How CoffeeSpace Powers Its Tinder-Like Cofounder Matching App with Proxycurl

We at Proxycurl have had the privilege of speaking with Hazim, the CEO and co-founder of CoffeeSpace, a Tinder/Hinge-like platform for co-founder matching.

Intrigued? We’re here to tell you all about it: its origins, core idea and features, challenges faced, and the tech stack that powers its data-matching algorithm.

The space that CoffeeSpace is delving into is a relatively new and innovatively-disruptive space, insofar that they earned a spot in TechCrunch Disrupt 2024’s Startup Battlefield 200, a premier startup competition by TechCrunch.

Here’s CoffeeSpace’s elevator pitch: Similar to dating apps, users/co-founders can swipe left or right through profiles on the platform. A match occurs when two co-founders swipe right on each other. They can then start chatting and connecting.

Watch the full interview here:

Still intrigued? Keep reading.

This was how CoffeeSpace started

Hazim was a finance graduate from MIT with experience in prominent financial roles like the World Bank, yet he always had a passion for startups and innovation.

During the peak of the Covid pandemic, Hazim, like all of us, found himself with a sudden availability of ample time at home. It was during the same period that he met Carin, now the co-founder and CTO of CoffeeSpace. They had countless hours and days of brainstorming and realized there was a significant gap in the co-founder matching space, stemming from their own challenges in finding compatible co-founder partners.

And so, CoffeeSpace was born.

CoffeeSpace’s core idea and features

CoffeeSpace stands out as a disruptive and innovative solution to this notorious and “age-old” struggle within the startup scene of finding co-founders. Traditionally, co-founder matching often involves organizing meetups, or tapping on a community’s existing network such as Y Combinator’s own co‑founder matching network. These meetings are however not easily discoverable, necessitate in-person meet-ups limited to certain cities, and are not scalable.

This is exactly the gap that CoffeeSpace strives to solve.

CoffeeSpace drew major inspiration from popular dating apps like Tinder and Hinge and deployed the familiar "swipe right" feature and algorithms to match users to potential co-founders. They aim to streamline the entire process of finding and connecting with potential co-founders onto a single app platform.

Users can download the app for free. Upon creating a new account, users are prompted to complete a series of quick questionnaires that help the algorithm construct the users’ co-founder profile. This profile will then be displayed and used to match with other users/co-founders.

Here are some snapshots of the questionnaire interface:

How does Proxycurl power CoffeeSpace behind the scenes?

Proxycurl is a full-fledged data enrichment API provider, where developers can pull data at scale about people, companies, contact info, jobs, and more. Our APIs and dataset products power many such applications like CoffeeSpace.

In the series of screenshots shared above, the very first question that CoffeeSpace asks of users during onboarding is their LinkedIn profile URL. CoffeeSpace then uses Proxycurl’s Person Profile Endpoint to enrich the users’ profiles with their educational backgrounds and work experiences automatically. These all happen behind the scenes automatically and at scale for all users during onboarding.

Using Bill Gates as an example. Say he’s looking for a co-founder, he proceeded to download CoffeeSpace and register for an account, this is likely CoffeeSpace’s code input that pulls Bill Gates’ enriched data programmatically via Proxycurl’s People API.

import requests

api_key = 'YOUR_API_KEY'
headers = {'Authorization': 'Bearer ' + api_key}
api_endpoint = 'https://nubela.co/proxycurl/api/v2/linkedin'
params = {
    'linkedin_profile_url': 'https://www.linkedin.com/in/williamhgates/',
    'extra': 'include',
    'github_profile_id': 'include',
    'facebook_profile_id': 'include',
    'twitter_profile_id': 'include',
    'personal_contact_number': 'include',
    'personal_email': 'include',
    'inferred_salary': 'include',
    'skills': 'include',
    'use_cache': 'if-present',
    'fallback_to_cache': 'on-error',
}
response = requests.get(api_endpoint,
                        params=params,
                        headers=headers)

The above code includes other parameters that aren’t directly related to CoffeeSpace’s use case, but it shows the various parameters that can be used with Proxycurl’s Person Profile Endpoint.

