This month, Opus 5.5 leads the @WeAreLegora BAR on overall quality, 6% above average. But overall rankings don’t tell the whole story. Muse Spark 1.3 ranks in the bottom half overall yet places high on review tasks. That’s exactly why the October update adds filtering by practice area, task family, and model: 30 practice areas, seven task families, 17 models. Filter by task family and you’ll see how models actually perform on the type of work you need done, not just where they land on average. Since launching the BAR, our Benchmark for Agentic Reasoning, we’ve kept testing the latest frontier models on tasks drawn from real-world cases, tracking what actually improves legal work as both the models and our harness evolve. Explore all results and the updated BAR: legora.com/bar/oct26

Today we’re launching @WeAreLegora's integration ecosystem. It covers 30+ tools across 9 integration types: document management, contracting, data rooms, eSignature and more. These are the systems legal teams use every day, and Legora now connects them. More of a lawyer’s work can happen in Legora, and the Agent can handle it end-to-end. Explore the ecosystem: legora.com/integrations

Today we’re launching Intake, the agentic legal front door for in-house teams. A better tool inside a broken process only helps lawyers move faster through the broken process. Requests still arrive incomplete. Routine work still eats senior time. And the General Counsel still can’t see what the team is working on. Intake fixes the front end. An ad-hoc request becomes tracked work in @WeAreLegora. The Legora Agent does the work and sends it back to the requester. A lawyer is accountable the whole way through. Available now: legora.com/product/intake

I was in the @etnshow studio in London last week. We got onto model strategy and which model is best for legal work. My answer is simple: there is no best model. Different models are good at different tasks, and the ranking moves every few weeks. That's why we've invested heavily in model routing and benchmarking, so the right model gets the right task. When a task comes up thousands of times and has a right answer, we post-train a smaller model to do just that. We don't want to build sandcastles that get washed away when the tide comes in. We want to build boats that rise with it. Thanks @lukeknight and @Ronanchamberss for having me.

Law is one of the most difficult places to put AI to work. The stakes are high, and lawyers have no patience for a tool that's only mostly right. If you can earn their trust, you've learned something every other industry will need. Looking forward to digging into that with @EricNewcomer and the other speakers at the @NewcomerMedia Cerebral Valley AI Summit on November 12 in San Francisco.

Today were launching Skills. Ask a lawyer why they rewrote an AI draft and you'll hear the same thing: It's not wrong. It's just not how we do it here. That's fair feedback. Every team and professional has their own way of working. How a review is structured. Which positions you'll give up, and in what order. How an email to a client should sound. Until now, the Agent didn't know any of that. A Skill teaches the @WeareLegora Agent how your team wants something done. You write it in plain language, the way you'd brief a new team member on their first day. After that, the Agent applies it whenever the work calls for it, dynamically. No more time wasted looking for the right workflow. Every firm and in-house team will leverage AI. The ones that pull ahead will be the ones whose AI works to their standards and can be used immediately. Legora's Skill system scales with versioning, permissions and the auditability required for the scale of the largest legal organizations globally. We're also launching the Skills Library with 250+ Skills built and tested by our legal engineers from leading law firms and organizations all over the world. They cover commercial contracts, privacy, M&A, litigation, employment, bank and finance, IP and more. Live today for every Legora customer: legora.com/skills

"Our customers are actually hiring more lawyers." Legora CEO Max Junestrand explains how large enterprises are using AI to support their in-house legal teams  bloom.bg/4AJTyCT

I was in the Bloomberg studio in London this morning. Q3 was the most hectic quarter in @WeareLegora's history. We added 800 new customers in three months and now work with more than 2,300 across 80+ countries. We also added more ARR this quarter than our total ARR at the end of 2025. I was asked the jobs question, and my answer hasn't changed: our customers are hiring more lawyers. Legal is supply constrained. If you could review every contract, you would. If you could run full diligence on every asset before it goes to investment committee, you would. Better tools mean more of that work gets done, and a lawyer still owns the judgment. We talked about junior lawyers wondering whether they need to learn to code. With large language models, the programming language is English. I'm not especially good with words. Lawyers are, and they turn out to be some of the best drivers of our product. I've said it before, and I'll say it again: I think this is the best time in history to be a lawyer. Thanks @TomMackenzieTV for having me on The Opening Trade. Full interview below.

Learning to be American

CODY FUCKIN BELLINGER THREE RUN BLAST!

Had a great conversation with @johncoogan and @jordihays on @tbpn last week about how we think about models at @WeAreLegora. If you break down legal work, there are many different skills you need to be good at: drafting, reviewing, fact checking, legal research, and so on. Different models are good at different things, and the frontier moves almost every week. So what’s interesting to us is where you apply which model, and when, to get the best outcome for our customers. That's the IP we've spent years getting good at. Post-training a model makes sense when we know it gives our customers better performance on a specialized task. Post-training for general intelligence, to get a small performance bump that won't last, doesn't. As a vertical AI company, you need to be positioned to benefit from all the R&D money being spent across the market. Thanks for having me on the show!

