CEO https://xitter.cf/t.co/ThjDtdbWYR / Returning Time.
Los Angeles, CA
Joined April 2012
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This isn't just true of big companies.
Nobody knows what anyone actually does at work all day. Including the person doing the work it turns out.
Above Dunbar's number (150), the problem compounds.
By the end of your day, every client call is already a time entry, coded to the right NetSuite project and waiting for approval.
Laurel for NetSuite is now live on the Oracle NetSuite Marketplace.
Laurel captures your work across apps, meetings, documents, and messages. It matches each entry to the customer, project, and service item already in NetSuite. You review, edit, and approve. Only approved entries post to NetSuite, as standard time records ready to bill.
For firms that run on NetSuite, time feeds billing, project accounting, and every margin decision. When that time is rebuilt from memory at the end of the week, every number downstream carries the error.
NetSuite stays the system of record. Laurel makes sure the record is right.
Thank you to Folarin Okulaja and Mike Dixon on our team, and to Chad Zimmerman and the Oracle NetSuite team.
Learn more: suiteapp.com/Laurel-for-NetS…
Laurel and Legora are partnering to automate the recording of every piece of legal work done in Legora.
Because every stakeholder—the client, the lawyer, and the firm—needs to know the source of truth on what work is being performed in AI platforms.
And because you can only manage what you measure, we are teaming up to also quantify the exact client value that AI-performed legal work delivers.
Thank you to the @WeAreLegora team for helping us answer the most relevant question in Legal AI right now: what is my real ROI?
Last week we held our 8th Laurel Offsite in Chicago. It was the best yet.
The highlights:
• We opened with our origin story. The takeaway was that this moment is earned. The lessons we paid for along the way are why we're set up so well for the next phase.
• Darren Gold and Meredith Whipple Callahan, the best in the business, ran a masterclass on living out two of our values, Extreme Responsibility and Speed of Truth. #CultureAsAMoat
• Carol Rubin of Jenner & Block and Truda Chow of FBT Gibbons joined us for a COO panel. It turned into a lesson on what it takes to lead a firm through AI.
• The Second City put on a private improv show for us. We were in stitches.
• Kevin Cushing left no dry eye in the room when he talked about what he would have done with more time.
But the biggest highlight was looking around the room and seeing how much care, commitment, and love every Laureate has for our customers and our mission.
There's no metric for a week like last. But if you were in the room, you'd know without a shadow of a doubt that we are building something special.
A decade ago, I started dreaming about creating enough customer love to host a Customer conference.
Last week, the dream came true. More than 100 leaders across professional services, financial services, and tech came to New York for Proof, our first customer summit.
The customers in that room have entrusted us with $13.4B of revenues. Much more importantly, our partnership has returned 1.56 million hours to over 45,000 professionals across 70 countries.
That is 736 years of human time.
Returning time is personal for us. Once life teaches you that time is finite, you understand it is all that matters.
Proof was filled with people who understand that.
Meg Whitman reminded us that AI will change everything, and yet timeless principles, like working hard, being passionate, and delivering customer value, will always matter most.
@ariannahuff reminded us that AI makes "busy" the new stupid. We haven't stopped repeating it.
Charles Pickett of PwC showed how his team measures both the inputs and outputs of AI (quality, efficiency, speed to insight) to find its real ROI.
There is a lot of noise in AI right now. A lot of demos that don't work in production. A lot of AI spend disconnected from customer value. A lot of fundraises with splashy numbers.
Proof is the signal in AI.
The most incredible people in the world, connecting in real life, to build the future of work together.
That is being human in the age of AI.
Few days are dreams come true. Our inaugural Customer Summit was one of those days.
The last time a portco hosted at One Liberty Plaza in NYC, they were acquired for ~$1.7B soon after.
Complete coincidence, of course. It's a big city. (And to be clear, Laurel is not for sale)
Today @getlaurel is hosting its first conference, called Proof.
Laurel captures professional services work automatically at the source, so lawyers, accountants, and consultants stop reconstructing their week from memory. Firm leaders finally see where their time goes and where each matter earns or loses money.
The premise of Proof is simple: less theory, more receipts.
Leaders from PwC, EY, Freshfields, Reed Smith, Cozen O'Connor, and more are sharing how their AI rollouts actually went and what it means for how firms staff and bill.
Meg Whitman and @ariannahuff close out the day with a fireside chat.
Congrats to @ryanalshak & the Laurel team on this epic first one. I've already learned a ton.
You walk out of a meeting, tell your phone what happened, and the entry is done. Laurel identifies the client, calculates the time, and drafts the narrative before you reach the subway.
That was never possible on a phone. Mobile timekeeping meant a cramped timer and a keyboard too small to write a narrative on, so the work waited for the desktop. By Friday, half of it had faded.
Today we relaunched Laurel Mobile as an AI-native offering.
