It is not simply a marker of adoption or growth. It is a sign of trust.听One million professionals chose to trust 成人VR视频 in听transforming听how they work.听They chose to听test and learn听to rely on something new, and to integrate AI into moments that matter. Each one听represents听a small but meaningful act of transformation: a lawyer who found an hour back in their day, a tax professional who turned research into insight, a compliance officer who had the right information at exactly the right moment. Those moments are why we build.

But if听I’m being听honest, one million is not enough.听We are winning the professional AI market for legal, tax, and compliance鈥攂ut we are not dominating it.听Not yet. And the gap between those two things is what propels us forward.

Transformation Is a听Journey,听not听a Headline

If you have ever tried to change something fundamental鈥攁 process, a company, or a mindset鈥攜ou know transformation is rarely clean or linear. It is messy. It is slow. It is full of hard conversations and rainy days when true north is hard to find and progress feels elusive.

At 成人VR视频, we have experienced all of that. What we have learned is that progress compounds when you keep showing up, block out the noise, and stay anchored to the mission.

Over the past two years,鈥�we have been transforming鈥痜rom a historically content-driven company into an AI-powered technology company. That shift takes more than shipping features or adopting new tools. It requires unlearning deeply ingrained habits, questioning long-held assumptions, and building the courage to change how decisions get made.

My role as CTO is to see where change needs to happen, incite it, and steer it鈥攚hile also听setting听the guardrails and tripwires that keep us from going off the rails. Our听teams’听role is to push against those boundaries and show us when they need to move. That tension between rigor and exploration is where innovation happens.

Creating Sparks of Change听

We see that tension听manifests听most clearly in how change happens. Transformation does not come from large committees or perfect plans. It comes from small, empowered teams making focused progress.

Across 成人VR视频, those teams have been the catalysts of change. They moved quickly, tested boldly, learned fast, and shared what worked and what did not. Their work is often unglamorous and invisible, but it is the reason this transformation is real.

They are also the reason CoCounsel exists. They turned agentic AI from a bold idea into something听nearly a听million professionals now use in their daily workflows.

Building Trust from the Inside Out

One of the most important lessons we learned early is that trust cannot be layered on after the fact.听It has to be engineered into the system.

Two years ago, we launched AI Assisted Research鈥攖he first generative AI feature in Westlaw. We had a vision of what good looked like, but the reality taught us that defining ‘good’ in generative AI is an iterative process, not a one-time decision.

What felt strong in our research loops needed refinement when put to the test with real human feedback. Legal professionals expected both the precision they relied on and the fluency they were beginning to experience elsewhere. Each round of feedback sharpened our understanding. Each deployment taught us something new about where the bar needed to be.

Those months were challenging, but they were also formative. The conversations with customers and with each other鈥攖he honest ones about what was working and what听wasn’t鈥攎ade our AI more reliable and听reshaped听how we think about accountability in AI systems. We learned how to build solutions with high trust. And in building trust,听slow听became fast.

But over time, this focus on trust created trade-offs we听hadn’t听fully听anticipated. Every verification layer we added, every human review checkpoint, every conservative threshold鈥攖hey made our AI trustworthy. But they also made us less听versatile,听less ambitious. More precise, but less fluid. More reliable, but less delightful.

We听optimized听for never being wrong. Our users wanted us to also听optimize听for being genuinely helpful.

From Vendor to Partner

Understanding that gap changed how we think about our relationship with customers. We do not want to be another vendor with a product. The world does not need more vendors.

What professionals want, and deserve, is a partner. A partner who listens, adapts, and is honest when something does not work. A partner who understands that trust is earned slowly and lost quickly.

This next phase of our transformation is about moving from transactional relationships to true partnerships. It is about building tools with our customers, not just for them, and meeting them where they are in their own transformation journeys.

Looking Ahead

One million users听proves听we听are听trusted. What it听doesn’t听prove yet is that听we’ve听built the AI professionals genuinely want to use鈥攏ot just the one they know听won’t听fail them.

That’s听what comes next.听We’re听keeping the trust听we’ve听earned while closing the gap on experience. Being both precise and ambitious. Both reliable and delightful.

This is harder than what听we’ve听done so far. It means moving faster without cutting corners. Being bolder without being reckless. Matching the pace of consumer AI without abandoning professional standards.

But听here’s听what I know: the teams who evolved AI Assisted Research into Westlaw Deep Research鈥攖he industry’s most advanced legal research system鈥攁nd who built CoCounsel into something a million professionals rely on鈥攖hey’re听not done.听We’re听not done.

Learn more about CoCounsel

But professional work听doesn’t听work that way.

When a lawyer needs to draft a court-ready brief, when a tax professional needs to navigate multi-jurisdictional compliance, when an auditor needs to assess risk across thousands of transactions鈥攖hey听don’t听need the cleverest chatbot. They need AI that understands their work, their standards, and their accountability.

That’s听what听we’ve听built. And the market is responding.

One million professionals have chosen CoCounsel. Not for pilots. Not for experiments. As core infrastructure for how they work. We serve leading enterprises across legal, risk, compliance, tax, accounting, audit and global trade in 107 countries and territories.

While competitors are听showcasing听demos,听we’re听delivering deployments. While startups are raising capital,听we’re听generating revenue. While others are figuring out trust,听we’ve听already earned it.

The Four Pillars of Professional AI鈥擜nd Why We Lead

成人VR视频 has been building technology and using AI for decades. But what听we’ve听done with generative AI over the past two years puts us in a category of our own.

Professional-grade AI听requires听four essential components working together. 成人VR视频 has all four听at scale:

We have听the technology. We work with every leading AI lab鈥擜nthropic, OpenAI, Microsoft, AWS, Google鈥攁nd听we’re听developing our own AI model built specifically for professional work.听We’re听not dependent on a single vendor or locked into one approach. We can use the best technology for each specific workflow.

