For litigators, that matters because some of the most important context in a matter does not begin in a research or drafting tool. It begins in the evidence.听

Documents. Testimony. Facts developed over the course of discovery. The record a lawyer ultimately has to connect to the law and turn into analysis, strategy, and work product they can stand behind. AI should make that process easier.听

This week at ILTACON, 抖阴成年 and Everlaw announced plans to integrate Everlaw with CoCounsel Legal. The first planned integration will allow mutual customers to bring Everlaw documents into CoCounsel Legal in bulk, making it easier to use litigation and investigation materials across CoCounsel Legal鈥檚 research, analysis, drafting, and workflow capabilities.听

For customers, that means less friction between reviewing evidence and doing the legal work that follows.听

For us, it is also one more piece of the broader CoCounsel Legal ecosystem we are building: connecting the systems, content, and tools professionals already rely on so they can move through complex legal work with more continuity and less unnecessary handoff.听

Everlaw brings an important part of that ecosystem into the picture for litigation: the evidentiary record.

Connecting evidence, context, and legal analysis听

A litigator rarely asks a purely abstract legal question. The real question is how the facts, evidence, and applicable law come together: whether a particular document changes the argument, whether testimony is consistent with the rest of the record, or whether the evidence supports the position being put before a court. Carrying that context through the legal workflow is essential to making AI genuinely useful in litigation.听

CoCounsel Legal brings together research, analysis, drafting, and other legal workflows with authoritative content from Westlaw and Practical Law. But in litigation, authoritative legal information is only one part of the picture. The evidentiary record matters just as much.听

Bringing those worlds closer together can make AI much more useful in the day-to-day practice of law.听

By reducing the need to manually move documents between systems, we can help lawyers spend less time on those handoffs and get to the substantive legal work faster.听

Moving from evidence to analysis with less friction听

Consider what happens when a litigation team identifies a set of important documents during discovery.听

Those materials may already have been collected, reviewed, organized, and understood within an eDiscovery platform. But when the team moves into other parts of the legal workflow, that context does not always move with them.听

That can mean exporting documents, uploading them into another environment, and reconstructing parts of the matter before the lawyer can move forward. Every handoff creates friction.听

The planned Everlaw integration is intended to shorten that path. Once Everlaw documents are available in CoCounsel Legal, lawyers can apply CoCounsel Legal鈥檚 research, analysis, drafting, and workflow capabilities to those materials, creating a more direct connection between the evidentiary record and the legal work that follows.听

It is also exactly the kind of connection we want to keep adding across the CoCounsel Legal ecosystem: bringing more of the places where legal work already happens into a workflow where professionals can research, analyze, draft, and act with the right context around them.听

Connected AI still has to meet the standard of legal work听

Making more information available to AI cannot mean lowering the standard for what comes out. The lawyer is still responsible for the argument. Still responsible for the citation. Still responsible for understanding whether the evidence supports the conclusion.听

That is why verification, transparency, and professional judgment matter so much. At 抖阴成年, we describe this standard as Fiduciary-Grade AI: AI designed for high-stakes professional work, grounded in authoritative information and built so professionals can review, verify, and ultimately stand behind the work it helps produce.听

Connecting more of the matter into that workflow should strengthen the lawyer鈥檚 ability to exercise judgment, not remove the lawyer from the process.听

Building a broader ecosystem around legal work听

Law firms and legal departments have invested in specialized technology for a reason.听

Evidence may live in an eDiscovery platform. Documents may live in a document management system. Legal research comes from trusted legal sources. Work product may move through several systems before it is complete. AI is not going to make that ecosystem disappear. The opportunity is to make it work together better.听

That is the direction we are taking with CoCounsel Legal. We are building an ecosystem designed to connect the tools, content, and workflows professionals already depend on, while preserving the context, permissions, controls, and trust required for high-stakes work.听

Everlaw is an important addition to that ecosystem because it brings the evidentiary record closer to the research, analysis, and drafting lawyers are already doing in CoCounsel Legal.听

And it is one part of a much broader direction.听

As we continue expanding the CoCounsel Legal ecosystem, we want professionals to be able to bring more of their work, their context, and the systems they trust into a more connected AI experience.听

For customers, that can mean fewer unnecessary handoffs and a more direct path from evidence to insight and work product.听

For the industry, it is another signal of where legal AI is headed. The next generation of legal AI will not just be more capable. It will be built to connect the work around it.听

抖阴成年 is working with Google Cloud to connect HighQ with Gemini Enterprise for Legal, giving legal professionals a secure way to bring authorized matter documents, structured data, and workflows into the AI environment where they are collaborating.