Describe your work out loud and Laurel turns it into a billable entry. Swipe captured work into your timesheet. Start, stop, and resume a timer from the lock screen. Review and release the full day from the back of an Uber.
Getting credit for your work dies in the gap between doing the work and recording it. Laurel Mobile closes that gap at the moment the work happens. Less time disappears. Less work gets rebuilt. More of the record reflects what you actually did.
Learn more: laurel.ai/blog/introducing-l…
Ryan Alshak retweeted
The new @getlaurel plugin for @ChatGPT is awesome. I’m setting up a weekly report for myself.
The lawyers we work with have no shortage of ambition. Their tools haven't kept up.
Today we're sharing the Laurel plugin for ChatGPT Enterprise. A lawyer can ask ChatGPT where their week went and find the work Laurel captured that never made it onto a timesheet, without logging into Laurel to go looking. It brings Laurel's record of work, captured at the source, together with ChatGPT's ability to question that record and act on it.
What I did not anticipate is what lawyers would do next with it. Build a weekly readout. Build an agent that flags which matters are eating the week. The work record becomes something they can build on, not just something they review.
Every lawyer has recorded less time than they worked. Until now there was no way to see the difference.
Thanks to our team and everyone at OpenAI who helped get us here.
Take a look: chatgpt.com/plugins
Only nine platforms had over half of the 500 firms surveyed using it:
•iManage AI Enrichment (91%).
•Ask iManage (80%).
•Claude (68%).
•Litera One / Lito (64%).
•NetDocuments’ ndMAX (58%).
•Clio’s Vincent AI (56%).
•ChatGPT (55%).
•Legora (51%).
•Laurel (51%).
Can't wait for next year.
From @BobAmbrogi citing an @ILTANet survey, the leader by a wide margin in AI solutions used law firms is Microsoft 365 Copilot, used by 76% of firms.
Second place was effectively a three-way tie between two of the leading legal AI products, Thomson Reuters CoCounsel (44%) and Harvey (43%), and one non-legal general AI product, Anthropic’s Claude (44%).
Legora came in much lower in the results, at 16%, behind products such as Lexis+AI (26%), ChatGPT Enterprise (22%), iManage (22%) and Litera One (17%).
Breaking that down by firm size shows interesting patterns. Among firms of fewer than 50 lawyers, Copilot retains its top position (59%), followed again by Claude (42%) and CoCounsel (40%), but Harvey drops to 22% and Legora to 6%.
At the other end of the size spectrum, among firms of 700 or more lawyers, the gap narrows between Copilot and Harvey, with Copilot seeing usage among 88% of firms and Harvey among 84%. But even among those large firms, Claude still gets 64% of usage, ahead of Legora (47%) and CoCounsel (43%).
Can’t forget that the vast majority of lawyers in the States practice alone or small firms.
lawnext.com/2026/09/which-ai…
"The war is a fight for the record. What doesn't commoditize: the record of what actually happened, and the ability to take responsibility for the outcome."
Vertical systems of record are about to get bigger. Horizontal tools are getting eaten.
Two years of AI hype produced noise. The actual market shape is clear: AI is the greatest expander of vertical software ever built, and the worst thing that ever happened to generic horizontal tools.
Most founders read this wrong. They think AI threatens their vertical business. It doesn't. It's the force multiplier that makes the system of record the most valuable asset in software.
The AI world collapses into three buckets:
Horizontal AI labs. A handful of companies own general intelligence and the interface. They'll absorb every generic workflow tool.
Headless. The rails. CRM, payments, scheduling, compliance. They process transactions but lose the relationship. Someone else owns the front door.
Vertical. Systems of record, vertical agents, AI-native services. This is where expansion happens.
The real fight is inside the vertical bucket. Three armies competing for the same territory:
1. The vertical SoR. Owns the record. Has distribution, trust, compliance. Weakness: thinks in seats, not outcomes.
2. The vertical agent. Fast, outcome-priced, trained on industry data. Weakness: no record. Rents commoditizing models.
3. The AI-native services firm. Sells outcomes, not software. Blends AI and human labor. Weakness: thin margins, replicable work.
The war is a fight for the record. What doesn't commoditize: the record of what actually happened, and the ability to take responsibility for the outcome.
Three endings: Absorption (SoR wins), Displacement (insurgent wins), or Fusion (record, assistant, service layer merge).
The tell: watch who accumulates the exceptions. Exception data is the training data for the next decade of vertical AI. Whoever owns it builds the moat.
AI Magazine ran a story last week on Laurel's partnership with Microsoft.
The story explains how Laurel tracks Microsoft Copilot adoption across a firm and ties it to profitability data, so leaders can see the return on Copilot deployment at the engagement level.
aimagazine.com/news/laurel-a…
Thanks to Daisy Hawker and the AI Magazine team.
#ILTACON2026 is in the books.
Two trends came up in every conversation.