We have the content.听Decades of curated, authoritative professional content that听can’t听be replicated. Not web-scraped data鈥攖he actual听sources听professionals stake their reputations on.

We have听the听expertise. 4,500+ domain experts who understand what “good” looks like in legal, tax, and compliance work. They define quality standards,听validate听outputs, and ensure our AI meets professional requirements.

We have听the tools. CoCounsel integrates directly into the professional workflows and platforms our customers already use鈥攆rom Westlaw听and听Checkpoint听to Microsoft 365.听Our AI doesn’t sit outside听the听work; it becomes part of听the听work.

These four components working together let us build AI capabilities that others simply听can’t.

Westlaw Deep Research听on CoCounsel Legal听can analyze thousands of documents and synthesize complex legal findings because we combine frontier AI models with our authoritative content library and domain听expertise听to ensure accuracy. Ready to Review听on CoCounsel Tax and Audit听can prepare complete 1040 tax returns鈥攏ot suggestions or drafts, but finished, filed returns that meet IRS standards鈥攂ecause our tools integrate directly into professional workflows with the quality standards our experts define.

Having one or two of these components means you can build demos. Having all four means you can build products professionals trust with their reputations.

We Have Advantages That Accelerate Our Lead

Having听the four听essential pillars is necessary. But two听additional听advantages strengthen our position:

We have听the听scale. One million professionals using our AI in production听teaches听us things competitors听can’t听learn from pilots. Every edge case becomes common. Every rare failure happens daily. That feedback loop makes our AI听better,听faster.

We have the capital. 成人VR视频 invests more than $200 million annually in productized AI and听has听11 billion dollars听in capital capacity through 2028 to fund continued innovation and selective acquisitions.

But having all four pillars plus scale and capital only matters if professionals听actually trust听your AI with their work. And trust at this level鈥攚here reputations, client relationships, and regulatory compliance are on the line鈥攔equires a different approach than consumer AI.

Trust听and Capability:听Our Competitive Advantage

Here’s听what we听learned听building AI at scale: in professional work, you need both trust and breakthrough capability. One without the other听isn’t听enough.

Consumer AI听optimizes for听impressive demos. Professional AI must deliver results you can stake your career on,听while听actually transforming听how work gets done.

Two years ago, we launched AI Assisted Research,听the first generative AI feature in Westlaw. We had a vision of what “good” looked like, but听deploying to听real legal听professionals taught us that defining quality in AI is iterative, not one-time.

Those early months were challenging. Every conversation with customers, every piece of feedback, every deployment taught us something new about where the bar needed to be. We learned that professionals expect both the precision听they’ve听always relied on from 成人VR视频 and the听transformational capability听they’re听experiencing with generative听AI.

We built for both. And we used what we learned to build something even better.

Every piece of feedback from AI Assisted Research informed how we developed Westlaw Deep Research鈥攏ow the world’s leading AI legal research capability. Deep Research听doesn’t听just answer legal questions; it analyzes thousands of documents, synthesizes complex findings across听jurisdictions, and delivers court-ready analysis with the citations and reasoning professionals require.听It’s听what happens when you combine frontier AI technology with authoritative content, domain听expertise, and real-world learning from a million professionals.

That same approach drives everything we build. CoCounsel delivers capabilities no one else can match听鈥撎齮he most advanced legal research system in the world, and the first AI that can prepare a complete 1040 tax return. Not suggestions or听drafts, but听finished work that meets professional standards.听

These听aren’t听incremental improvements.听They’re听capabilities that fundamentally change听what’s听possible in professional work.

And we deliver them with the trust professionals require:听

• 听Accuracy you can stake your reputation on听鈥� because we verify outputs against authoritative sources听
• Transparency you can explain to clients and regulators听鈥� because we show our reasoning and cite our sources听

• Security that guarantees your data stays yours听鈥� because we understand professional confidentiality听isn’t听negotiable听

• Integration with professional workflows听鈥� because AI that sits outside your tools听doesn’t听transform your work听

This is what professional-grade AI means.听Breakthrough capability with professional trust.听And this is why one million professionals chose 成人VR视频.

We’re听Accelerating鈥擜nd Defining the Future

One million users听proves听we’re听the leader in professional AI. But leadership听isn’t听a milestone鈥攊t’s听a commitment to staying ahead.

We’re听advancing听development听of our vertically specialized language model designed specifically for legal, tax, and compliance work.听We’re听expanding听CoCounsel’s听global footprint.听We’re听releasing new workflow-specific capabilities throughout 2026 that will further separate us from competitors.

Because听here’s听what we know: the real AI race听isn’t听about who builds the smartest general-purpose model.听It’s听about who can deliver transformational ROI in high-stakes professional environments where trust is non-negotiable.

成人VR视频 is听leading听that race. We have听the technology,听expertise, content, tools, scale, and capital. We have one million professionals听who’ve听chosen us as their AI partner. And听we’re听building the best professional AI in the world.

This听isn’t听the beginning of our AI journey鈥攚e’ve听been on it for decades. But it is the moment when the market recognizes what听we’ve听become: a leading AI technology company听that’s听defining what professional-grade AI means.

One million professionals are already experiencing that future. And听we’re听just getting started.

Learn more about CoCounsel.听听

Tax, Audit and Accounting has always been a profession built on rigor and responsibility. But the reality of running a modern tax practice is that complexity keeps rising, timelines keep tightening, and client expectations keep evolving. Firms are being asked to do more, faster鈥攚ithout compromising quality.

Why this matters for firms

This recognition is not just about a new solution being introduced鈥攊t’s about what firms are prioritizing right now. Across the industry, leaders are focused on creating repeatable capacity鈥攏ot just surviving busy season, but building workflows that are reliable year-round. That means reducing friction in the return process, improving consistency across teams, and ensuring professionals have the time to apply judgment where it matters most.

