TamLabs Thinks AI Can Redesign Knowledge Work and They're Starting with Professional Services

The Macro: Professional Services Firms Are Drowning in Busywork

Professional services is a $6 trillion global industry that runs on smart people doing repetitive things. Consultants rebuild the same market sizing models. Lawyers review thousands of documents looking for the same clause patterns. Analysts at PE firms pull the same financial data into the same templates for every new deal.

The tools these firms use haven’t changed much in twenty years. Excel. PowerPoint. Word. Maybe Tableau if someone on the team went to a conference. The entire industry is built around billing hours, which creates a structural disincentive to adopt technology that makes work faster. If your revenue model depends on people spending time on tasks, tools that eliminate tasks are a threat, not an opportunity.

But that’s changing. Not because firms suddenly got enlightened about efficiency, but because clients started pushing back on bills. Corporate legal departments are demanding alternative fee arrangements. PE firms want faster diligence timelines. Management consulting clients want deliverables in weeks, not months. The pressure to do more with fewer billable hours is coming from the buy side, and it’s real.

The AI tooling that’s emerged so far for professional services falls into two camps. The first is horizontal. Tools like Copilot, ChatGPT, and various summarization products that work across industries but don’t understand the specific workflows of a law firm or an investment bank. The second is deep vertical. Products built for a single use case, like contract review or financial modeling, that do one thing well but don’t connect to anything else.

There’s a gap between those two camps, and that’s where TamLabs is trying to build.

The Micro: Brothers, Blackstone, and the Applied Research Angle

Joshua and Ben Doolan are brothers, which is either a great co-founder dynamic or a terrible one, and there doesn’t seem to be much middle ground. They launched TamLabs through Y Combinator’s W25 batch.

Joshua is the CEO. He was previously at Blackstone doing data science, where he deployed AI solutions across the private equity portfolio and led data science diligence for PE acquisitions. He did his AB and SM at Harvard in computer science with a focus on AI. Ben is the COO. He was a consumer PE data scientist at L Catterton, then a PE consultant at EY-Parthenon, and before that a lobbyist and policy analyst in DC at Brownstein. He studied physics, classics, and data science at Georgetown.

What strikes me about this team is the combination of technical depth and genuine domain experience. They didn’t read about private equity in a textbook. They sat in the rooms where diligence decisions get made. They know what the workflow actually looks like at 2 AM before a deal committee meeting. That kind of embedded knowledge is hard to replicate and even harder to hire for.

TamLabs describes itself as “an applied research lab redesigning how knowledge work gets done.” The website is minimal right now, essentially a landing page with a logo animation and a contact email. That’s not unusual for a company at this stage, especially one coming out of a YC batch. The product is likely in private beta or being built in close collaboration with early design partners.

The tags on their YC profile tell a story: AI, Finance, Productivity, Legal, AI Assistant. That’s a broad surface area, but it maps to the professional services verticals where the Doolan brothers have direct experience. Finance and legal are the two professional services categories where the pain of manual knowledge work is most acute and the willingness to pay for solutions is highest.

The “applied research lab” framing is deliberate and worth paying attention to. It signals that they’re building foundational capabilities, not just wrapping an API around GPT-4 and calling it a product. Whether that research focus translates into defensible technology or just delays time-to-market is the open question.

The Verdict

TamLabs is early. Very early. The website is a landing page. The product details are thin. The team is two people.

But the founders have exactly the right background for this problem space, and the timing is strong. Professional services firms are under real pressure to adopt AI, and the current tooling options are either too generic or too narrow.

At 30 days, I’d want to know what their first product actually does. Is it a diligence acceleration tool for PE? A document intelligence platform for legal? Something else entirely? The “applied research lab” positioning gives them room to explore, but eventually they need to ship something specific.

At 60 days, the question is design partners. Who are the first firms using this, and what workflow does it replace? The best professional services AI companies I’ve seen get adopted when a specific team at a specific firm says “this saved me four hours on a deal.” Not when a CTO reads a whitepaper.

At 90 days, I’d be watching for signs that the “research lab” identity is a strength rather than a distraction. Companies that stay in research mode too long get lapped by competitors who ship faster with messier code. The Doolan brothers seem practical enough to avoid that trap, but it’s worth watching.

The professional services AI market is going to be enormous. The question is whether TamLabs can carve out a meaningful position in it before the space gets crowded. I think the founding team gives them a real shot.