AI is compressing billable work, but firms can't price AFAs accurately until they know their true cost of delivery.
AI providers are moving to consumption-based pricing, and you can't calculate ROI on those deployments without seeing the business before and after AI—and tracking what the AI actually did.
Both problems come back to source-of-truth data on time (input) and work (output). The firms that understand their own work will set the pricing standard and lead on AI transformation.
If you want the playbook the leading professional and financial services firms are using for both, join us at Proof this September.
Request to join here 👉 laurel.ai/proof
Every enterprise has an AI roadmap. Microsoft is on every one of them.
Almost no enterprise has a record of how its work is actually done. That gap is why AI deployments aren't delivering ROI.
Microsoft is the foundation of knowledge work. Laurel turns that work into a structured account of what happened, who did it, and how long it took.
Together, borrowing @satyanadella's framing, we are building the trust boundary for an enterprise's human and token capital to compound.
With that in mind, I am thrilled to announce our partnership with @Microsoft. Laurel is now live on the Microsoft Marketplace.
Three specifics for enterprises already running on Microsoft.
MACC eligibility. Laurel spend can apply against Azure budget already committed.
IP co-sell certification. Microsoft sellers covering regulated and knowledge-intensive industries can now bring Laurel into those enterprises.
Pegasus Program. Microsoft partners with fewer than 150 companies a year. Laurel is now one of them.
Laurel runs on Azure with SOC 2 Type II, ISO 42001, bring-your-own-key data control, and in-region storage.
An enterprise has to use frontier intelligence without giving up the knowledge that makes it unique. That is the reverse information paradox Satya wrote about, and it is what Microsoft and Laurel are solving together.
Find us on the Microsoft Marketplace, or reach out for a demo.
Knowledge work has never been measured.
For a hundred years, professional service firms have run on one data point, the hours a professional remembered to write down at the end of the week. Pricing, staffing, profitability, and client trust all sit on top of memory reconstructed after the fact.
Other knowledge industries (financial services, insurance, etc.) don't even have that data point. They track client outcomes well and have no idea what effort or cost went into producing them.
One of our customers deployed Laurel to 105 timekeepers for a quarter and compared them against 399 peers who kept using the market incumbent.
Each professional recovered 0.17 billable hours a day, about ten minutes. Projected across the firm, that is roughly $22M a year in real profit. And yes, the firm immediately started rolling out firmwide and we are now wall-to-wall across +1200 professionals.
Those hours are client work the firm was already doing and never captured. The non-client work surfaces too, which gives a firm its first honest look at where the rest of the day goes.
Three things follow from that:
-- Professionals stop spending 1-2 hours a week reconstructing their work. They confirm a record rather than write one, and that time goes back to clients or to their families.
-- Firms stop pricing from memory. Once you know what an engagement actually costs to deliver, alternative fee arrangements become possible.
-- And firms can finally measure AI ROI and audit their token spend. Most firms are spending heavily on AI with no baseline to measure it against. You cannot tell whether a tool saved a professional four hours a week if you never knew how the four hours were spent in the first place.
The lawyer-per-capita ratio in the US held flat from 1900 to 1970, through two world wars and the Depression. Then it doubled in 25 years.
Part of that is Laurel's demand curve. The rest is what happens when trust stops being self-enforcing and comes back priced.
Clients once paid a retainer to a firm they knew ("for services rendered"). When that trust failed, the meter arrived. In came itemized narratives, UTBMS/LEDES codes, outside counsel guidelines, e-billing vendors, billing audits, appeals.
None of it measures legal work better. It substitutes for a relationship that once held on its own.
A better meter is worth building. Full-accuracy capture, faster narratives, fewer write-offs. The harder job is making the work legible again, so a client can see what their firm did and why it cost what it cost.
Which is why the business of professional services suits AI better than the practice of it does.
"Of all our tech stack change, Laurel is the crown jewel. I love it. It's fantastic."
The crown jewel of enterprise AI isn't the model. It's understanding the work.
Coming soon: Laurel Billing.
One firm needed 210 emails between partners and billing to get a single bill out the door.
Most firms think the money they're missing is upside. New business they haven't won yet.
It's not. It's revenue they already earned, leaving the firm right now.
Bills that come back with cuts after a partner already spent a Sunday getting them right. Hours written off instead of billed.
Laurel Billing is how you keep what you've earned.
Early look at ILTACON 2026, before it's available anywhere else. Booth #327.
Learn more: laurel.ai/blog/coming-soon-l…
As Laurel continues to spread around the world, I got curious: How many countries are we being used in over the last 30 days?
The answer: 70.
Most: 🇺🇸 United States — six (and soon, seven) figures of active usage
Least: 🇱🇧 Lebanon — apparently my cousin keeps time
That means Laurel is now being used in 36% of the world’s countries.
Vanity metric? Of course.
Does seeing something that started in our head show up in 70 countries make us proud? Yes.