That’s the lens I bring to . It’s designed to support the parts of the tax return process that can slow teams down, so professionals can stay focused on the work of humans: review, judgment, accountability, and advising clients with confidence.

Restoring time for professional judgment

There’s a lot of discussion about automation and the future of work. What I see in firms today is more practical: talented professionals spending too much time on repetitive steps, and not enough time on review, coaching, and client conversations.

The opportunity here is to shift time back to the professional鈥攕o firms can:

• Strengthen quality and consistency
• Improve responsiveness to clients
• And make the work more sustainable for teams

Honorable Mention: Ready to Advise

Accounting Today also gave an Honorable Mention to , which is aimed at supporting tax planning and advisory services.

That matters because once firms create more capacity, the next question is how to use it. Many firms are looking to grow advisory in a way that’s scalable and consistent 鈥� grounded in strong workflows and clear client outcomes.

Recognition like this is meaningful for us at 成人VR视频鈥攂ut it’s even more meaningful because it reflects progress our customers can feel. When firms can rely on their technology to create more capacity and consistency in the work, they can serve clients with greater confidence, support their teams through peak demand, and make the practice more sustainable. That’s the kind of win we’re focused on: one that strengthens firms and the professionals who power them.

This post was authored by Elizabeth Beastrom, President of Tax, Audit & Accounting Professionals at 成人VR视频.

Ready to Review听is our new cloud-based, agentic AI tax workflow solution built on听CoCounsel.听For tax year 2025, it听modernizes 1040听tax听return听preparation听and is designed to take on the heavy, repetitive work of gathering client documents and preparing returns鈥攕o tax professionals can focus on what drew many of us to this profession in the first place: problem solving, critical thinking, and delivering great counsel to clients.听

For too long, firms have been stuck in a pattern that everyone recognizes as unsustainable鈥攅ver more complex returns, tighter deadlines, and mounting pressure on teams already stretched thin. Busy season has become synonymous with burnout and staffing strain. AI alone听won鈥檛听fix that, but AI put to work in the right way鈥攖hrough agentic AI that is deeply embedded into tax workflows鈥攃an fundamentally change the equation.听

The goal is not to replace professional judgment, but to clear away the manual, time-consuming tasks that prevent professionals from using that judgment to its fullest. Ready to Review gives firms a single, cloud-based, scalable platform that automates the gather and tax prep stages of the听workflow鈥攈elping firms manage more individual returns with existing staff while听maintaining听quality and control.听

We鈥檙e听already seeing the impact. Indiana-based CLH CPAs & Consultants听participated听in our early adopter program and saw听the potential for听transformative time savings. As Bob Lange, Partner at CLH, told us:听鈥淩educing return preparation time by听approximately an听hour on each simple 1040 is significant in terms of efficiency gains. For firms like ours, these time savings will be a game changer.鈥�听

I鈥檝e听said before that I expect firms will听ultimately pair听each CPA with at least one virtual agent. Ready to Review is a tangible step in that direction. It brings that 1:1 vision closer to reality by embedding Gather and Tax Preparer AI agents directly into the 1040 workflow in a way听that鈥檚听responsible, auditable, and grounded in trusted 成人VR视频 tax content and compliance听expertise.听

As solutions like Ready to Review become part of the day-to-day fabric of tax work,听we鈥檒l听see fewer 80-hour听weeks听and more time spent on the nuanced, client-focused work that truly differentiates firms.听We鈥檒l听make room for new talent who are excited about a career that leans into analysis and advisory rather than pure grind.听听

Ready to Review is now generally available in the United States for 1040 use cases, and its launch marks an important milestone in our broader journey with agentic AI on the听 platform.听It鈥檚听one more way听we鈥檙e听helping firms modernize in a way that is practical, grounded, and built for the realities of tax season.听

This post was authored by听Elizabeth Beastrom,听President of Tax and Accounting Professionals at听成人VR视频.听

At 成人VR视频, our starting point is, and will remain, methodology. For decades, firms have relied on 成人VR视频 PPC methodology as the gold standard for audit quality, documentation, and compliance. Our vision for AI in auditing builds on that foundation. We’re not asking firms to change how they practice. We’re focused on making PPC the most AI鈥慳utomated audit methodology in the market鈥攖hrough our own products and through deep partnerships with innovators our customers already trust.

That’s the idea behind our recent partnerships with , , , , , and . Together, we’re embedding PPC into AI鈥慸riven tools across We’re supporting AI-powered automation with , so firms can automate more work while staying grounded in the trusted methodology they already rely on.

Trullion: Methodology鈥�aware automation for financial statement review

Financial statement review is one of the most judgment鈥慽ntensive parts of the audit鈥攂ut many of the underlying procedures are repeatable. Our integration with Trullion brings AI鈥憂ative automation to financial statement review and testing, with full traceability back to PPC methodology and the relevant guidance at every step.

Artie Minson, CEO at Trullion, describes the shift: “This partnership signals a new era for audit automation and lays the foundation for trusted and truly agentic workflows. Our vertical AI solution is built for auditors by auditors, ensuring our outputs are within the framework of professional standards. This integration creates methodology-aware automation. Auditors can now focus their time on applying judgment to fully evidenced, agentic outputs, rather than searching for them, delivering audits with unmatched efficiency, accuracy, and quality.”

For us, “methodology鈥慳ware” is key: automation is valuable only when it operates within the same professional framework firms already use to define, document, and support their work.

Audit Sight: Substantive analytics that reduce testing

Substantive testing is another area where firms feel the strain. Even when technology is available, many teams still default to large samples and manual procedures.

As T.C. Whittaker, Co鈥慒ounder and CEO of Audit Sight, puts it: “Audit firms are seeking smarter ways to expand capacity and elevate quality without adding headcount. Bringing automated testing together with 成人VR视频’ PPC methodology 鈥� and enabling it through Guided Assurance 鈥� is the ultimate unlock for auditors. It transforms the audit plan itself, making it intelligent and dynamic by tailoring procedures, eliminating unnecessary tests, and reducing sample sizes based on automated evidence and client-specific risk. This partnership represents a shared vision to redefine how assurance is delivered in the modern era.”

