationship with 抖阴成年 very collaborative, transparent and supportive 鈥� real partners who go the extra mile to support us in getting value out of our relationship,鈥� said Christina Demetriades, global operating officer, Accenture Legal. 鈥淐oCounsel is a massive opportunity for our function 鈥� we see it as a way of displacing outside counsel spend and augmenting our team in practice 鈥� I see it helping build the Future Ready Legal professional. I have already used it myself to prepare advice for our business on an upcoming opmodel transformation. It was a great value add.”

Deep Research: A Global First for UK Legal Professionals

The UK launch introduces several industry firsts. debuts globally in the UK, with its U.S. release set for February. The new brings professional-grade agentic AI research capabilities specifically tailored to UK legal content. Most significantly, both content sets are unified in a single platform, eliminating the need to navigate between systems while delivering comprehensive results across practice areas.

What makes Deep Research genuinely transformative is its ability to reason, plan, and execute comprehensive legal research autonomously. It doesn’t just retrieve information 鈥� it generates multi-step research plans, traces its logic with transparent reasoning, and delivers structured reports backed by Westlaw and Practical Law citations. Legal professionals can hand off complete research questions to an AI that understands the assignment, explains its process, sources its answers, and builds argument foundations, all with human oversight.

The Foundation for Professional AI

David Wong, chief product officer, 抖阴成年, said: “Professional-grade AI is fundamentally changing how legal work gets done, and with CoCounsel Legal, we’re delivering enterprise-ready agentic AI that helps UK law firms and legal departments future-proof their practices. This isn’t just about efficiency 鈥� it’s about empowering legal professionals with AI that reasons through complex problems, integrates seamlessly into existing workflows, and scales across entire organizations while maintaining the trusted, authoritative foundation our customers depend on. This isn’t just about convenience 鈥� it’s about delivering real value to our clients and their work.”

That foundation 鈥� combining advanced reasoning models, authoritative content, deep subject matter expertise, and native integration 鈥� represents the essential components needed to complete complex, multi-step professional work. It’s what separates professional-grade AI from consumer-grade tools, and what makes CoCounsel Legal uniquely positioned to transform how legal work happens in practice, not just in theory.

Looking Ahead

The UK launch of CoCounsel Legal signals a broader shift in how professional services will be delivered. As agentic AI capabilities mature and expand, the question isn’t whether AI will transform legal work 鈥� it’s whether legal professionals and organizations will embrace tools purpose-built for their needs or settle for generic solutions that promise much but deliver little.

For UK legal professionals ready to explore what professional-grade agentic AI can do for their practice, the opportunity is here. The future of legal work isn’t waiting 鈥� it’s embedded in the work itself.

Learn more about .

Recognizing that client expectations are evolving, BLG is committed to anticipating client needs and exploring new approaches to legal work using emerging AI capabilities. This means reimagining workflows to free up lawyer time for complex problem-solving and strategic work, enabling teams to rethink how matters are handled and drive greater value for clients. By embracing AI, the firm is positioning itself for more agile client service in a rapidly evolving environment. To support these efforts, BLG needed tools that could handle growing work volume and sophistication without compromising quality.听

The firm also identified a talent imperative: today’s emerging legal professionals expect to work with advanced AI tools that will shape the future of legal practice and empower them to do their best work. To continue attracting forward-thinking talent, BLG needed to demonstrate its leadership in responsible AI adoption by giving professionals access to the right tools and training to elevate their impact and redefine exceptional client service.听

As part of its firmwide AI strategy, BLG undertook a comprehensive evaluation of AI solutions, piloting CoCounsel through multiple versions. This hands-on evaluation gave BLG confidence that 抖阴成年 was building something transformative.听

BLG selected CoCounsel for three reasons:听

• 鈥�Integration and workflow fit:鈥疌oCounsel integrates with Westlaw and Practical Law to create a single, trusted legal ecosystem based on authoritative Canadian legal content. Everyone at the firm can access these AI capabilities鈥攍awyers, law clerks, paralegals, and members of business services teams.
• 鈥�Governance and responsibility:鈥兑醭赡�’ guardrails, security practices, and Trust Principles align with BLG’s standards for client confidentiality and responsible AI use.
• 鈥�Product maturity and roadmap:鈥疌oCounsel’s demonstrated performance, together with 抖阴成年’ evolution as a legal technology company, gave BLG confidence in a platform that will continue to evolve.