And this is the response - specific to CoffeeSpace’s use case - the users’ LinkedIn profile picture, education background and work experience:

{
    "public_identifier": "williamhgates",
    "profile_pic_url": "https://s3.us-west-000.backblazeb2.com/proxycurl/person/williamhgates/profile?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=0004d7f56a0400b0000000001%2F20240927%2Fus-west-000%2Fs3%2Faws4_request&X-Amz-Date=20240927T050405Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=f3959b437dc80e9281bb864bbad28f53312565ab1cd7776bfd6e8e17cea4dc90",
    "experiences": [
        {
            "starts_at": {
                "day": 1,
                "month": 1,
                "year": 2000
            },
            "ends_at": null,
            "company": "Bill & Melinda Gates Foundation",
            "company_linkedin_profile_url": "https://www.linkedin.com/company/bill-&-melinda-gates-foundation",
            "company_facebook_profile_url": null,
            "title": "Co-chair",
            "description": null,
            "location": null,
            "logo_url": "https://s3.us-west-000.backblazeb2.com/proxycurl/company/bill-%26-melinda-gates-foundation/profile?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=0004d7f56a0400b0000000001%2F20240927%2Fus-west-000%2Fs3%2Faws4_request&X-Amz-Date=20240927T050405Z&X-Amz-Expires=1800&X-Amz-SignedHeaders=host&X-Amz-Signature=77937a411477b30790ce699266efabd2cca85edea619f2af747cb5e0f9697884"
        },
        {
            "starts_at": {
                "day": 1,
                "month": 1,
                "year": 2015
            },
            "ends_at": null,
            "company": "Breakthrough Energy ",
            "company_linkedin_profile_url": "https://www.linkedin.com/company/breakthrough-energy",
            "company_facebook_profile_url": null,
            "title": "Founder",
            "description": null,
            "location": null,
            "logo_url": "https://s3.us-west-000.backblazeb2.com/proxycurl/company/breakthrough-energy/profile?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=0004d7f56a0400b0000000001%2F20240927%2Fus-west-000%2Fs3%2Faws4_request&X-Amz-Date=20240927T050405Z&X-Amz-Expires=1800&X-Amz-SignedHeaders=host&X-Amz-Signature=92e52762e76f15b03c35704c35a74b9667c06be40019789485423b169d7a9724"
        },
        {
            "starts_at": {
                "day": 1,
                "month": 1,
                "year": 1975
            },
            "ends_at": null,
            "company": "Microsoft",
            "company_linkedin_profile_url": "https://www.linkedin.com/company/microsoft",
            "company_facebook_profile_url": null,
            "title": "Co-founder",
            "description": null,
            "location": null,
            "logo_url": "https://s3.us-west-000.backblazeb2.com/proxycurl/company/microsoft/profile?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=0004d7f56a0400b0000000001%2F20240927%2Fus-west-000%2Fs3%2Faws4_request&X-Amz-Date=20240927T050405Z&X-Amz-Expires=1800&X-Amz-SignedHeaders=host&X-Amz-Signature=6436aebfa6d4e4aaf00ca41d011ff9011e0985006c5697015617cf4d1ded37ad"
        }
    ],
    "education": [
        {
            "starts_at": {
                "day": 1,
                "month": 1,
                "year": 1973
            },
            "ends_at": {
                "day": 31,
                "month": 12,
                "year": 1975
            },
            "field_of_study": null,
            "degree_name": null,
            "school": "Harvard University",
            "school_linkedin_profile_url": "https://www.linkedin.com/company/1646/",
            "school_facebook_profile_url": null,
            "description": null,
            "logo_url": "https://s3.us-west-000.backblazeb2.com/proxycurl/company/harvard-university/profile?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=0004d7f56a0400b0000000001%2F20240927%2Fus-west-000%2Fs3%2Faws4_request&X-Amz-Date=20240927T050405Z&X-Amz-Expires=1800&X-Amz-SignedHeaders=host&X-Amz-Signature=f364c50c234e9eb9f06a39c3c92a6a5331ca30096f57f405da5472ce3bf39894",
            "grade": null,
            "activities_and_societies": null
        },
        {
            "starts_at": null,
            "ends_at": null,
            "field_of_study": null,
            "degree_name": null,
            "school": "Lakeside School",
            "school_linkedin_profile_url": "https://www.linkedin.com/company/30288/",
            "school_facebook_profile_url": null,
            "description": null,
            "logo_url": "https://s3.us-west-000.backblazeb2.com/proxycurl/company/lakeside-school/profile?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=0004d7f56a0400b0000000001%2F20240927%2Fus-west-000%2Fs3%2Faws4_request&X-Amz-Date=20240927T050405Z&X-Amz-Expires=1800&X-Amz-SignedHeaders=host&X-Amz-Signature=4ef24eca69fdada887d5faa63ceb5606718be833439c930e75d8813638f7f157",
            "grade": null,
            "activities_and_societies": null
        }
    ],
   }