Crunchafi: Automating lease procedures inside PPC

Lease accounting has become a complex, time鈥慶onsuming area for many firms. Too often, teams spend hours on calculations and reconciliations instead of higher鈥憊alue work.

By integrating Crunchafi into Guided Assurance, we bring seamless lease accounting automation directly into PPC鈥慴ased workflows, eliminating manual lease calculations and providing audit-ready journal entries, amortization schedules and footnote disclosures while preserving firms’ established methodology.

Mike Cooke, CRO at听Crunchafi, explains: “Audit teams want efficiency without sacrificing quality. By aligning听Crunchafi鈥檚 automation with the PPC Methodology, we鈥檙e giving firms a clearer, more reliable way to handle lease accounting from the start of the engagement to the final deliverable.”

This is the pattern we’re aiming for: automation that plugs into how firms already work, rather than asking them to start from scratch.

Fieldguide: Empowering Firms with Flexible Paths to Automate PPC Methodology

Many firms also want a more connected environment where methodology, evidence, and automation all live together. Our goal is to meet firms where they are 鈥� and give them options.

That is why we鈥檝e partnered with Fieldguide to embed Guided Assurance鈥攚hich delivers PPC methodology鈥攄irectly into Fieldguide’s professional鈥慻rade agentic AI platform. This creates a unified experience where trusted PPC content and intelligent automation collaborate to execute engagements efficiently and consistently.

Whether firms choose to automate audits with 成人VR视频 or Fieldguide, they can be confident they鈥檙e using the most trusted and automated methodology in the profession. This flexibility reflects our commitment to innovation and the unique needs of our customers.

Jin Chang, Co-Founder and CEO of Fieldguide says: 鈥淔irms are under pressure to do more with less. They need trusted methodology and AI agents that work the way they do. By embedding 成人VR视频 PPC methodology into our platform, we鈥檙e helping firms deliver higher quality work with more consistency and less effort. This partnership reflects a shared commitment to the future of the profession.鈥�

Validis: Data as the foundation for AI鈥�driven auditing

AI is only as good as the data behind it. For many firms, getting clean, audit鈥憆eady data from clients is one of the toughest operational challenges.

Through , our work with Validis focuses on solving that. Validis powers secure, on鈥慸emand ingestion of client trial balance, general ledger, and subledger data directly into Audit Intelligence. From there, we use AI and machine learning to focus testing on high鈥憆isk areas, segment populations by risk, and reduce the number of items to be tested, with anomaly detection automatically surfacing unusual items and generating the required documentation.

As Jeff Gramlich, Managing Director at Validis, explains: “We’re excited to collaborate with 成人VR视频, a true market leader and innovator, to deliver audit-ready data through our cutting-edge ingestion capabilities. This partnership provides auditors with the data breadth and granularity crucial for effective AI-driven auditing. By integrating our technology into the Audit Intelligence suite, we’re empowering auditors to conduct data-driven audits with enhanced efficiency and risk analysis, ultimately transforming the process to benefit both auditors and their clients.”

Valid8 Financial: Turning evidence gathering into an automated workflow

Finally, there’s the everyday work of matching samples to evidence and documenting that work in a way that stands up to inspection and peer review. This is some of the most manual and time鈥慶onsuming work in an audit.

, developed with Valid8 Financial, automates the matching and documentation of samples to supporting evidence, dynamically tracing accounting transactions to banking activity to confirm occurrence. It brings technology traditionally used in advisory, forensic, and financial crime work into an integrated audit workflow.

Brett Suchor, CEO of Valid8 Financial, says: “We built our technology to solve real problems auditors face every day 鈥� reducing the manual, time-consuming work of matching samples to evidence. Through our collaboration with 成人VR视频, we’re delivering a faster, more reliable testing experience to audit professionals across the industry.”

The future of Audit

In the next 3-5 years, we鈥檙e going to see big changes to the audit profession. Audit is moving decisively toward an automated, data-driven future. Using the right tools to increase efficiency and quality so teams can focus on higher risk areas and deliver better outcomes for clients is paramount.

In today鈥檚 environment, firms are being asked to do more with less, navigating tighter deadlines, increasing complexity, and growing client expectations. At 成人VR视频, we are bringing auditors advanced audit technologies, with our听newest audit solutions听increasing efficiency and accuracy.

We’ll keep investing in our own AI capabilities and in this partner ecosystem so firms can modernize at their own pace, on their own terms鈥攚ithout walking away from the methodology that has served them well for decades.

This post was authored by Dave Wyle, General Manager of Audit at 成人VR视频.

At TechCrunch Disrupt 2025, the buzzword wasn鈥檛 鈥淎I.鈥� It was scale. How do you take technology powerful enough to transform billion-dollar industries and make it trustworthy enough to run them?听

That鈥檚 the challenge 成人VR视频 has been solving in real time.听

At the Women of Disrupt Breakfast: From Vision to Velocity, Women Driving AI Innovation at Scale, Laura Safdie (Head of Legal Innovation, 成人VR视频, and former co-founder of Casetext) and Kirat Sekhon (Head of Engineering, 成人VR视频) joined Martine Paris, Forbes and BBC AI reporter, for a conversation on building agentic AI that doesn鈥檛 just assist professionals, but collaborates with them.听

From Startup Grit to Global Infrastructure听

Laura Safdie knows what it means to build from scratch. Before joining 成人VR视频, she co-founded Casetext, the legal AI startup that created CoCounsel, the world鈥檚 first GenAI legal assistant.听

