Why legal AI connectors don't fix your missed call problem. Anthropic just announced new legal connectors that integrate Claude with platforms like Casetext and Westlaw. The legal tech press is excited. Enterprise law firms will probably find them useful. If you run a criminal defense, DUI, immigration, or personal injury practice, they won't help you sign more clients. These tools are built for document research and case management. They help large firms bill more efficiently. They don't solve the problem that actually costs small and mid-sized practices revenue: the prospect who calls at 7pm on a Tuesday, gets voicemail, and hires the first attorney who picks up. What anthropic's legal connectors actually do. The new integrations connect Claude to legal research databases and case management systems. Attorneys can query case law, analyse documents, and pull information from Westlaw or Casetext without leaving their workflow. This is useful if your bottleneck is research time. It's useful if you have associates billing hours on document review. It's useful if you're a large firm optimising internal efficiency. It does nothing for the small firm that just lost a $15,000 DUI retainer because no one answered the phone on Saturday morning. Big law and small law have different AI needs. Enterprise firms and small practices operate in completely different markets with completely different constraints. Big law firms optimise for billable efficiency. They have intake teams. They have marketing budgets that can afford to lose a few leads. Their AI needs centre on reducing research time, automating document review, and managing complex cases across multiple attorneys. Small and mid-sized criminal defense, DUI, immigration, and PI firms optimise for lead capture. You don't have a receptionist available 24/7. You can't afford to lose prospects to competitors who answer faster. Your revenue depends on converting inbound calls while the prospect is still on the line. These are fundamentally different problems. Enterprise AI tools solve the first one. They don't touch the second. The real ROI gap: missed calls. Most small law firms lose 30-40% of inbound calls outside business hours. Prospects don't leave voicemails. They call the next attorney on their search results. This is especially brutal in criminal defense and DUI work. Someone who just got arrested isn't comparison shopping. They're hiring whoever answers first. If your competitor picks up and you don't, that retainer is gone. Personal injury and immigration practices face the same dynamic. These are high-stress, time-sensitive situations. The prospect wants help now, not a callback on Monday morning. Legal research tools don't fix this. Case management integrations don't fix this. You can have the most efficient document workflow in your market and still lose half your inbound leads to missed calls. Voice AI solves the conversion problem. Voice AI agents answer every call instantly. They don't take weekends off. They don't miss calls during intake meetings or court appearances. A properly configured voice agent qualifies leads with the same intake questions your front desk would ask. It captures case details, urgency, and contact information. It routes hot prospects directly to an attorney while they're still engaged. This solves the actual bottleneck. You stop losing retainers to competitors who happened to answer faster. You capture leads at 11pm when someone searches for a DUI attorney after getting released. You turn missed calls into booked consultations. The ROI is immediate and measurable. Every retained client who would have gone to voicemail is revenue you weren't capturing before. Legal AI is fragmenting into two markets. The legal AI market is splitting into enterprise tools and small firm growth tools. Anthropic's connectors are firmly in the first category. They'll continue building features for large firms with complex research needs and big budgets. Small and mid-sized practices need different technology. You need tools that capture leads, qualify prospects, and get retainers signed. You need AI that solves for revenue growth, not billable efficiency. Knowing which category solves your actual problem determines whether you waste budget on impressive-sounding technology that doesn't move the needle, or invest in automation that directly increases retainers. If your bottleneck is document review time, enterprise tools might make sense. If your bottleneck is missed calls and lost leads, you need voice AI that answers the phone. Stop losing retainers to voicemail. Legal AI will keep advancing. Research tools will get better. Case management will get smarter. Large firms will buy expensive integrations that optimise their workflows. None of that helps you if prospects are calling your competitors instead of you. The small firms winning right now are the ones solving lead capture first. They answer every call. They qualify every prospect. They turn inbound interest into booked consultations before the prospect moves on. That's the AI investment that actually grows revenue.