The HighQ MCP connection is now live alongside Google Cloud’s announcement of Gemini Enterprise for Legal.

This is an important milestone, but it is also exactly that: one milestone. HighQ is the natural place to begin because it contains the live matter context AI needs to be useful. Over time, we see opportunities to extend more of the trusted capabilities of CoCounsel Legal across the AI environments our customers choose to use.

Why matter context matters

Enterprise AI continues to improve, but legal work has always depended on context. That context is more than documents. It includes structured matter data, workflows, tasks, templates, collaboration history, deadlines, permissions, and the institutional knowledge surrounding a case or transaction. Much of that lives in HighQ.

Law firms and corporate legal departments rely on HighQ to manage matters, collaborate internally and externally with clients and outside counsel, power secure client portals, and organize work that evolves over weeks, months, or years. Connecting HighQ with Gemini Enterprise for Legal allows authorized users to securely access that context without exporting files, copying information between systems, or recreating it somewhere else.

A legal team could ask Gemini Enterprise for Legal to summarize documents in an authorized matter, identify upcoming deadlines from an iSheet, compare structured deal data with underlying agreements, or bring relevant matter information into a draft.

The value is not simply giving AI access to more information. It is giving AI access to the right information, with the governance legal organizations already depend on.

Governance isn’t optional

Legal organizations should not have to choose between adopting new AI capabilities and maintaining the controls their work requires.

The HighQ MCP connection is designed so organizations don’t have to make that tradeoff. Content remains in HighQ. Once a customer securely connects HighQ, users authenticate using their existing HighQ credentials, and existing matter walls; folder permissions, document-level security, and audit logging continue to apply. Gemini Enterprise for Legal can retrieve only the content an individual user is already authorized to access. The connection is read-only, allowing AI to retrieve authorized information without changing the underlying content.

That means organizations can confidently extend trusted matter context into Gemini Enterprise for Legal while keeping governance exactly where it belongs.

Extending CoCounsel Legal into the enterprise AI ecosystem

This announcement is about more than connecting two products.

CoCounsel Legal remains the trusted platform where legal professionals perform complex legal work. It brings together authoritative legal content, customer context, agentic workflows, verification, and human oversight to help professionals produce work they can verify and stand behind.

At the same time, legal teams increasingly collaborate with business colleagues, outside counsel, customers, and partners who may be working in different AI environments.

Open standards like MCP make it possible to extend trusted legal context and capabilities into those environments without requiring organizations to move their work out of CoCounsel Legal or compromise on governance.

Today’s HighQ integration is the first exciting step in that broader vision with Google Cloud.

Building an open ecosystem for trusted legal AI

The future of enterprise AI will not be defined by a single model or a single interface.

Organizations will continue using different AI environments for different types of work. Our role is to ensure that wherever legal professionals collaborate, they can securely access the trusted matter context, authoritative content, and professional capabilities their work requires.

That is why 抖阴成年 continues to invest in MCPs, APIs, agentic systems, and strategic partnerships across the AI ecosystem.

“Customers have told us they want our AI solutions to connect seamlessly with the trusted systems they already rely on for everyday legal work,” said Satish Thomas, Vice President, Google Cloud. “Working together with 抖阴成年, we鈥檙e making it easy to bring critical matter context directly into their workflow today, while creating a path toward even deeper integrations over time.”

The launch of Gemini Enterprise for Legal and the HighQ MCP connection demonstrates what’s possible when trusted matter context and enterprise AI are designed to work together. It’s an important step in our collaboration with Google Cloud and another step toward making trusted legal AI available wherever professionals need it, while keeping CoCounsel Legal at the center of how that work gets done.

