We put together a list of the top YC companies by valuation as of October 2018. You can see that list at https://ycombinator.com/topcompanies.

Here’s a Q&A with Jason Tan, Cofounder of Sift Science, one of the companies featured on the list.

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What does Sift Science make/do?
Our SaaS platform enables digital trust and safety at scale. Online businesses use our real-time machine learning system to accurately and quickly assess customer risk so that they can provide safe and simple experiences.

How many employees does Sift Science have?
174 across our SF and Seattle offices.

How many founders?
Two founders.

What is your most impressive recent product milestone?
We currently ingest and classify more than 35 billion user events per month across the 16,000 sites that use Sift, up from 18 billion events per month a year ago. These events fuel the effectiveness of our machine learning systems.

What is the larger impact / societal impact of your product in the space you work within?
Trust is the foundational currency of any interaction in the real world. As everything moves online, decisions around who to trust must be made with unprecedented accuracy, reliability, and speed. Our digital trust and safety platform reduces risk and friction around any online transaction, message, login, account creation, etc.

What’s an interesting element of Sift Science’s company culture?
People rave about our onboarding – that it’s easy to grab time with anyone at the company and everyone is eager to help the new hire.

Looking back, what motivated you to start Sift Science?
Life is short. If you’re spending 8 – 12 hours at the office, spend it with people who you really enjoy learning from, solving tough problems with, and having fun with. Selfishly, starting a company gave me control over company culture and who I get to work with. 😉

As for what we do – we believed that machine learning would disrupt a lot of industries. We surveyed friends’ companies about top challenges they’d outsource. Fraud was frequently mentioned. We didn’t know anything about fraud, but as we dug in it was obvious that status quo solutions were primarily rules-based systems that were highly reactive, expensive, and unscalable. We recognized an opportunity to democratize the real-time machine learning solutions that Google, Amazon, Facebook, etc. use internally to protect against bad actors.

Is what you’re working on now the original idea or did you pivot?
Original idea – just now expanded beyond credit card fraud to be a more holistic digital trust and safety platform that also protects against spam, fake accounts, and account takeover.

What’s one piece of advice you’d share with a young founder?
Take a hard look in the mirror and embrace that you’re imperfect. You’re a better leader when you really know yourself; what pushes your buttons, how you best show up, etc. Work with a therapist and/or executive coach early and often. Enjoy the challenge and fulfillment of self-improvement and hire a team around you that complements your weaknesses.