The data retrieved using the Person Profile Endpoint also plays a key role in providing CoffeeSpace with insights into their most prevalent co-founder demographics, informing them about their ideal customer profiles (ICPs) and more, quoting Hazim,

Stanford is our number one user pool by school.

With this information, they know better who their key ICPs are.

In addition to front-end features, Hazim leverages Proxycurl’s Person Profile Endpoint to access data about new users for background verification purposes. This proves especially useful when users provide incomplete information or when their LinkedIn profiles are missing crucial details. In such cases, he retrieves users' data from alternative sources using Proxycurl's API endpoint.

What if users uninstall the app after a successful match?

During the interview, a pressing question was on our minds: Will most users uninstall the app after a successful match? We were glad Hazim gave us a great response to this question.

The short answer is, no. This is because CoffeeSpace’s use case extends beyond just co-founder matching. It also caters to early-stage hiring and networking within the startup scenes as founders continue to find the need to seek talents for their companies.

Even if a successful match is made, co-founders may find that they are not compatible in real life and may need to search for another like-minded partner, again using CoffeeSpace.

Some statistics:

• The average lifespan of a startup is typically 6-12 months, indicating that users may return to CoffeeSpace to find new co-founders for other ideas.
• Early-stage hiring is crucial to the survival of startups (citation), indicating matched co-founders might still use CoffeeSpace to find talents

In short, users do stick around even after successful co-founder matching.

That’s exciting. What’s next for CoffeeSpace’s future?

Improving the cofounder matching algorithm

CoffeeSpace’s superpower lies in its matching algorithm, and that remained the top priority in their product roadmap, to continually improve the algorithm.

One strategy involves leveraging LLM solutions like OpenAI to enhance semantic understanding. This includes interpreting user input, preferences, and enriched profile data to better grasp user personas and enhance matching accuracy.

Besides drawing inspiration from popular dating apps like Tinder and Hinge, CoffeeSpace is also getting inspiration from major social networking sites like TikTok on how to improve its algorithm. Improvements involving tracking various users’ behaviors such as profile views, time spent on profiles, and scrolling habits.

Beyond person data, CoffeeSpace could also pull company data related to their users to enhance that part of their algorithm relating to the users’ professional backgrounds. For instance, with Proxycurl’s Company API, a plethora of additional data points such as a company’s funding history, acquisition information, company size, and more can be pulled to improve user matching.

Expanding into the VC and startup investment matching space

CoffeeSpace has already been attracting interest from investment firms and venture capitalists due to the valuable data insights it possesses on its extensive user base of really-early stage co-founders.