鈥淲hen GPT-4 launched, we knew the ground had shifted,鈥� Laura said. 鈥淭he world, and our profession, would never be the same.鈥�听听

Within a week, Casetext rewrote its roadmap and shipped a working product that redefined legal work. Months later, 成人VR视频 acquired Casetext, turning that same startup innovation into the foundation for a professional-grade AI ecosystem now used across legal, tax, and corporate domains.听

Today, CoCounsel powers workflows for hundreds of thousands of professionals worldwide, combining the speed of machine learning with the rigor of human judgment.听

The Next Evolution: AI as the Junior Professional听

Forget chatbots. The next era of AI is here, and it looks a lot like your most capable new hire.听

In law, that means systems that can draft, review, and analyze complex documents with context and accuracy. In tax and accounting, it means interpreting new regulations, scanning data sets, and preparing the groundwork for filings at lightning speed.听

鈥淭he human is still the strategist,鈥� Kirat explained. 鈥淏ut the AI is that relentless team member who never tires, never loses focus, and helps you get to the insight faster.鈥�听

This isn鈥檛 automation. It鈥檚 augmentation. It鈥檚 about freeing people to do the creative, analytical, and human work that truly moves the needle.听

Why Trust Is the Killer Feature听

In high-stakes industries, accuracy isn鈥檛 optional. 鈥淐lose enough鈥� doesn鈥檛 cut it.听

That鈥檚 why trust has become the new measure of technical excellence. 成人VR视频 builds AI that shows its work, with authoritative citations, verifiable sources, and a full digital audit trail.听

Whether it鈥檚 a contract analysis or a tax interpretation, professionals can trace every step. Transparency isn鈥檛 an add-on; it鈥檚 the architecture.听

In a world where hallucinations can tank credibility, professional-grade AI earns trust one verified line at a time.听

Building Fast Without Breaking What Matters听

Innovation moves at a blistering pace. Models update weekly; frameworks shift overnight, and what鈥檚 state-of-the-art today can feel dated tomorrow.听

That鈥檚 why 成人VR视频 has engineered adaptive architecture. A flexible layer that lets teams integrate new large language models, swap them out, and test emerging capabilities with precision and control.听

Every model passes through a rigorous evaluation framework that measures accuracy, speed, and relevance. Engineers even collaborate directly with model developers, shaping future releases with real-world performance data.听

But speed isn鈥檛 just about shipping code. It鈥檚 about changing how people think and work. 鈥淭his is the most energizing moment in many people鈥檚 careers,鈥� Laura said. 鈥淏ut it takes a mindset shift. Change management is as important as the technology itself.鈥�听

Resilience as the Invisible Superpower听

When cloud providers falter or networks crash, professionals still expect their tools to perform. That鈥檚 why resilience is built into every layer of the 成人VR视频 AI stack.听

The company鈥檚 systems are multi-cloud and multi-model by default. If one model slows, another takes over. If a provider fails, others stay live. It鈥檚 a design built for continuity, transparency, and trust in motion.听

Reliability is no longer a technical metric. It鈥檚 a brand promise.听

The Human Edge听听

成人VR视频 is hiring AI engineers and data scientists who want to build the future of agentic systems. AI that collaborates, learns, and adapts alongside professionals.听

The goal isn鈥檛 to replace human expertise. It鈥檚 to elevate it.听

The future of professional work will belong to teams that combine computational intelligence with human judgment, creativity, and integrity. AI isn鈥檛 just transforming how we work; it鈥檚 transforming how we lead.听

The Takeaway听

The companies that win in this new era won鈥檛 just move fast. They鈥檒l build right.听

The next wave of AI innovation will be defined by systems that scale, teams that adapt, and leaders who build with trust and purpose.听

As Laura and Kirat reminded the audience at TechCrunch Disrupt, the goal isn鈥檛 just smarter technology. It鈥檚 a smarter, more human future for professionals everywhere.听

Why legal input is crucial

The law is a complex universe 鈥� each case requiring careful and thorough research, each document requiring specific language to ensure its validity and compliance. When lawyers leverage legal technology to find answers, assist with drafting, or carry out multi-step workflows, they need to feel confident that they鈥檙e not missing something. Many of the tasks we expect legal AI to perform involve a nuanced understanding of the law and its application, which is often anything but black-and-white. Without meticulous testing and grading by legal experts, the door is left open for costly mistakes. Take the for example. When testing various legal AI platforms against a human lawyer, 3 out of 4 platforms could not identify and extract contract language relating to a specified clause. The one that did? 成人VR视频 CoCounsel.

What this looks like in practice

成人VR视频 is deeply committed to using legal and subject matter experts when testing and grading the output of our legal AI.

For our developers working on AI for legal research, that means partnering with our licensed Westlaw attorney editors. Our editors help identify data that should be referenced for each skill, create standards by which to test the AI, conduct the AI testing, and evaluate and grade the output. Our attorney editors have conducted hundreds of evaluation sessions and graded thousands of responses to ensure that our AI-enhanced tools like CoCounsel meet accuracy standards, adhere to source documents, and apply logical reasoning that accounts for nuances in the law.

Similarly, our Practical Law attorney editors are integral in our development and improvement of agentic workflow capabilities in CoCounsel and beyond. Not only do our subject-matter experts create gold-data tests for our new agentic capabilities but also improve how we conduct human grading and output evaluation for autonomously performed complex, multi-step legal tasks.

CoCounsel鈥檚 outputs must meet complex criteria like factual accuracy and logical consistency, which aren鈥檛 easily judged with simple true-or-false tests. Evaluating legal content is also often subjective 鈥� some users prefer detailed summaries, others concise ones鈥攎aking automated assessments challenging. Enter our Trust Team. The Trust Team is a group of experienced legal professionals with backgrounds ranging from in-house counsel to law firms of every size. They create tests that represent actual work attorneys need to complete, set up the gold-standard response, and then run these tests against CoCounsel鈥檚 skills for automated evaluation. Using this process, CoCounsel鈥檚 skills have undergone over 1,000,000 tests, and any output that does not meet the attorneys鈥� standards is reviewed manually to ensure reliability.

