Alum Q&A: Tower discusses their Y Combinator and UWaterloo experience

Monday, May 27, 2024

Tower, a startup with unique ties to the University of Waterloo, is revolutionizing the legal space.

Using the power of AI, they are helping in-house counsels triage and handle incoming legal requests automatically. Their company, which was founded in 2024, is further bolstered with recent seed funding from the Y Combinator (YC).

YC is one of the world’s biggest and most prestigious startup accelerators. It is responsible for the launch of Airbnb, Twitch, and Reddit. Each startup receives $500,000 in funding and other resources such as networking sessions, alumni talks and mentorship, particularly on finance, public relations, or product design.

Entry to the program is extremely competitive. The latest cohort, Winter 2024, had an acceptance rate of less than one per cent, among 27,000 applications. Yet, Tower was selected, joining 11 other startups founded by former and current students at the University of Waterloo.

 CEO Adam Dorfman (left) and CTO Andy Zhang (right)

Tower's co-founders CEO Adam Dorfman (left) and CTO Andy Zhang (right) are Faculty of Mathematics alumni

Tower’s co-founders include CEO Adam Dorfman (BMath ’23) and CTO Andy Zhang (BCS '21). They are both graduates of the University of Waterloo’s Faculty of Mathematics. Adam studied Mathematical Physics while Andy was in Waterloo and Wilfrid Laurier University’s Business and Computer Science Double Degree Program.

We recently connected with Adam and Andy to discuss their company, future goals, and their experience with YC and the University of Waterloo.  

How would you describe your company?

Tower is building an AI assistant for in-house legal counsels. We are building software that first helps lawyers manage their influx of work via an intake, matter, and document management solution, and then automatically completes burdensome tasks using our AI assistant.

A lot of companies in the legal-tech space are looking at how to replace lawyers with AI, but we don’t see that happening any time soon. We’re working on how to help lawyers leverage AI automation to become 10x more efficient.

What issues is your company trying to resolve?

Legal is a core need for businesses to operate. However, businesses are cost-sensitive and legal is a cost-center. Over the last 20 years, companies have been moving legal functions in-house to reduce costs, which has resulted in in-house legal headcount growing at five times the pace of private practice firms.

We’re working on helping in-house teams operate more efficiently and automate time-consuming, burdensome tasks that detract from their substantive work. Every day, counsels are spending 30 to 70 per cent of their time handling ad-hoc requests. Things like finding contracts deep in drives, triaging internal and external requests, and answering questions – we’re working on automating these processes with AI (of course with legal review & approval).

Our goal is to make in-house teams operate more efficiently and more smoothly. We want to amplify the efficiency of your legal team tenfold.

How do you feel about being a recipient? 

Honestly, we’re super proud and grateful for the opportunity to have been part of the latest YC batch. YC shares so much knowledge that is essential to first-time founders. The group partners give you so much incredibly valuable advice and stop you from going down a lot of rabbit holes.

In addition, being surrounded by a community of top-tier founders is invaluable– people are always willing to help you ideate & solve problems and push you to be the best version of yourself. Going through YC is among the most stressful and rewarding experiences one can go through. I hope to see more Waterloo alumni going through this!

How will your startup use this funding? Any next steps?  

We’re using the YC funding as functionally a pre-seed round (as do most YC startups). We will build out our core offering and work closely with our customers to develop the best tools for them. AI in legal is a space with a lot of technical complexity, so we’re iterating a lot on our AI pipelines to develop tools that are both high quality and deliver value to lawyers.

How did your education and experience at UWaterloo prepare you for your career, particularly in founding and managing your startup?

I think that the intensity of Waterloo really prepares you to work hard and dedicate yourself 100% to things. You also meet a ton of incredibly bright people in Waterloo– genuinely some of the smartest, hardest working, and most innovative people I know. Many of our close friends from undergrad went on to become founders (Ruslan Nikolaev and Griffin Keglevich of Float, Tony Cai and Matt Black of Atomic.Finance). Having a community of founders where you can share ideas, best practices, and connections has been incredibly important. I also think the co-op program is hands down the best way to get real work experience and learn about real problems in the industry as a student.

What did you like most about being a student at UWaterloo?

The best part of Waterloo is hands down the network. Having a group of insanely smart, high-achieving alumni is unparalleled. I really believe that you become most like the 10 people you’re closest with, so being surrounded by the really talented people at Waterloo drives you to be the best and hardest-working version of yourself. Also being chased by rabid geese really builds resiliency and cardiovascular health– there’s no stress like hearing the ear-piercing honk of the militant geese.

  1. 2024 (66)
    1. July (9)
    2. June (11)
    3. May (15)
    4. April (9)
    5. March (13)
    6. February (1)
    7. January (8)
  2. 2023 (70)
    1. December (6)
    2. November (7)
    3. October (7)
    4. September (2)
    5. August (3)
    6. July (7)
    7. June (8)
    8. May (9)
    9. April (6)
    10. March (7)
    11. February (4)
    12. January (4)
  3. 2022 (63)
    1. December (2)
    2. November (7)
    3. October (6)
    4. September (6)
    5. August (1)
    6. July (3)
    7. June (7)
    8. May (8)
    9. April (7)
    10. March (6)
    11. February (6)
    12. January (4)
  4. 2021 (64)
  5. 2020 (73)
  6. 2019 (90)
  7. 2018 (82)
  8. 2017 (51)
  9. 2016 (27)
  10. 2015 (41)
  11. 2014 (32)
  12. 2013 (46)
  13. 2012 (17)
  14. 2011 (20)