It is common for investment companies to rely on investment signals such as tracking the movements of potential startup founders to identify investment prospects. However, investors will know of this information only after a founder founded a startup and updated his/her social profiles. In some cases like stealth startups, they won’t even know.

Through CoffeeSpace however, VCs can tap into the huge reservoir of potential startup founders even before they start a company, even as early as when they’re exploring ideas or finding a co-founder on CoffeeSpace’s platform.

To better algorithm, data, and co-founder matching

We are stoked to be part of CoffeeSpace’s remarkable growth. Launched in March 2024, CoffeeSpace now has a whooping 5600 users (and growing) and secured $500k in funding.

Similar to the evolution seen in the dating app industry, there initially was a lot of stigma around such tech and algorithms in matching people for love, and now for starting a company. The skepticism was that it’s just odd for tech to connect people for such an intimate and complex endeavor as love, or in this case the startup journey. Over time though, dating apps have become the norm. We believe it’ll happen for the work that CoffeeSpace is doing here too.

CoffeeSpace Interview Transcipt

Colton: Hi I'm Colton here with Proxycurl. Normally you would find me over on the blog but today you'll find me either on the blog or on YouTube. And I'm here with Hazim, the founder of CoffeeSpace. So I'm going to go ahead and let him introduce himself.

Hazim: So I'm Hazim, co-founder CEO of CoffeeSpace. We're building the Tinder for people exploring ideas to find co-founders essentially, that's the easiest way to explain it.

Short background about myself. I'm from Malaysia, born and raised. Went to the UK for my undergrad. Came to the US about 8 years ago, slightly more than 8 years now. I came from my grad school, I was in MIT, I was doing the Masters of Financial Engineering, the MFin program over there. Went to the World Bank for about 5 years. I was in DC, much colder weather than it is in SF. So I move from the worst weather of Boston to like, yeah, that has been the gradual shift. I was with the World Bank for 5 years I was doing basically quantitative risk for the treasury portfolio management. So my team managed basically the risk of like a 45 billion portfolios. Which is completely different than what CoffeeSpace is of course.

What led me to CoffeeSpace was Covid actually. Because of Covid many of the things, you know, the social elements of work was not there. I have a bit more time now working from home in DC and let's explore some ideas. So I posted about a problem space, CoffeeSpace was not the first iteration of the idea explored actually. I posted about the problem space I was passionate about on Facebook, LinkedIn. My co-founder Carin reached out, we did not know each other, and this ties up to why we believe CoffeeSpace is so important. Because I thought about an idea for two years, didn't do anything about it, till Karin reached out. She was a stranger, we met at a random event years before that never kept in touch but because of this article we connected. We explored things over weekends. When you don't go to school together have work together you need to build that foundation of a relationship of trust, that working relationship. So what we did was, she was at Facebook at the time. We explored things over weekends, we had a call every Sunday night, two three hours. We'll talk about the things we want to learn, read, watch or explore, validate over the next week, and that was what was for months. We didn't know we wanted to do a start up full time, we were perfectly happy with our jobs. But yeah you explore something enough and it gets somewhere.

Colton: What was your primary role in CoffeeSpace in comparison to like how your partner complimented your role as well.

Hazim: So we, in terms of interest, personality we couldn't be further apart, and that is why it's so perfect right. We cover absolutely, I mean, we compliment each other perfectly in that sense. So she is the engineer, she handles the product side essentially. Like the app you saw, she built alone in two months, frontend, backend, design algo. My co-founder handles the engineering technical side, I handle everything else essentially. So fundraise is on me, customer support, growth, getting users on board, legal, finance, all the things that you need to keep a company going, your team has to do everything right, when it was just a two three person team. It was just the two of us, we added the third co-founder rather recently.

Colton: Now I also have a question for you, I forget which Tinder-like dating app does this or or says this, but one of them has like a slogan like, we're the app that's designed to be uninstalled. So my question to you is is essentially, if your app is to work probably, ideally they would find their partner and then not need the app anymore. Is that correct? Have you ever thought about that?