Bringing it all together

The recent development and release of the CoCounsel workflow Draft a Discovery Request highlights the importance of collaboration between tech and legal expertise. It鈥檚 not enough to build an AI tool with the hope it might be useful to attorneys. You need actual lawyers to tell you what a specific workflow looks like now, what their pain points are, and how AI can alleviate those challenges.

When creating Draft a Discovery Request, the CoCounsel team relied on three separate teams of legal subject matter experts to guide the build: seven litigators from the Trust Team to create consistent automated and manual testing during development, an AI editorial team to provide process and grading input, and 13 Practical Law editors with litigation experience ranging from labor and employment to intellectual property law to review formatting, style, and the substantive output. During the testing and review process, the Practical Law editors noted that the skill output omitted several key definitions and neglected to include requests relating to interstate commerce issues and additional parties connected to the suit. Any one of these errors could result in confusion or an objection from opposing counsel, but careful editorial review allowed our CoCounsel team to adjust the output requirements and account for the necessary legal considerations and best practices. Without the review of the 20 legal subject matter experts working on this skill, these issues would not have been flagged because they were not technical errors, but substantive or procedural ones. Legal expertise and guidance were critical to verifying the accuracy of the workflow and ensuring this is AI lawyers will find useful and trustworthy.

AI that thinks like a lawyer

Having attorneys and legal subject matter experts provide guidance, develop test criteria, and evaluate legal AI is critical to providing a truly valuable tool for legal professionals. You can鈥檛 have AI that thinks like a lawyer if no lawyers are involved in the process. That鈥檚 why CoCounsel Legal is the AI lawyers swear by.

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Introduction听听

At 成人VR视频, we are redefining what it means to deliver professional-grade AI for the legal industry. More than 20,000 law firms, corporations, nonprofits, and government agencies worldwide rely on CoCounsel, our GenAI assistant, which transforms how legal professionals work by automating complex document review, contract analysis, drafting, and other time-intensive tasks with unprecedented speed and accuracy. That trust is earned through a comprehensive evaluation methodology that encompasses dataset rotation, automated testing, expert assessment, continuous monitoring, and strategic partnerships. This post focuses on one critical component of our broader testing framework: how our teams combine attorney expertise with large-scale automated testing through Scorecard, a proprietary evaluation platform originally developed by the engineers behind Waymo鈥檚 self-driving car testing infrastructure. While Scorecard represents just one pillar of our multi-layered approach, it exemplifies our commitment to proactive system optimization and continuous improvement. 听

Testing and Benchmarking with Scorecard听

Our teams of attorney subject matter experts (SMEs), machine learning experts, and engineers rely on a robust array of testing tools and methodologies, including human legal expertise, specialized testing software, expert prompt engineering, and continuous monitoring of test results. Rather than waiting for performance issues to emerge, we proactively identify and address potential challenges through systematic testing and optimization. When issues arise that may affect CoCounsel鈥檚 performance, these teams are equipped to mobilize a collaborative, rapid response effort, locating and remedying performance issues before they affect our customers.听听

A key tool is Scorecard, a specialized application that quantitatively evaluates CoCounsel responses against ideal responses created by our attorney SMEs. is the evaluation infrastructure for AI agents in legaltech, fintech, and compliance, and enables us to supplement our manual testing with large-scale, automated testing against our internal benchmarks. Built by the team behind Waymo’s self-driving evaluation infrastructure, Scorecard runs millions of agent simulations to help teams evaluate, optimize, and ship reliable AI agents faster.听

Performance issues typically arise from two distinct factors:
(1) the quality of user inputs, such as user prompts or queries, and documents; and,
(2) system limitations.

We address the first factor by providing customers with high-quality training, support, and tools鈥攊ncluding CoCounsel-created prompts, guided expert workflows, and agentic systems. In contrast, addressing the second factor requires recalibrating the system itself.听

Each CoCounsel skill is a precisely engineered legal tool, tailored on the backend to perform a specific legal task. Because we calibrate each skill to reliably extract information by leveraging the unique strengths of its underlying AI model, migrating a skill from one model to another often introduces performance issues that require recalibration. Such migrations may occur, for example, when a third party releases a new AI model with enhanced capabilities. To safeguard our customers, we conduct all migration and recalibration work within testing and staging environments before deploying any changes.听

Case Study: AI Model Migration of Review Documents Skill听

Large-Scale Testing Using Realistic Scenarios & Manual and Automated Review听

Jessica, an attorney SME on the CoCounsel AI Reliability Team鈥攁lso known as the Trust Team鈥攐versees the evaluation of CoCounsel鈥檚 Review Documents skill. In just minutes, the Review Documents skill can closely review and analyze large troves of legal information that would ordinarily require an attorney to spend hours or even days of manual review.听听

Jessica proactively monitors the upcoming migration of the Review Documents skill to a new AI model. This migration promises significant improvements in CoCounsel鈥檚 speed and accuracy. Working in a CoCounsel testing environment, Jessica manually reviews and evaluates the skill鈥檚 responses on the new model using a carefully curated 鈥渢estset鈥� of sample 鈥渢estcases鈥� that reflect real-world legal practice scenarios. Jessica checks CoCounsel鈥檚 response to each testcase user query against an ideal or 鈥済old-standard鈥� response that she has personally crafted using knowledge and expertise gained from years of experience as a real-world attorney.听听

Because each testset can contain several hundred testcases or more, reviewing each result would ordinarily be prohibitively time-consuming. However, Scorecard enables Jessica to supplement and scale the impact of her manual review by providing an extra layer of automated review.听听

Scorecard works by evaluating each response produced by CoCounsel and the AI model against the corresponding ideal response, then assigning the testcase a passing or failing numerical score using several criteria, such as the model鈥檚 ability to recall information, its precision, and its accuracy.听听

Reviewing the Scorecard results enables Jessica to compare the full testset鈥檚 scores on both models for the Review Documents skill. This means she can evaluate CoCounsel鈥檚 performance at scale much more efficiently.

