The top 7 startups from Y Combinator S’17 Demo Day 2

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The top 7 startups from Y Combinator S’17 Demo Day 2

Day 2 of YC S’17 brought us autonomous store checkout, cannabis genomics and at-home fertility testing. We whittled down the strong day of pitches to just seven hot companies. These are the startups our writers and the investors we spoke with were most excited about. If you want to check out the full list of startups from day 2 you can read about them here. 

Additional reporting by Ryan Lawler and Katie Roof.

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Modern Fertility – At-home test to check and monitor your fertility

Modern Fertility is selling home fertility tests for women to provide transparency at a fraction of the cost of traditional fertility clinics. Having launched just a week and a half ago, Modern Fertility has managed $70,000 worth of pre-orders and it expects each customer to test on a yearly basis. The company is currently selling direct to consumer but also sees potential in selling to businesses. Businesses like AngelList, Plaid and OpenDoor have expressed interest in sponsoring home fertility care for employees.

Why we picked it: Modern Fertility is undercutting the market in price and offering more tests than its competitors. At-home testing is a rapidly expanding space and fertility tests are one of the more common tests that are repeated in a regular cadence.

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Standard Cognition – AI-powered checkout in store

Standard Cognition is using machine vision to build the checkout of the future. Called autonomous checkout, the technology will allow shoppers to grab what they want and walk out of a store without having to go to a cashier. Standard Cognition believes it tech will enable those companies to save money and reduce theft.

Why we picked it: There are millions of other stores that are not Amazon that will still need technology upgrades for autonomous checkout. The space is huge and this quant-heavy team seems fit to capture some of it.

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Py – Teach coders new skills on mobile

Py is an app for teaching coders new skills. From Python to iOS development, they help software engineers learn and also match them with jobs. With a ranking system that can identify strengths in categories like data science and app development, Py believes that it will help job seekers demonstrate what they’re good at. With 100,000 monthly active users, Py hopes to make a dent in what it estimates is a $3 billion market opportunity.

Why we picked it: Online education hasn’t caught up with our mobile consumption habits. Programming is an ideal and growing market to focus on and the gamification of Py seems to be paying off, earning the startup healthy retention.

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Rev Genomics – Cannabis genomics company

Rev Genomics thinks that it can create the best marijuana with biotechnology. Using everything from CRISPR to genomic selection, the startup believes it has what it takes to make the “best cannabis in the world.” They are also targeting Botrytis, a fungus that can destroy cannabis crops. By “quantifying the gene expression levels of all 30,000 genes in the cannabis genome,” Rev Genomics says it will create plants with higher yields. The startup hopes to someday be the “Monsanto of Cannabis.”

Why we picked it: The cannabis market is exploding. Rev can help growers meet demand more efficiently and someday create new opportunities for high-margin specialty products.

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Dharma Labs – p2p lending on the blockchain

Dharma Labs is building what it calls the first “protocol for debt on blockchains.” Citing the popularity of ICOs, the startup believes there’s a “proven demand for cryptoassets that look and act much like equity.” So Dharma has built a mechanism for decentralized peer-to-peer lending. “Anyone in the world can borrow and anyone in the world can lend.”

Why we picked it: It’s still early days in the world of crypto, but if Dharma succeeds it could fundamentally disrupt, and reduce the costs associated with, the process of obtaining a line of credit.

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Quilt Data – Docker for data

Enterprises like to say they’re data-driven, but for many that data is a mess spread across the organization. Quilt wants to help businesses integrate their data sources to make sure everyone in the company is on the same page, and has already been adopted by some of the largest banks. By defining data “packages,” Quilt wants to become a sort of Docker for data, making it more discoverable and actionable across its clients.

Why we picked it: Packaging for data makes it easier to version when doing data science and machine learning. This is going to be critical as AI becomes more ubiquitous.

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Gameday – Fantasy sports app for everyone

Gameday thinks Draft Kings and FanDuel have completely ignored casual fantasy sports players. To fill that void, the startup is simplifying fantasy sports and integrating with Facebook Messenger. About 70 percent of the company’s 50,000 weekly active users are first-time players of fantasy sports, and 60 percent of them have continued to use Gameday over a 20-week period. Eventually, Gameday wants to grow to accommodate as many leagues as it can as it aims to grow the entire fantasy space.

Why we picked it: Retention is a big problem in fantasy sports. Gameday brings fantasy directly to the massive Messenger community with smart reminders.

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