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Thomson Reuters

Thomson Reuters builds CoCounsel, an AI assistant grounded in Westlaw case law and Practical Law guidance, for lawyers, tax and compliance teams who need cited, verifiable answers rather than plausible prose.

ResearchBusiness ToolsAI Assistant#Legal AI Assistant#Legal Research#Tax Compliance
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What is Thomson Reuters?

Thomson Reuters is a global content and technology company that sells authoritative information and professional software to lawyers, tax and accounting practitioners, compliance officers, trade teams and newsrooms. In an AI tools directory, however, the company is best understood through one product line rather than the whole conglomerate: CoCounsel, its AI assistant for professional work. The group organises itself around Legal, Tax and accounting, International trade and supply chain, Risk fraud and investigations, and the Reuters news business, and CoCounsel is the AI layer that now runs across most of those verticals.

What makes CoCounsel different from a general chatbot is not the model behind it but what it is allowed to reason from. The company describes CoCounsel Legal as reasoning from authoritative Westlaw primary law, Practical Law guidance, and your organization's own knowledge. That grounding is the entire product thesis: in legal and tax work, an answer that sounds right but cites a case that does not exist is worse than no answer at all.

Thomson Reuters markets CoCounsel as "Fiduciary-Grade AI™ built for high-stakes professional work", a phrase that signals the company's core bet. Thomson Reuters defines it as the standard for "how AI should work in high-stakes professions", aimed at professionals with duties of care and regulatory oversight. The positioning is deliberate: this is software sold to people who can be sanctioned by a court or a regulator for the work they submit.

The scale is substantial. Thomson Reuters has said CoCounsel reached one million customers across 107 countries and territories, running on a multi-model architecture that draws on frontier models from Anthropic, OpenAI and Google. That user figure is a vendor announcement rather than an audited disclosure, and should be read as such. (Based on public information)

Where CoCounsel came from

CoCounsel did not originate inside Thomson Reuters. It launched in March 2023 as a product of Casetext, billed as the first AI legal assistant built on GPT-4, and Thomson Reuters acquired the company a few months later for $650 million in cash. Since then the brand has been extended well past its original litigation-support scope, absorbing tax, audit, accounting, risk and trade workflows, and becoming the umbrella name for the group's professional AI.

Who this page is for

If you are evaluating AI for regulated professional work, the questions that matter are narrow and unusually consequential: what corpus does it search, can you verify every citation, does your confidential material leave your control, and how often is it wrong. This page answers those questions with sourced material where sources exist, and says so plainly where they do not.

Core Features

  • Deep Research: Deep Research is positioned as a professional-grade agentic research capability that reasons and plans before returning results grounded in Westlaw and Practical Law content. Rather than a single retrieval pass, it decomposes a legal question, works through sub-issues, and assembles a longer-form answer with the underlying authority attached.
  • Linked citation verification: Thomson Reuters states that every citation is linked and one click away for easy verification. This is the practical difference between a research tool and a drafting toy — the reviewer can jump from the assertion to the primary authority without re-running the search by hand.
  • Agentic workflow execution: The next generation of CoCounsel Legal is built on Anthropic's Claude Agent SDK as a unified agentic platform that plans, selects tools and adapts mid-workflow. The stated ambition is a system that behaves less like an autocomplete box and more like a junior colleague working through a matter.
  • High-volume document analysis: Tabular Analysis handles bulk document review at a scale the company quantifies as up to 10,000 documents and 100 questions in one pass, turning discovery sets and due diligence rooms into structured, queryable grids.
  • Guided workflows for named tasks: Rather than an open prompt box, Thomson Reuters ships production workflows for concrete deliverables — privacy policy drafting, employee policy drafting, complaint drafting, discovery requests and responses, and deposition transcript review.
  • Tax, audit and accounting coverage: The CoCounsel brand extends beyond law into tax compliance and audit, powering capabilities across ONESOURCE and Checkpoint, with the knowledge base extended to authoritative accounting standards content.
  • Firm knowledge integration: Alongside published authority, CoCounsel can reason over an organisation's own documents, so precedent from past matters sits beside primary law in the same answer.