Fig 1: Attorney SME manual review workflow.

Fig 2: Scorecard automated review workflow.

Reviewing the Scorecard data, Jessica quickly observes that on the new model, Scorecard consistently assigns failing scores to a specific testcase, assigning it a 1 out of 5 on all metrics. She identifies underperformance in other testcases, too; however, the other testcases still yield higher scores than the problem testcase. Recognizing the stakes are high, Jessica immediately begins troubleshooting the performance issue.

Troubleshooting

Jessica and her team of SMEs begin to troubleshoot by homing in on the problem testcase that Scorecard identified.

The testcase user query asks:

What medications is the patient currently taking? Please be specific with prescription names and dosages.

Analyzing CoCounsel鈥檚 outputs for the testcase, Jessica determines that on the new model, the Review Documents skill is failing to identify all medications for the patient consistently, causing a clear discrepancy with the ideal response. The new model occasionally includes all the relevant medications, but such inconsistent behavior does not meet the required standard.

[Click image to expand] Fig. 3: Scorecard screenshots of the AI model鈥檚 failing answer. As can be seen in the expanded 鈥渕odel response鈥� window above, the model was including medications that were no longer currently active and was failing to identify the only two current, active medications (Aspirin 81MG EC TAB and Aspirin 325MG EC TAB).

By digging deeper and examining the problem testcase response as well as some of the other, underperforming testcase responses, Jessica pinpoints the core issue as being the AI model鈥檚 ability to provide a sufficiently comprehensive level of detail. Since the model sometimes does output a complete response, Jessica observes, as a secondary concern, that the AI model struggles to produce consistent results.

Iterative Resolution & Continuous Improvement

Having identified the core issues, Jessica brings the issue to the CoCounsel engineering team for resolution. She describes the parameters of an ideal response and how the new model鈥檚 response fails to meet target metrics. This gives the engineers concrete goals, which they can use to modify the backend AI prompts. After each prompt change, Jessica evaluates a portion of the test set which is continuously updated, complemented by independent attorney reviews. Jessica and the engineering team continuously execute multiple rounds of prompt changes and use Scorecard to evaluate the results until the issue has completely resolved, and the new model is performing as expected. Scorecard now assigns the problem testcase a 4 out of 5 on all metrics, a good score鈥攊t reflects that the model has produced a valid response that captures all relevant substantive data points contained in the ideal response but may differ in more subtle ways, such as writing style or level of additional detail. Resolving this core issue ensures the secondary issue of inconsistent performance has been resolved as well. Jessica further conducts manual reviews of CoCounsel鈥檚 performance on the problem testcase.

These adjustments have cascading positive effects. When the problem testcase begins passing 99-100% of the time, the other testcases that had experienced the same issues (albeit less frequently) begin passing 100% of the time.

[Click image to expand] Fig 4: Scorecard screenshots of the AI model鈥檚 passing answer. This was achieved after multiple rounds of testing and prompting changes, which confirmed the engineers were able to pinpoint and fix the issue. As shown in the expanded 鈥渕odel response鈥� window above, the issue was ultimately fixed, and the model began answering this testcase correctly (as well as a few other testcases that had been failing, albeit less frequently, due to the same issue).

Once the model consistently returns results that meet TR鈥檚 expectations and are suitable for legal work, Jessica feels secure in the knowledge that the Review Documents skill meets necessary standards and can be released to customers.

Even after the skill is released on the new model, Jessica continues to run various Scorecard tests, multiple times daily to ensure consistency.

Fig 5: Continuous improvement process between attorney SME and engineers.

Observations

CoCounsel鈥檚 proactive and continuous iterative improvement process is painstaking but necessary. The problem testcase identified by Jessica using Scorecard provided a useful benchmark for improvement, because it failed more consistently than other testcases. Using a 鈥渓east common denominator鈥� testcase provided a measuring stick against which we could measure other testcases.

Using Scorecard allowed Jessica to extrapolate improvements from the single problem testcase to all other testcases, dramatically increasing the efficiency and speed with which she could iterate and improve CoCounsel鈥檚 performance across the board.

Conclusion

Innovation in AI is never 鈥渙ne and done.鈥� Models evolve, new risks emerge, and customer needs grow more complex. While this post has focused on Scorecard as one essential component of our testing infrastructure, it represents just one element of our comprehensive evaluation methodology. Our broader approach integrates dataset rotation, automated testing at scale, expert assessment from legal professionals like Jessica, continuous monitoring of live performance, and strategic partnerships with leading AI providers.

This multi-layered framework is what sets CoCounsel鈥檚 approach apart. By combining deep legal expertise with world-class technology infrastructure, we鈥檙e not only raising the standard for AI in professional fields, we鈥檙e defining it. Through proactive system optimization and evaluation approaches, CoCounsel continues to deliver the transformative professional-grade legal AI capabilities that tens of thousands of legal professionals depend on.

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About the Authors

Tyler Alexander is the Director of AI Reliability at 成人VR视频, where he leads a team of attorneys to ensure CoCounsel delivers trustworthy, professional-grade performance. He specializes in large-scale testing and benchmarking of AI systems for legal professionals.

Heather Nodler is a Lead CoCounsel AI Reliability Manager at 成人VR视频. With years of experience practicing law, they now apply their expertise to evaluating, calibrating, and continuously improving CoCounsel鈥檚 legal AI skills. Heather works closely with product and engineering teams to ensure that every CoCounsel feature meets the high standards required for real-world legal practice.