Hazim: I mean that was the assumption, that was the assumption we needed to validate essentially. Is it true that when people find a co-founder, they're gone from the app? We've been around long enough, we launched our app in March so it's been over six months since launch. But no that is not true, for three reasons people stick around. So the first reason is this is not like dating in the sense you find your partner you got to leave the apps right? Like you can't just stay on Tinder if you're in a committed relationship, generally that that is the societal convention. But no, not for co-founders. You could find a third co-founder, we added a third co-founder. So they will be as actively swiping. They're open to it because a co-founding team can very well be three people if not up to four people. It is rare to see beyond four person founding team. So this is not like a marriage with one to one generally.

So second reason is people are already finding their early hires on CoffeeSpace. So employee number one two three for example they're very close to a co-founder in nature. So we had double trial periods with people who could be our first founding hirers as well. Through CoffeeSpace, they swiped on us. So they told us, "I'm exploring ideas but I don't mind being a founding hire as well." So this is the natural expansion again, people are sticking around for that, we have not optimized the platform for that purpose yet, we are not publicly stating that, but it is a use case that we are actively exploring given that it is already happening on the platform. A third of the people who have told us, they are working together right now are actually of early hires. They might need more than just that first original founding team.

The third reason, so the third reason is just the velocity of startup life, like 6-12 months is roughly the lifespan of startup. Marriages is a lot longer, 15-20 years. So within 6-12 months we see them coming back because even if it's a good co-founder relationship, if the idea is invalidated and they need to explore something else, we have users who come back, like you know, okay we need to explore something. As long as you have the startup bug yeah you always need something. That is very fair like startup founders rarely just start one. It's just the nature of this space right, it's very hard to have a startup immediately succeed usually it takes a few iterations just like ourselves it took us three iterations before we got to this idea. So that actually helps people come back and yeah so the LTV you know the tail life of people on our platform is a lot longer than we initially assumed.

Colton: What is the app built with?

Hazim: So on the frontend it's built with FlutterFlow, so that's the frontend. Backend is Firebase. But yeah Proxycurl is one of the tools we use to enrich the users profiles. We have the founder profile, the co-founder preferences but you do want basically the enrichment of LinkedIn information, the experience, education.

Colton: So you said that you used Flutter for the frontend but what was the backend?

Hazim: Firebase. The simple reason it just integrated really quickly and easily with Flutter Flow. Because we're using Flutter Flow on the frontend it affects many of the decisions of the other tools we use, for example we chose Revenue Cats for subscription management instead of Stripe because it just integrates easier with Flutter Flow.

Colton: I'm going to look that up really quick.

Hazim: Yeah I never heard of Revenue Cats before that but yeah they've done the job for us we've been very happy using the platform. They are basically an alternative to Stripe for subscription management.

Colton: So the general app is essentially like we were talking about a little bit earlier, it's kind of just being about like the Tinder for startup founders essentially. So it's just it's all centered around like finding the missing puzzle piece for your startup idea. So like if you're maybe you know the business, marketing, sale- oriented side, you might want the technical co-founder on the other hand. So it's just about about integrating and connecting these people at the end of the day.

Hazim: So basically we collect data points and based on these data points we match people up algorithmically. People can change their preferences and all it's quite, I mean ,the UI is quite similar to Hinge. That was our main source of inspiration Yeah like Tinder yes, or the Tinder no. So you can't exactly swipe but this is deliberate right because when you can just swipe you're going to too long, you're not going to deliberate too much on a profile. So that's why Hinge you have to like a specific part of the profile, to optimize for a match, to optimize for connection. So that is the model we will be, we are going after essentially. We will not introduce a swipe element anytime soon until validated people will still put in the time deliberation as they should.

Colton: Okay and then so when you sign up you have to insert your LinkedIn URL right. So you're using our API on the backend, Proxycurl to populate a lot of the profile information from that LinkedIn URL?