“We see this technology as fundamentally transforming how legal work gets done,” said David Di Paolo, National Managing Partner & CEO of BLG. “It allows our lawyers to spend their time on the high-impact, complex problem-solving that clients really need from us.”听

BLG’s decision is grounded in a purposeful and holistic review process and a value creation framework designed to support long-term adoption and maximize the positive impact of the firm鈥檚 AI investments.听

“Clients are asking great questions about how AI can drive efficiency, and we see a powerful opportunity to advance how we deliver value for them,” added Di Paolo. “With CoCounsel, we鈥檙e stepping into a future of new possibilities, equipping our professionals with the right tools to meet rising expectations while positioning us to attract the next generation of legal talent.鈥�听

With CoCounsel, BLG deepens its relationship with 抖阴成年 and brings authoritative AI to its teams鈥攅nhancing speed, quality, and client service. As one of only two national, full-service Canadian law firms to partner with 抖阴成年 on this technology, BLG is helping to define legal industry transformation.听

Learn more听

To see how CoCounsel supports responsible AI adoption for leading firms like BLG, visit .听

At the conference, we are unveiling new beta features for CoCounsel Legal that tackle document review and agentic execution in a much more powerful way. Over the coming months, these new features will expand CoCounsel Legal鈥檚 capability to handle the broadest range of legal work with even more precision. We’ve also released several drafting improvements and announced a new partnership to seamlessly bring our trusted, authoritative content together with a law firm鈥檚 proprietary work product.

Built for How You Work

Focusing on speed, security, and collaboration, we’re making CoCounsel Legal faster, more intuitive, and more collaborative 鈥� all while maintaining the professional-grade trust and compliance our customers require.

Bulk Document Review (beta)

The beta release of CoCounsel Legal’s bulk document review redefines the approach to high-volume document analysis. Designed to tackle one of legal practice’s most resource-intensive challenges, this powerful solution will empower legal professionals to ingest vast document sets and receive intelligently structured, sortable results in an intuitive table format.

This capability will overhaul traditional review cycles, moving beyond the limitations of manual methods by enabling the efficient analysis of up to 10,000 documents in a fraction of the time. This can directly reduce the number of write-offs firms take when reviewing documents 鈥� an area that often impacts profitability per attorney.听听 CoCounsel Legal鈥檚 structured analysis provides immediate access to critical data, allowing for rapid filtering and sorting to pinpoint key information across a spectrum of vital workflows: from optimizing litigation discovery and streamlining M&A due diligence to enhancing regulatory compliance reviews and accelerating contract analysis.

Agentic AI, Grounded in Expertise

Leveraging an unmatched foundation of expertise and authoritative content from Westlaw and Practical Law, CoCounsel uses advanced AI to plan and execute complex, multi-step legal workflows.

Independent Execution of Legal Tasks (beta)

CoCounsel Legal will independently plan and execute complex, multistep legal workflows. With a single natural language prompt, legal professionals can trigger sophisticated workflows 鈥� whether conducting legal analysis, drafting documents, or researching case law. The platform intelligently interprets each request, maps the optimal execution strategy, and completes the entire workflow by integrating 抖阴成年 authoritative Westlaw and Practical Law content with the law firm’s proprietary knowledge base. The result? Less time managing tasks, more time delivering strategic counsel.