Redesigned drafting capabilities unify CoCounsel tools, content, expertise, and workflows

Informed by customer feedback, we’ve reimagined the legal drafting experience 鈥� making it more intuitive, intelligent, and seamlessly integrated. The drafting capabilities in CoCounsel fuse users鈥� institutional knowledge with trusted 成人VR视频 content and AI-powered technology to expedite the legal drafting process. The redesigned homepage puts everything users need right at their fingertips 鈥� CoCounsel Chat, skills, and powerful litigation and document analysis tools 鈥� all in one clean, intuitive space. Eliminating the need to jump between tabs or hunt for resources, it鈥檚 now an even smoother, faster experience that lets users stay focused, work smarter, and get more done with less friction.

Live Draft brings the ability to summarize and modify a document using natural language in Word. Live Draft also delivers contextual awareness of the document and understanding of the content and structure, so every suggestion and edit is tailored to the content. This helps to further reduce time spent producing a final draft, by delivering more accurate, relevant suggested changes.

Append Authorities enables users to combine all cited documents into a single file suitable for court use, reducing the risk of errors and increasing efficiency. Every cited document is linked for verification purposes, and a hyperlinked table of contents is included.

Region settings customizes CoCounsel tools for global legal professionals

The new region settings capability enables users to select their geographic preference from U.S., UK, Australia or Canada. Based on the selected region, region settings will automatically adjust tools and prompts in the CoCounsel Library making the work product more relevant. Users can now automatically tailor their documents using specific regional requirements, including for the UK and Australia, British English spelling variations, legal terminology, grammar, and content formats. Similarly, this will be coming soon for Canadian English. Additionally, CoCounsel Library is now available in the UK, Canada and Australia.

HighQ integrates CoCounsel AI for intuitive, conversational client data access

With听CoCounsel鈥檚 Search a Database skill embedded within HighQ, this customer-driven development allows clients the ability to pose queries regarding their data and receive summarized, highly relevant answers. Sourced from pre-approved content within their site, clients can quickly review summaries, generate reports, and make informed decisions without waiting for manual responses.

Legal Tracker adds AI-powered capabilities

Legal Tracker鈥檚 new AI features help users manage legal spend more efficiently. The AI-powered PDF-to-LEDES converter and invoice review speed up invoice evaluation and ensure accurate billing. An AI assistant also streamlines reporting and reduces manual data handling.

These transformative features reinforce our commitment to empowering legal professionals with the tools and solutions they need to excel. or to see firsthand how they elevate work to new heights.

To stay abreast of newly added features, monthly releases, and more, please sign up for the .

But what followed was less about innovation and more about disruption. Longstanding models like GPT-4o were pulled without warning. Familiar workflows broke. Performance felt inconsistent. Some users even said the model felt distant and robotic. Within days, OpenAI had rolled back several changes and re-enabled access to older models.

It wasn鈥檛 a failure of any one model or company but rather a failure of expectations. And it鈥檚 a reminder of a broader truth in the AI industry: even the most advanced systems can introduce friction if change outpaces the ability to adapt to it. As models evolve, so must the frameworks around them, especially in professional environments, where progress only matters if it delivers measurable, reliable benefits for the humans it鈥檚 meant to empower.

At 成人VR视频, we work with lawyers, tax advisors, and compliance professionals whose work leaves no room for guesswork. For them, consistency is not a preference鈥攊t鈥檚 a fundamental requirement for them to uphold their professional duty to their clients. That鈥檚 why we don鈥檛 chase upgrades for their own sake. And we certainly don鈥檛 ask our customers to pick which model they want to use. That鈥檚 our job. Our customers expect us to deliver a result they can trust, not a menu of models to experiment with. They want confidence, not complexity.

When we evaluate a new LLM, we do it through the lens of real-world use:

• • Can it reason over long documents with accuracy?
  • Can it explain its conclusions with transparent citations?
  • Will it behave consistently inside multi-agent workflows?
  • Does it integrate with how professionals already work?

If the answer is no, we don鈥檛 ship it鈥ntil we鈥檙e confident that we鈥檝e mitigated those concerns appropriately.

One example: earlier this year, our team benchmarked several leading LLMs for long-context performance. The task was to extract and apply insights from large, multi-thousand-word legal documents, a common need in law and compliance. We found significant variance. Some models struggled to maintain context or reference earlier sections accurately. Others returned plausible-sounding answers that fell apart under scrutiny. Rather than push forward with the best-performing model, we paused. We refined how our agents chunk and reason over large documents. We optimized prompts and guardrails. And we only moved forward when the system delivered answers that we鈥檇 be willing to stand behind in a courtroom.

This kind of work doesn鈥檛 show up in a product demo. But it鈥檚 what builds trust.

We also design our products to abstract that complexity away. In CoCounsel Legal and Deep Research, we use multi-agent systems to coordinate model selection, content access, and validation behind the scenes, so the user sees a transparent, explainable result, not a swirling mix of models and prompts.

Recent model rollouts offer an important reminder: in enterprise AI, newer isn鈥檛 always better. Progress should be measured not just by technical benchmarks, but by the clarity, consistency, and confidence it delivers to real users. The systems that will define the next chapter aren鈥檛 just the most advanced, they鈥檙e the ones that work reliably, integrate seamlessly, and build trust from day one.

The reality is, there will be more disruption. We are all moving fast because the potential of AI is enormous and the demand for it is real. But speed does not have to come at the expense of the hard-earned trust of our customers. The more we treat disruption not as a cost of innovation, but as a signal to improve our processes鈥攎odel governance, human oversight, testing frameworks鈥攖he better we will get at delivering AI that is not just powerful, but trustworthy. Over time, the industry will learn. We will see fewer rollbacks, clearer standards, and smarter integration. But that will only happen if we choose to build that way, with intention, transparency, and the end user in mind.

That鈥檚 the future we鈥檙e building toward. Not hype-proof. Trust-proof.