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Y Combinator is renowned in Silicon Valley for a lot of reasons, but there’s one service that has quietly become one of its most powerful: an online founder-matching tool.
“I think this is the most valuable digital product that YC has built (i.e. more valuable than Bookface, etc,). It’s astonishing how many founders I meet who met each other on the YC co-founder matching platform,” tweeted seed investor Nikhil Basu Trivedi. (Bookface refers to YC’s famed online collection of how-to startup advice for its program participants.)
Recent Y Combinator grad Hona is an example, although its founders’ meet-cute story is a bit more exciting than just using that tool.
Hona is a GenAI medical records startup. It integrates into multiple electronic records systems and then summarizes a patient’s medical records, helping doctors prep for the patient’s visit.
It was initially founded by two friends who have known each other since middle school, Danielle Yoesep and Adam Steinle. They reconnected after graduating college and respective early careers in tech and biotech. Steinle had been a biomedical engineer, Goldman banker, and big tech product manager at Facebook. Yoesep was a scientist for a biotech startup that had just been acquired. They were hanging out with their high school friends while home for Thanksgiving, chatting about wanting to do a startup when the idea for Hona arose. While neither of them were doctors themselves, both had family members who were doctors or in healthcare and they soon settled on an idea: AI to assist doctors with patient data summaries.
They knew they needed an AI specialist co-founder, so signed up on the Y Combinator Co‑Founder Matching Platform. They found one in Shuying Zhang, who also knew she wanted to do a startup, something in healthcare and AI, and had signed up on the service. Zhang’s background combined biomedical engineering and software development, most recently working on AI at Google, and she was at Amazon prior to that.
What came next was a process that sounds a bit like Tinder for co-founders.
Yoesep and Steinle swiped through profiles in the matching tool as did Zhang. Each of them held several meet-and-greets with potential co-founders. When Zhang met with Yoesep and Steinle, they instantly clicked so well, that the long-time friends offered Zhang a full one-third share of the company.
“We literally met each other and like three weeks later, we’re jobless, trying to build this,” Steinle told TechCrunch.
Having met on Y Combinator, with their backgrounds in tech, they were exactly the type of startup sure to be accepted into the competitive program. They immediately applied to YC for the Summer 2023 batch.
And they were promptly rejected.
So they got to work on their own, building a prototype, showing it to their network of doctors, earning solid reviews, and raising a small seed round.
About four months later, they applied to YC again for the winter 2024 batch, and were accepted. One of the reasons they got in the second time, Yoesep recalled, was that they never changed directions, or never pivoted, to use the hackneyed Silicon Valley term. Another reason was “because of our dynamic during our interview, showing that we had grown close and enjoyed working together,” she said.
Things started cooking for them after that. Medical doctors at Duke and Harvard agreed to test the product and write a white paper, due to publish later this month. Some angels who were known in the tech and biotech worlds invested. And by the time Hona graduated from YC and did its famed Demo Day, it had already raised a $3 million seed round from General Catalyst (which is pursuing healthtech so seriously it bought a hospital system), Samsung, Rebel Fund (founded by Reddit co-founder Steve Huffman and Cruise co-founder Daniel Kan) and 1984 Ventures.
Hona still has a tough road ahead. AI for medical transcription is an increasingly crowded field. Big cloud providers like Google and Amazon are offering such tools and dozens of startups are tackling it, too.
But Steinle says that Hona will compete because it’s “super customizable” to search through medical records for the specific data a particular doctor needs prior to seeing a patient. A cardiologist would get a different summary than a nephrologist. For instance, the upcoming white paper is on kidney stone referrals, so “so we’re pulling stuff like how many millimeters was the stone on the right here?” Steinle describes.
As for Zhang, her advice for others who dream of doing a startup, and are considering using YC’s matching tool, is to “just go out and try,” she says. “Once you start working with people, you will quickly have a good sense whether you get along. You will know right away.”
Tim Goltser and Curtis Mason have been building things together since high school, when the two were the co-captains of their school’s robotics team. In college, Goltser and Mason teamed up to create an app — Hang, for scheduling hangouts with friends — with Sean Doherty, who Mason had met while an undergrad at Boston University.
Fast forward to 2022, and Goltser and Mason — along with Doherty — felt the entrepreneurial itch strike again. After considering a few ideas, they decided to go after what they saw as a largely unaddressed market: Tools to help small businesses secure U.S. government contracts.
“The federal contracting community has seen a shrinking of the small business industrial base for much of the past decade,” Doherty told TechCrunch. “It’s hard for these companies to compete against giants like Lockheed Martin or Northrop Grumman. It’s also expensive for them to bid on contracts — if they don’t win, they may run out of cash.”
As a result of labyrinthine systems and mountains of paperwork, finding and bidding for U.S. federal contracts is a laborious process. It takes weeks at a minimum to complete, according to Doherty — and often the best-resourced companies are the most successful.
In a 2023 survey from Setscale, a purchase order financing startup, small business owners cited insufficient cash flow and working capital — and a lack of time and resources — as their top roadblocks to securing government contracts.
To attempt to give these small businesses a boost, Goltser, Mason and Doherty founded GovDash, a platform that provides workflows to support government contract capture, proposal, development and management processes. GovDash was accepted to Y Combinator in 2022; Goltser dropped out of college to help spearhead it.
GovDash is essentially a contract proposal generator. The platform automatically finds contracts possibly relevant to a business, reads through the requests for proposals and — leveraging generative AI — writes proposals
GovDash can trawl through solicitation documents to identify requirements, requested formats, evaluation factors and submission schedules for contracts, Doherty says. It can also identify contracts a business might be qualified for based on their past performance, sending alerts to the inbox of a customer’s choosing, according to Doherty.
“When a contractor wants to respond to a government solicitation, they can run that through GovDash to produce a proposal in a fraction of the time,” Doherty said.
Now, generative AI makes mistakes. It’s a well-established fact. So why should businesses expect GovDash to be any different?
Two reasons, argues Doherty.
One, GovDash built a system that cross-checks a businesses’ info to see just how relevant the business is to a given federal contract. If the relevancy — as judged by the system — isn’t obvious, GovDash prompts the business to template out sections of the contract proposal with more information.
GovDash’s platform tries to automate many of the more tedious aspects of going after — and securing — U.S. federal contracts.
Two, GovDash involves heavy human review. At each stage of the proposal-generating process, the platform checks in with a human reviewer to get their seal of approval.
These steps — cross-checking and human review — aren’t infallible, Doherty admits. But he claims they’re better than what a lot of the competition’s doing.
“Companies now have one place where their business development data flows seamlessly, with an AI agent at its core to automate tedious workflows,” Doherty said. “This is a huge win for the C-suite as they can get out more proposals, at a higher quality level, in a fraction of the time, and put all the associated workflows on autopilot.”
GovDash’s competition is growing — and quickly.
GovDash competes with Govly, whose platform lets companies assess, search and analyze government contracting requirements across disparate sources. A more recent rival, Hazel, aims to use AI to automate government contracting discovery, drafting and compliance. Both — like GovDash — are Y Combinator-backed, interestingly.
But Doherty claims that GovDash is positioned well for expansion.
Having raised $12 million from investors including Northzone and Y Combinator, inclusive of a $10 million Series A funding tranche this month, GovDash plans to grow its engineering team, hire additional federal proposal managers to guide its product efforts and add new capabilities to its existing platform.
New York-based, six-employee GovDash currently works with around 30 federal contractors across the U.S., Doherty said, and is “nearly” cash-flow positive.
“We’re building for the long term for our customer base,” Doherty said. “[We’re] well-capitalized for eventual market tailwinds.”
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