LawNext on Location: the view from Tiburon - A conversation with Pablo Arredondo, Casetext cofounder. - February 24, 2026 Why it matters. The acquisition validates AI's transformative potential in legal services, and CoCounsel's rapid use-case expansion signals a shift toward AI-driven workflow automation across the profession. Key takeaways. * - Casetext launched CoCounsel, GPT-4 AI legal assistant * - Thomson Reuters acquired Casetext for $650 million cash * - CoCounsel identified 74 distinct legal use cases quickly * - Founder now left TR, focusing on personal projects * - Reasoning and agentic AI seen as next breakthrough Pulse analysis. The legal technology landscape has been reshaped by a series of incremental experiments, from crowdsourced research platforms to narrow-purpose analysis tools. Casetext, founded by Pablo Arredondo and Jake Heller, spent a decade iterating on these concepts before securing an early-access license with OpenAI that granted them GPT-4 ten weeks ahead of the public ChatGPT rollout. That early partnership allowed the team to embed a large language model directly into their product suite, laying the groundwork for what would become the first GPT-4-powered AI legal assistant. When CoCounsel debuted on the nationally televised Morning Joe program in March 2023, it instantly demonstrated the scalability of AI in everyday legal work. Within the first 48 hours the founders catalogued 74 separate use cases, ranging from contract review to brief drafting, proving that a single model could replace multiple legacy tools. The rapid validation prompted Thomson Reuters to acquire Casetext for $650 million in cash, a deal that underscored the strategic value of AI-enhanced research platforms for large information providers and signaled broader industry consolidation around generative technology. Looking ahead, Arredondo argues that the next wave will move beyond text generation toward reasoning and agentic AI, where models can autonomously plan, execute, and adapt legal strategies. Competitors such as Anthropic, Google, and emerging specialist firms like Harvey are already training foundation models tailored to jurisprudence, raising the bar for accuracy and compliance. For law firms and corporate legal departments, these advances promise end-to-end automation of routine tasks and smarter decision support, but they also raise ethical questions about accountability and data privacy that the industry must address. Bob Ambrogi As I continue my LawNext on Location series - all recorded live in the San Francisco area at locations of each guest's choosing - he sits down with Pablo Arredondo at his home in Tiburon, a quaint Marin County town with a history stretching from Mexican land grants to naval outposts to a southern railway terminus. From Pablo's home office, the view looks out over Richardson Bay towards Sausalito and, if you look carefully, the Golden Gate Bridge can be seen in the distance. It is a setting that is entirely fitting for a conversation with someone who helped shape one of the more remarkable journeys in the annals of legal technology. (My apologies for the video quality. A videographer, I'm not.) Pablo was co-founder of Casetext, the once-scrappy startup that spent a decade iterating, pivoting and persisting before striking gold with CoCounsel, the first GPT-4-powered AI legal assistant, unveiled on the nationally televised Morning Joe show on March 1, 2023. Just four months later, Thomson Reuters acquired Casetext for $650 million in cash. Now, 2.5 years later, Pablo recently left TR, where he is, as he puts it, building a Lego Death Star with his daughter and finally paying attention to his well-being after 16 years of nonstop pursuit. In this wide-ranging conversation, Pablo reflects on the long road to CoCounsel - from a failed crowdsourcing experiment to CARA's brief analysis tool to the pivotal moment when Casetext signed a $20,000 innovation license with OpenAI and got early access to GPT-4, 10 weeks before ChatGPT's public launch. He describes the surreal experience of those first 48 hours after CoCounsel's debut, when he and co-founder Jake Heller identified 74 distinct legal use cases the tool could handle - any one of which, he says, "would have been a company in the old world." Pablo and I also dig into the bigger questions surrounding legal AI, including whether the field is advancing as fast as he expected; what the foundation models from Anthropic, OpenAI and Google mean for legal-specific AI companies such as Harvey; and why he believes reasoning models and agentic AI represent the next genuinely profound leap beyond GPT-4. Pablo also candidly reflects on the TR acquisition and his work while at TR, and he offers hints on what may lie ahead for him - at least once that Death Star model is done. It is a conversation that is part memoir, part technology seminar and part meditation on what it means to have built something that changed a profession - and his life - all recorded with a sweeping, albeit cloudy, view of the majesty of San Francisco Bay.