Use Cases

  1. Litigation research under time pressure: A associate facing a motion deadline needs the controlling authority in a specific jurisdiction, plus the contrary line of cases. Deep Research runs the multi-step search across Westlaw, returns a structured answer, and links each proposition to its source so the associate spends their time judging the authority rather than hunting for it.
  2. Document review in discovery and due diligence: Given a production set or a data room, Tabular Analysis applies a consistent set of questions across thousands of documents at once and returns the answers as a grid. The value is not just speed — it is that every document gets asked the same questions, which manual review across a rotating team rarely achieves.
  3. Transactional drafting from a firm's own precedent: Because CoCounsel can be pointed at an organisation's knowledge as well as Practical Law, first drafts can inherit house style and negotiated positions instead of generic templates, which is usually the difference between a draft a partner will edit and one they will discard.
  4. Indirect tax compliance cycles: In tax departments, the recurring monthly grind is data import, validation and return mapping. Thomson Reuters has pushed agentic AI into exactly this loop through ONESOURCE, aiming to reduce the manual handling that generates both delay and audit exposure.
  5. Audit sampling and workpaper preparation: Document analysis applied to audit samples produces the supporting workpapers as a by-product of the review, which matters because audit defensibility depends on documentation as much as on the conclusion.
  6. Regulatory and compliance monitoring: For compliance teams tracking obligations across jurisdictions, the combination of authoritative regulatory content and AI summarisation shortens the gap between a rule changing and the business understanding what it must now do.

How to use Thomson Reuters

  1. Identify the right product, not the brand: Thomson Reuters is a group, not a single app. Decide first whether your need is legal (CoCounsel Legal, Westlaw, Practical Law), tax and accounting (ONESOURCE, Checkpoint, UltraTax), trade, or risk — the buying path and the interface differ by line.
  2. Contact sales for access: Thomson Reuters does not publish a price list for CoCounsel Legal; the product pages route buyers to a sales contact and a telephone number instead. There is no public self-service checkout, so plan for a scoping conversation rather than a credit card signup.
  3. Confirm jurisdictional coverage before committing: Coverage is rolled out region by region rather than switched on globally. Verify that your jurisdiction and practice area are actually supported by the content set, because the tool is only as good as the corpus behind it in your legal system.
  4. Connect your own knowledge sources: Configure the integrations you will actually use — Westlaw and Practical Law, Microsoft 365, and your document management system — so answers can draw on both published authority and internal precedent.
  5. Start with a bounded, verifiable task: Run a research question or document set where you already know the correct answer. This calibrates your sense of the tool's reliability before you rely on it for something you cannot independently check.
  6. Verify every citation before it leaves your desk: Use the linked citations to open each authority. This step is not optional in professional work, and the independent evidence discussed below explains exactly why.

Tips & Best Practices

  • Treat the citation link as the deliverable, not the prose: The generated summary is a navigation aid. The linked authority is the thing you are professionally accountable for, so read it rather than the paraphrase.
  • Ask jurisdiction-specific questions explicitly: Open-ended doctrinal questions invite generic answers. Naming the jurisdiction, the court level and the time window narrows the retrieval and materially improves what comes back.
  • Beware false-premise questions: If you ask a question that assumes a rule that does not exist, retrieval-based systems can still produce a confident-sounding answer. Phrase questions neutrally rather than asking the tool to confirm what you already believe.
  • Use it to widen the search, not to close it: The strongest reported use is surfacing lines of authority a practitioner had not considered. Treat output as an expanded starting set for your own judgment.
  • Keep a human in the loop at each stage of multi-step workflows: Agentic workflows chain several steps together, which means an early error propagates. Approving intermediate outputs catches mistakes while they are still cheap.
  • Feed it your own precedent deliberately: Output quality on drafting tasks improves sharply when the system can reason over the organisation's negotiated positions rather than only published templates.
  • Budget for the whole stack, not the AI line item: The AI capability is generally sold alongside the underlying research subscriptions, so evaluate total cost of the combined platform rather than the assistant in isolation.

Who is Thomson Reuters for?

  • Litigators and disputes teams: The document-heavy end of legal practice, where bulk review, chronology building and research across large case law corpora dominate the workload.
  • Transactional and corporate lawyers: Practitioners drafting and negotiating against precedent, who benefit from guidance content sitting alongside their firm's own document history.
  • In-house legal departments: Teams under pressure to absorb more work without headcount growth, where triage and first drafts are the bottleneck rather than novel legal analysis.
  • Tax and accounting professionals: Practitioners running compliance cycles across jurisdictions, where the work is high-volume, deadline-bound and unforgiving of data errors.
  • Audit teams: Reviewers who need consistent sampling and defensible workpapers, where documentation quality is itself part of the deliverable.
  • Compliance and risk officers: Functions tracking regulatory obligations across multiple regimes, where the cost of missing a change is measured in enforcement risk.
  • Trade and supply chain teams: Groups managing classification, sanctions screening and cross-border obligations against constantly shifting rules.
  • Large firms and enterprises generally: The commercial model, procurement path and integration surface are all built around organisational buyers rather than individual practitioners.