The annual report relies on data from the Thomson Reuters Institute to review the performance of U.S. law firms and explore the trends and factors shaping the U.S. legal market. Below are five takeaways from the report.

1. A transformative shift is under way in the legal profession. Amid the evolution from traditional practices to innovative business models, law firms need to continue innovating and adapting to remain competitive, including implementing the latest technology, employing new business models and prioritizing client-centric practices.
2. Law firm leaders should 鈥渢ake advantage of the benefits of a lucrative 2024.鈥� The report noted that firms鈥� strong 2024 performance was defined by three metrics: demand, rates and expenses. Solid demand growth 鈥� across counter-cyclical and transactional practices 鈥� coupled with law firm billing rates accelerating at their fastest pace since the Great Financial Crisis contributed to law firms鈥� soaring profits, alongside expense growth levelling off.
3. The impact of generative AI will continue to drive shifting market factors in 2025:

• Strategic investment in technology: Firms need to prioritize technology investments to enhance productivity and adapt to the evolving legal tech landscape in order to drive long-term growth.

• Shifting pricing paradigms: The traditional billable hour model will be challenged by alternative pricing structures that prioritize value and client-centric approaches.

• Evolving talent models: The composition of law firms is in flux, with a shift toward more experienced lateral hires, growth in two-tier partner structures and less emphasis on junior associate hiring.

4. Growth may be dampened in 2025 due to potential weaker demand and global economic uncertainty. Though firms may see demand weaken in 2025, the report notes that results of the U.S. presidential election could boost demand as greater levels of economic and geopolitical instability generally see clients turn to their lawyers to mitigate risk. In addition, the 2025 outlook includes expense growth remaining at elevated levels, putting more pressure on profits.
5. 2025 will require firms to continue adapting to the impact of generative AI and emerging technologies. While firms took steps in 2024 to ensure sustainable growth in a changing market, innovative firms that invest in technologies and implement strategies to update their business model in 2025 鈥� including how they measure and reward lawyer performance 鈥� will be best positioned to achieve ongoing success.

Download the report鈥痜or strategies law firms can use to adapt their business models and implement new technologies to thrive amid changing market demands and clients鈥� needs.

Customers will experience a more seamless workflow within CoCounsel 2.0, the professional-grade GenAI assistant, across legal research products, including CoCounsel Core. The deeper integrations, available in late October, will further a user-centric experience throughout the 抖阴成年 legal solutions portfolio and improve ease of use.

The deeper integrations will improve ease of use in two ways:

• The full CoCounsel AI assistant will be available in the user interface of Westlaw and Practical Law, enabling users to be able to use CoCounsel Core skills seamlessly.
• Users will soon be able to create an on-page analysis of Westlaw and Practical Law content with CoCounsel.

In addition, two new GenAI research features 鈥� Mischaracterization Identification and AI Jurisdictional Surveys 鈥� will help customers save substantial time and deliver greater confidence that legal research is accurate, thorough, and complete.

Mischaracterization Identification and AI Jurisdictional Surveys

Mischaracterization Identification is a new generative AI capability to help detect mischaracterizations and omissions in legal briefs. Customers can upload a brief to Westlaw Precision with CoCounsel and see where opposing counsel has mischaracterized the law, and judges using this feature will be able to see where all litigants may have mischaracterized the law in their filings.

鈥淚 often find that opposing counsel has miscited or overstated case authority, and when that happens, we can use it to great advantage with the court.鈥疶his tool would save tons of time in finding those opportunities,鈥� said Scott Matney, general counsel, FPS Inc.

鈥淭his enhancement [Mischaracterization Identification] is one of the most innovative legal tools available,鈥� said Susan Verbonitz, partner, Weir Greenblatt Pierce. 鈥淚t not only reduces time spent on the rinse-and-repeat task associated with human research, but it also identifies potential weaknesses in opponent鈥檚 arguments.鈥�

AI Jurisdictional Surveys on Westlaw Precision with CoCounsel is a generative AI skill that enables customers to do 50-state-survey research much faster than with traditional methods, saving hours of time. It provides relevant statute language for legal questions for each jurisdiction selected for federal and state jurisdictions and U.S. territories.