Custom Workflows (beta)

CoCounsel Legal’s workflow builder lets legal professionals design, save, and share custom workflows that combine 抖阴成年’ trusted content with their firm’s own expertise. It’s a straightforward way to build repeatable processes that capture institutional knowledge and scale best practices across the entire firm鈥攎aking everyone more efficient and consistent in how they work.

Deep Research on Westlaw 鈥� Expanded coverage, enhanced precision

Deep Research now covers state administrative materials in addition to federal sources, giving customers a more complete view of the regulatory landscape. Customers also get timely, curated updates on case law, regulatory changes, and practice developments from JD Supra, Quinlan, and Westlaw Daily Briefings. Plus, the new Clarifying Questions feature asks for additional details when it spots gaps, then reruns the analysis to make each report more precise and tailored to what customers actually need.

Identifying Citation Issues

CoCounsel’s Identifying Citation Issues feature allows users to upload a brief or memo and get an instant review for inaccurate or missing citations eliminating tedious, line by line checks. CoCounsel flags potential errors and presents a clear side by side table showing the original cite and the issue detected, allowing the ability to fix problems fast. Every check is validated against the trusted authority of Westlaw, delivering confidence that the cited sources are accurate before filing. The result: tighter documents, fewer surprises, and more time for the substance of the argument.

AI Overview for Statutes Compare

Comparing statute versions just got easier. With AI Overview in Statutes Compare, users can click once to get a clear, plain language summary of what changed materially between two versions 鈥� so less time is spent wading through long sections and cosmetic edits, and more time spent understanding the impact. It filters out formatting and nonsubstantive tweaks to spotlight the revisions that matter for analysis, improving efficiency, reducing the risk of missing a key change, and briefing clients or colleagues with confidence.

Find Practical Law Drafting Language

Find Practical Law drafting language is a new skill available to quickly find the drafting language needed by simply entering in a prompt for specific clauses or to fit certain scenarios, such as 鈥渇ind me drafting language where party A resides in a different state but agrees to this state鈥檚 forum.鈥� This AI-powered search capability eliminates the need to navigate complex taxonomies or remember exact clause titles, reducing drafting time while maintaining the rigor and reliability users trust and expect from Practical Law.

Practical Law Search & Summarize in Word

Designed to deepen the Practical Law integration within Word, this feature, coming soon, lets legal professionals ask how-to questions and get summarized, synthesized answers pulled from Practical Law’s full collection of practice notes, checklists, and standard documents. Responses include citations to source materials, making it easy to verify information or dig deeper.

Update Contract Terms

CoCounsel can now handle the tedious work of updating contract terms. Upload a term sheet, and it populates your template or precedent agreement with tracked changes and annotations showing what was revised. It’s a straightforward time-saver that reduces manual data entry errors and frees up legal professionals to focus on higher-level work

Rooted in Your Knowledge

By integrating with document management systems, precedents, and templates, CoCounsel Legal delivers insights that draw from both a firm’s institutional knowledge and 抖阴成年 authoritative sources

NetDocuments and the ndConnect Program

A with NetDocuments delivers another advantage for legal professionals. With the introduction of ndConnect, NetDocuments鈥� new interoperability program, legal professionals can securely incorporate AI capabilities from CoCounsel Legal into their document management workflows. Users can now conduct legal research with Westlaw and Practical Law, draft documents based on both their own internal content and that of 抖阴成年, and analyze documents with advanced review capabilities 鈥� all while maintaining their documents鈥� integrity and metadata within NetDocuments.

Deep Research in Practical Law (beta)

Legal research is consistently one of the most important AI use cases for legal professionals. CoCounsel’s Deep Research is being built on authoritative 抖阴成年 content in Westlaw and Practical Law, giving lawyers the power to tackle complex, multi-step research through an agentic experience that is built on the legal authority they use and trust every day.

Deep Research on Practical Law, currently in beta with select customers, is a significant advancement toward the comprehensive, trusted, and seamless CoCounsel Legal research solution of the future. Deep Research on Practical Law plans the research steps, retrieves the most relevant guidance and templates from Practical Law, and presents clear, supported conclusions. It adapts as follow-up questions are asked, enabling deeper, more nuanced analysis.