Platforms

  • Web application: The primary interface for CoCounsel and the research platforms, accessed through a browser with an authenticated organisational account.
  • Microsoft 365 integration: The company describes CoCounsel Legal as working within Microsoft 365, which puts the assistant inside the document environment where drafting actually happens rather than in a separate tab.
  • Document management system integration: Connections into DMS platforms allow the assistant to reason over a firm's existing document estate.
  • Westlaw and Practical Law: The AI capabilities are woven into the existing research platforms rather than sold purely as a standalone destination.
  • Tax and accounting platforms: Separate product surfaces including ONESOURCE, Checkpoint and tax preparation software carry their own AI capabilities under the CoCounsel banner.
  • Mobile and public API: Thomson Reuters offers a broad enterprise product estate, but a general-purpose public API for CoCounsel comparable to a developer platform is not something the public product pages set out. Confirm any programmatic access requirement directly with sales. (To be verified)

Pricing & Plans

There is no free tier and no public self-service signup for CoCounsel in the way consumer AI tools offer one. Thomson Reuters does not publish a price list for CoCounsel Legal; the product pages route buyers to a sales contact and a telephone number instead. Prospective buyers can request a demonstration, but the commercial terms are established through a sales conversation rather than a published rate card.

Paid access is structured as enterprise and professional subscriptions, typically sold in relation to the underlying research platforms rather than as an isolated AI add-on with a flat public price. Pricing in practice depends on firm size, contract term, which underlying subscriptions you hold and which modules you enable. Third-party sites publish estimated figures, but those estimates vary widely and contradict each other, so no specific number is reproduced here. The reliable statement is the one the vendor makes: pricing is quoted, not listed. Anyone budgeting for this should treat the total cost of the research platform plus the AI capability as the real figure, and should confirm renewal terms and seat minimums during negotiation.

Alternatives

  • LexisNexis (Lexis+ AI): The closest direct competitor, pairing a comparable proprietary legal corpus with generative AI. The choice between them is usually decided by which content library a firm already subscribes to.
  • Harvey: An AI platform aimed at large law firms and in-house teams, positioned around firm-specific workflows and bespoke deployment rather than ownership of a primary law database.
  • Spellbook: Focused on transactional drafting and contract review inside the word processor, a narrower and typically cheaper scope than a full research platform.
  • vLex Vincent: A legal research and AI offering with notably international coverage, often attractive where multi-jurisdictional reach matters more than depth in a single market.
  • General-purpose AI assistants: Tools such as ChatGPT or Claude used directly. They are far cheaper and more flexible, but they lack a licensed primary law corpus and citation linking, which is precisely the gap professional tools exist to fill.

Limitations & Considerations

The most important limitation is documented by independent researchers rather than the vendor. A preregistered Stanford RegLab study found that the legal research tools it tested, including Westlaw AI-Assisted Research and Ask Practical Law AI, hallucinated between 17% and 33% of the time. The same researchers concluded that providers' hallucination-free claims are overstated, while acknowledging that these tools do reduce hallucinations relative to general-purpose chatbots. Both halves of that finding matter: grounding demonstrably helps, and grounding is demonstrably not a guarantee.

Thomson Reuters is explicit that the technology "is designed to support human judgment, not replace it", and that professionals remain responsible for the work they sign off on. That is not boilerplate in this context — it is the correct allocation of risk given the measured error rates, and it means verification effort must be budgeted rather than assumed away.

Vendor-reported metrics should be read with the same care. Thomson Reuters cites its own customer survey figures, reporting that 76% agree the product improved research and drafting quality and 64% agree it helped reduce risk. These are self-reported satisfaction figures from the vendor's own research, not independently audited performance measurements, and they measure perception rather than accuracy.