Last week, @WeAreLegora reached $200 million in annual recurring revenue (ARR). It took us 18 months to grow from $1 million to $100M ARR. It took us less than 6 months to double it to $200M ARR. To put that in perspective, we are on track to add more ARR this quarter alone than our entire ARR base at the end of 2025. Our positive gross margin improved while we did it. That is what makes the next double possible, and the one after that. The numbers behind the milestone are equally exciting. Our pilot win rate is 75 percent quarter to date, with improvement across every customer segment and geography. More than 40 percent of Q3 new business has come from in-house legal teams. The U.S. is now our largest market by revenue, and more than half of the AmLaw 50 are Legora customers. 130,000 lawyers now use Legora each month across 2,100 firms and legal teams in more than 80 countries. To our customers like @salesforce, @PaloAltoNtwks, @bakermckenzie, @WhiteCase, especially those who bet on us early, and to the entire Legora team, thank you.

Getting from $1M to $100M in ARR took us 18 months. The second hundred took less than six. Last week @WeAreLegora passed $200M. 130,000 lawyers now use Legora on a monthly basis, across 2,100 firms and legal teams in more than 80 countries. Two things from this year I would not have predicted: The first is how fast the US moved. 18 months ago we had no office in North America. Today over half of the AmLaw 50 work with us, out of our offices in New York, Denver, Chicago, Houston, San Francisco and Toronto. The US is our largest market by revenue. The second is where the demand is coming from. More than 40% of our new customers are now in-house legal teams, including Air Canada, Salesforce and Palo Alto Networks. Two thank-yous, before we get back to work. To our customers, who backed a small company from Stockholm with a lot to prove, and who still tell us plainly when we get something wrong. And to the team, engineers and lawyers sitting next to each other, who turn that into something better, faster than any group I have worked with.

There is no best model. There's a lot of noise about models right now. Who is training them, who owns them, where legal intelligence should live. One question actually matters: what produces the best outcome for the legal task in front of you? That's how we decide things at @WeareLegora. We optimize for the end-to-end outcome on a legal task. The model is one layer of that system, not the system. Models are uneven and the frontier changes almost weekly. One model plans a long job well, another runs deep analysis across thousands of documents. Some have to be told exactly what to do, and some are fine with a vague brief. They all break in different ways. So our lawyers write evals and we test them with the Legora BAR, our benchmark for agentic reasoning. Every model takes every test, and the model that wins gets the work. We post-train when we know it buys our customers better performance on a specialized task. Training is a tool we reach for when it helps, nothing more than that. The intelligence that compounds sits in the orchestration layer. Precedents, review standards, client requirements. That knowledge has to stay editable, auditable and portable. In our system, a changed review standard is an edit that takes effect the same day, with no new model training required. No lawyer should have to worry about which model did the work, any more than they think about which chip is in their laptop. They should only care about the quality of the work. That's what we are focused on. If you want the engineering version of this argument rather than the CEO version, our CPO, Bryan Tsao, and CTO, @jacsebl, take it apart in the video below.

Who owns the model? Where should a legal team's intelligence live? These questions are at the center of many conversations in legal AI, but we think the most important question to answer is: what produces the best outcome for every legal task? As CTO @jacsebl and CPO Bryan Tsao explain, there is no best model. Different models lead on different tasks, and the frontier changes almost weekly. At Legora, we use the best available model for each task, and invest in the system, where intelligence compounds and remains editable, auditable, and portable. We post-train when we know it delivers our customers better performance on a specialized task. Training is a tool, not a strategy. No lawyer should have to worry about which model did the work. Just whether the work holds up.

Working with @merritthummer, @Abby__Meyers and the whole @baincapVC team has been great. Congratulation on raising a new fund!

I first came to San Francisco when I was 15, with my dad. He is a programmer. To a teenager from a small island outside of Stockholm, this was the place where the future was being built. We walked into Salesforce East and stood there watching the enormous digital display of moving water. Outside, Salesforce Tower was starting to rise. I remember looking up and thinking it would be pretty sweet to have a tower someday. We are not there yet. What I could not have known is that I would be back years later, having dinner with @Benioff and welcoming @salesforce as a @WeAreLegora customer. Salesforce's Legal and Corporate Affairs organization will now use Legora across North America, EMEA and APAC. Their lawyers keep the judgment calls. We take care of the work around them. We have run on Slack since day one and became Salesforce customers when our sales team outgrew its first CRM, so it is good to have it run in the other direction too. Welcome to Legora, Salesforce. Dad, this one feels special.

For the first time, firms can build compounding engines of institutional knowledge. Those that succeed will become massively more valuable than those that don't.