鈥淭ime is valuable and there is never enough of it,鈥� Verbonitz said. 鈥淎I Jurisdictional Surveys and the new mischaracterizations enhancement expand our research capabilities while also saving us time and reducing cost.鈥�

Read the press release for more on the deeper integrations with CoCounsel and new Westlaw features as well as upcoming product enhancements, including CoCounsel Drafting UK, and more generative AI in Practical Law and Contract Express.

And here at 抖阴成年 鈥� we haven鈥檛 stood still; in fact, we have never moved faster!

Within this 24-month period Professionals no longer need to speculate how AI听could听affect their work because they now have a better sense of how it听will 鈥斕�and in some cases already听is.

And for our customers in November 2023, we launched听AI-Assisted Research听鈥� which allows customers to ask complex legal research questions in natural language and quickly receive synthesized answers, with links to supporting authority from Westlaw content and links to further examine that authority. AI-Assisted Research streamlines the initial phase of legal research with sophisticated answers to questions and the authority those answers are based on, saving hours of work. In fact, this is how one of our valued customers describes the solution:

鈥淏ecause 抖阴成年 has the best case law database, lawyers can feel confident that the answer AI-Assisted Research is generating in response to our questions is well supported.听 The fact that the AI-Assisted Research delivers all the resources it relied upon in coming up the answer, right beneath the answer, amplifies the confidence we all can have in using the program to help with our research needs.鈥�听Andrew Bedigian, Larson LLP

And since launch 6k customers have run more than 1.5M searches through AI-Assisted Research. 抖阴成年 closed loop LLM is trained on millions of terabytes of our trusted and verified content 鈥� rather than publicly available information 鈥� and this generates the most trusted and reliable answer on the market today.

鈥淚 did go through and compare the ChatGPT paid version as compared to this AI-Assisted Research. What I can tell you is there is a major difference in the libraries that Westlaw has versus any other program. There is no other program that has the secondary sources, the court orders, the appellate documents, the primary sources 鈥� every single thing that Westlaw offers, which is not only on point and published, you have the citations, there鈥檚 a source of truth from where the information comes from and it鈥檚 only as good as the prompts you give it and the parameters you put.鈥�听Jesse Guth, owner, Guth Law Office

Our customers tell us each day what a critical tool AI assisted Research is for their legal research both to those new to the profession and those that are experienced in the field. By design our intuitive user experience guides customers to run follow-up research 鈥� AI Assisted Research provides customers with a comprehensive answer which can be easily interrogated, linking to more sources for validation.

鈥�At Blank Rome, we are committed to providing the highest levels of innovative client service. As part of this effort, last year we were excited to implement Westlaw Precision and Practical Law Dynamic AI capabilities for our attorneys, which has resulted in increased efficiencies and enhanced results.鈥�听 Frank Spadafino, chief information officer, Blank Rome

Over the years 抖阴成年 has always been at the forefront of legal research innovation, helping customers to reduce research times and ensure nothing important is missed. AI-Assisted Research is among the very best of these tools, and when it鈥檚 used as intended, it offers enormous benefits with very little risk of harm. I strongly encourage you to try it yourself 鈥� you will find it鈥檚 a powerful research tool you鈥檒l want to employ regularly in your research processes.

They offered advice on evaluating a vendor鈥檚 technology expertise, support services, and transparency. Also, they shared how firms and organizations can mitigate the risks posed by acquiring a vendor鈥檚 AI services while maximizing their investment in AI. Below are highlights from their conversation.

Keys to choosing AI vendors

To start the process of assessing potential AI vendors, Yaghoubi emphasized the importance of reviewing their experience and expertise 鈥渢o allow your business to make informed decisions about whether to engage the vendor.鈥�

Wong said that in addition to performance and cost, firms should consider safety and trust factors.