Other considerations worth weighing before committing:

  • Jurisdictional coverage is uneven: Capabilities roll out market by market, with the United States leading and other jurisdictions following. Coverage depth outside the largest common-law markets should be verified for your specific practice area rather than assumed.
  • Subscription lock-in: The AI capability is generally tied to the underlying research platforms, so adopting it tends to deepen commitment to a single vendor's content ecosystem rather than remaining portable.
  • Opaque pricing complicates comparison: Without published rates, genuine like-for-like comparison against competitors requires running parallel sales processes.
  • Content recency and scope: Answers are bounded by the licensed corpus. Very recent developments, unpublished material, or sources outside the licensed set will not appear simply because the interface is conversational.
  • Verbosity in output: Reviewers on software marketplaces commonly note that responses can run longer than needed, which shifts some editing burden back onto the user.
  • Cost concentration for smaller practices: The combined platform cost represents a meaningful annual commitment, and the economics are considerably more favourable at firm scale than for a solo practitioner.

FAQ

Q1. Is Thomson Reuters CoCounsel free to use?

No. There is no free tier and no public self-service signup. Access is sold through enterprise and professional subscriptions arranged with the sales team, and the product pages direct interested buyers to contact the company rather than to a checkout page. A demonstration can be requested before purchase.

Q2. Does Thomson Reuters use my documents and prompts to train its AI models?

No, according to the company's own published statement. Thomson Reuters answers this directly: "Your user content and prompts are not used to train or improve CoCounsel and associated products or LLMs." The company further states that third-party partners such as OpenAI and Google are "contractually prohibited from using any customer data to train their models". Thomson Reuters also says it processes interactions with those third-party models in the United States and, where applicable, has controls to disable third-party abuse-monitoring so there is no human access to customer data.

Q3. Which AI models power CoCounsel? Are they built in-house?

Both. Thomson Reuters has described a multi-model architecture drawing on frontier models from Anthropic, OpenAI and Google alongside its own proprietary AI technology. The next generation of CoCounsel Legal is built specifically on Anthropic's Claude Agent SDK. So the underlying reasoning models are largely licensed from third parties, while the authoritative content, retrieval layer and professional workflows are Thomson Reuters' own.

Q4. Can CoCounsel hallucinate legal citations?

Yes. This is the single most important caveat. Independent Stanford RegLab research measured hallucination rates between 17% and 33% across the leading legal research AI tools it tested, including Thomson Reuters products, and concluded that vendor claims of hallucination-free output were overstated. Grounding in an authoritative corpus reduces the problem relative to general chatbots but does not eliminate it, which is why every citation must be opened and read.

Q5. How much does it cost?

Thomson Reuters does not publish pricing for CoCounsel. Costs are quoted individually and depend on firm size, contract length, which underlying research subscriptions you hold and which modules you enable. Third-party estimates circulate online but vary widely and conflict with one another, so they are not reliable for budgeting. Request a formal quote, and evaluate the combined cost of the research platform and the AI capability together.

Q6. Which platforms and systems does it work with?

CoCounsel Legal is described as working across Westlaw, Practical Law, Microsoft 365, and document management systems. The primary interface is a web application accessed with an organisational account, and the tax, audit and accounting capabilities appear within their own product surfaces such as ONESOURCE and Checkpoint rather than in a single unified app.

Q7. Is it available outside the United States?

Partially, and coverage is expanding rather than universal. Thomson Reuters announced CoCounsel Legal availability in the United Kingdom in January 2026, with further rollouts in markets including Canada and Australia. Because the tool's usefulness depends entirely on licensed content for your legal system, confirm coverage for your specific jurisdiction and practice area before purchasing.

Q8. Does it cover tax and accounting as well as law?

Yes. The CoCounsel brand now spans tax, audit, accounting, risk and trade in addition to legal work. Capabilities include agentic support for indirect tax compliance through ONESOURCE, document analysis applied to audit sampling and workpaper generation, and integration with Checkpoint research content, with the knowledge base extended to authoritative accounting standards material.

Q9. Who is accountable if the AI output is wrong?

The professional using it. Thomson Reuters states plainly that Fiduciary-Grade AI is designed to support human judgment, not replace it, and that professionals remain responsible for the advice they give and the work they sign off on. Courts and regulators have taken the same view, and no vendor assurance transfers professional responsibility away from the practitioner who files the document.

Q10. Is it worth it for a small firm or solo practitioner?

It depends heavily on practice volume. The economics favour organisations with enough document-heavy work to offset a substantial annual subscription covering both the research platform and the AI capability. For solo practitioners and small firms, the honest assessment is that the total commitment is significant relative to likely usage, and a narrower point solution may deliver better value than a full professional research stack. (Based on public information)

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