This streamlined approach saves time, reduces friction, and builds confidence in the resulting work product. As the leading resource for legal know how content, Deep Research in Practical Law complements Westlaw’s primary-law expertise and supports the evolving needs of legal professionals.

HigQ and CoCounsel integration

Embedded with GenAI from 抖阴成年 CoCounsel, HighQ users can maximize and build on AI-generated insights and outputs through new waves of integrations that bring AI directly into their workflows and deliver greater client service.

Document Insights

This integration embeds CoCounsel’s document review and summarize skills directly into HighQ enabling users to understand documents faster, gain critical insights, and pinpoint and extract information at the point of need.

Integration with CoCounsel drafting capabilities

Within their HighQ workflow, users can seamlessly access drafting capabilities in CoCounsel to review a document, edit, redline it against a playbook and more. The new integration allows users to leverage their documents in HighQ and eliminate versioning risks and manual uploads, saving significant time on drafting and review tasks.

Self-Service Q&A

A new AI-powered chat experience within modernized HighQ dashboards leverages CoCounsel鈥檚 search a database skill. Clients and stakeholders can now ask natural language questions about curated document sets and receive summarized, highly relevant answers in minutes, transforming static repositories into dynamic knowledge hubs.

Streamlined workflows, connected experiences and performance improvements

Practice area specific prompts in the CoCounsel Library

New expert-crafted prompts by Practical Law editors are now available directly in the CoCounsel Library, providing a precise starting point for tasks across various practice areas including criminal law, personal injury, data privacy, litigation, and more. Developed by legal experts, these prompts ensure accuracy and efficiency, helping move work forward faster.

Expanded CoCounsel Library accessibility

As the CoCounsel Library becomes even more accessible, users will be able to access CoCounsel directly from Westlaw and Practical Law in the U.S., and Microsoft Word and Outlook internationally. This reduces context switching and accelerates workflow with faster start times, improved document analysis, and quick access to frequently used prompts and skills without switching platforms.

Syncly Google Drive connector for CoCounsel Legal

For law firms using Google Drive, CoCounsel Legal now connects directly via Syncly. The connection allows users to upload documents from Google Drive into CoCounsel while preserving metadata and permissions. This will eliminate manual downloads and uploads, ensuring you’re always working with the most current and auditable document. version.

AI Overview for Statutes Compare

When comparing two versions of a statute, you can choose to receive an AI Overview of the substantive changes. This intelligent feature filters out minor formatting adjustments and highlights the changes that truly matter, saving you valuable time in reviewing lengthy statutory documents.

Moving Faster, Working Smarter

Platform updates led to a 97% reduction in CoCounsel’s average file download time. Additionally, the average time required to complete tasks using skills rooted in our industry-leading content has a 31% average improvement, reflecting changes in AI performance on features including Ask Practical Law AI, Summarize Documents and user鈥檚 open documents within CoCounsel.

In addition, through testing and optimization efforts, we have improved the quality and reliability of the draft skill in CoCounsel by migrating the underlying LLM to GPT5. Users should experience reductions in application startup times and higher-quality precision output enabling them to complete first drafts more completely and accurately.

CoCounsel grows internationally adding multiple languages

CoCounsel is expanding its footprint internationally and adding new languages including French, German and Japanese. The professional-grade legal AI assistant will be available in France, Benelux听/Brussels, Luxembourg and Quebec (French), Germany, Austria and Switzerland (German), Brazil (Portuguese), Argentina (Spanish), and Japan (Japanese) allowing more legal professionals to benefit from CoCounsel鈥檚 capabilities.

CoCounsel is also available in the U.S., UK, Canada, New Zealand, Hong Kong, Southeast Asia and United Arab Emirates.

And if you would like to see a deeper dive of Deep Research on Westlaw Advantage, check out the .

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