Ramanathan noted it鈥檚 important to consider whether you want a consumer- grade model 鈥� that鈥檚 cheaper 鈥� or a more reliable professional-grade model. He emphasized three criteria to focus on when choosing an AI vendor:

1. 鈥淲hat鈥檚 your philosophy and principles around how AI should be used?鈥� He said asking a vendor this question allows you to see if your firm鈥檚 vision and long-term strategy and roadmap are aligned with the vendor鈥檚 approach.
2. Request a vendor鈥檚 references and testimonials. Ramanathan explained that firms and organizations should ask vendors how many customers are already using their solutions. 鈥淎I is still a game of scale,鈥� he said. 鈥淵ou don鈥檛 want to be the first customer training a model.鈥�
3. Clarify the level of support and training a vendor provides. Ramanathan said this is key to ensuring that all levels of staff are trained and can use the AI solutions constructively.

Wong added that the questions he receives from potential clients focus on data, technology, and talent. He warned that some companies simply repackaged existing large language models (LLMs) for legal use cases without adding much.

鈥淐lients that are working with companies that are building AI have a say,鈥� Wong said. 鈥淭hey can contribute, iterate, and build the products.鈥�

Also, he stressed the importance of working with a vendor that knows how to customize solutions and integrate customer feedback into product development.

How vendors use data

Kapoor asked what customers should consider regarding how vendors use their data. Wong said that understanding the data flow and how the data is processed are key, as well as understanding licensing and data rights, including intellectual property usage rights, cyber risk, and data leakage.

Ramanathan noted encryption standards as well as access control are critical as is demanding transparency from vendors: 鈥淵ou have the right to ask how the data your inputting is used.鈥�

Ramanathan added, 鈥淕ood vendors should have governance systems that answer鈥� details such as where data is stored and who has access to it.

鈥淟ook for transparency鈥� on data output

Wong advised firms to 鈥渓ook for transparency鈥� from vendors, making sure they provide qualitative and quantitative information about the quality of their outputs. He said vendors should be guided by a set of AI principles and should follow a data governance and AI model governance process to mitigate hallucinations and potential risks.

Ramanathan noted that good vendors conduct regular model validation on a periodic basis. He also flagged that professional-grade AI solutions 鈥� unlike consumer-grade AI solutions 鈥� give a sense for the reliability of the answer.

Data output considerations also include encryption standards as well as vendors鈥� privacy and security policies. Ramanathan said a baseline is compliance with standards such as GDPR and CCPA.

鈥淭he privacy and security measures a vendor takes are a result of their philosophy about AI and how to use AI,鈥� Ramanathan said. 鈥淚t gives you a clue as to what you can expect downstream in terms of execution.鈥�

Ramanathan added that vendors should share their risk management framework and enterprise risk framework as well as disclose how frequently they conduct audits and what mitigating actions they put in place.

Wong added that most firms and organizations have 鈥渢ried and tested approaches for technology procurement鈥� that they should apply to assessing AI vendors too.

Lack of AI-Specific SLAs

When exploring initial and ongoing training and documentation, Shokoh asked if AI service-level agreements (SLAs) are similar to those offered for SaaS-type platforms.

Ramanathan said there are elements of SLAs similar to cloud software 鈥渢hat you can and should expect,鈥� such as uptime and maintenance. He noted the hard part is the lack of industry standards for AI-specific SLAs to address issues like response time and accuracy.

In the absence of industry standards, Ramanathan recommended asking questions around issues like product reliability controls and internal testing programs.

Going above the legal requirements

Part of assessing an AI vendor involves anticipating it will adapt to new and changing AI regulations, given the lack of a comprehensive federal law in United States and various states implementing their own guidance.

鈥淭here鈥檚 wide range and little consistency across the market,鈥� Wong said. 鈥淲hat 抖阴成年 has done is look at AI standards in all the markets that we operate in and identify the most restrictive standards. We use a combination of the NIST standards and the EU AI directive as the basis for much of our governance framework.鈥�

Wong added that 抖阴成年 applies this viewpoint to its risk management framework and to its data and AI model governance framework.

鈥淲e projected what the regulation would be rather than look at where the regulation is today,鈥� Ramanathan explained. 鈥淲e proactively defined what we call our Data and AI Ethics principles, which are very hard-coded guidelines that go into engineering our products as well.鈥�

To watch a recording of the webinar, .