Hazim: That's right, profile picture, education, experience mainly. There are other elements which we might use in the future depending on what users tell us they want, what the algorithm needs but yeah, that is what we are doing and that saves users a lot of time.

Colton: So that's, that right there is primarily how you're using Proxycurl right now.

Hazim: But it's also for the initial review of users right. We are now building an auto, thus far, I have reviewed every single person you know the 5,600 people have joined CoffeeSpace.

Colton: So that's how many people that, I was going to ask that as well.

Hazim: Yeah that's how many people we have on CoffeeSpace right now. We need to know that it's an actual person right. You are verifying right now you're verifying individually everybody that's most people go through of course but yeah there are specific things we look for within the LinkedIn profile to approve it otherwise right it's likely that this person has not because people don't even populate their LinkedIn profiles too much it's hard for us to believe they are serious about. There are there are some people that are you know qualified business individuals that relatively empty education experience. If it's zero experience, zero education, it will require my manual intervention to look at but this also you know number of followers. If they've only started the account you know with 10 followers for example. It's not a definite so it's like there's an auto approval process not an auto denial. I will be reviewing the edge cases for me to see like you know if this is a suitable to be on the app.

Colton: Have you received any funding yet for CoffeeSpace?

Hazim: Yeah so we have raised a total of half a million thus far, so these are mainly from angels, many of these angels are actually our users so it's interesting right because these people are in the startup space quite a few of them are angel investors. They're exploring some ideas themselves but yeah we have raised $500,000 to date from angels. yeah. Nice.

Colton: When I was using the app it kind of looks like your monetization strategy is just to make it easier to find partners, is that fair, like that's your monetization?

Hazim: We're motivated to solve it faster. So the basic version, the minimum version free version of CoffeeSpace is good enough to give people leads consistently but if you really want more leads fast so it's basically creating differentiated experiences with artificial scarcity you basically lock certain things which the most motivated people will want. For example I can give an example of a premium filter, it's prior startup experience if you want a filter for people who have sold a company before, started a company before or worked in a startup before at least right then these are premium filters. You don't need a co-founder who has sold a company before if you want that. So if you paid for the premium subscription, you would have the ability to essentially filter for more qualified individuals, you get more leads per day, you get premium filters, your invites go up of the top of the list instead of chronologically. If for example you had 10 invites the person with the premium account would have their invites go right up to the list but yeah these are all strategies dating apps have used that we have learned from essentially.

Colton: Gotcha. What are you doing to grow? What is the future? Like what do you have planned for?

Hazim: yeah so We're getting users through a few main ways. One is of course word of mouth. People who are looking for co-founders have spoken to other people looking for co-founders. So because we're so niche at this point not many people are serving the co-founder matching space. Apart from Y-combinators co-founder matching platform there are not really that many other incredible, very established or other platforms out there. So word of mouth is one, users post testimonials about this like we did a Product Hunt launch. So these big events like Product Hunt, like TechCrunch, they give us waves of new word of mouth, like new engagement. LinkedIn I've been building in public so I've been posting our progress almost every week basically on LinkedIn, Twitter has been another major source but yeah these have been our main ways of get to users.

Colton: Mostly just organic word of mouth just getting your name out there.

Hazim: More or less, social media, PR basically we've had multiple people publish about this on their blogs and we've been featured in a few sites.

Colton: I could imagine sites like Indiehackers could be useful for you or even like even like college campuses in the United States as well.

Hazim: I mean funny you say that because yeah one of our users, so Stanford is our number one user pool by school. Stanford people make up about 10% of the users pool of CoffeeSpace right now. So what one of our users did was he published us, he wrote a simple email in a newsletter, in a mailing list called Stanford Venture groups. Everyone in Stanford, generally at grad school and above building is start up. 80 people signed up overnight just from that one email. So schools have been where word of mouth has been propagated by users sharing about it in mailing list, Slack groups WhatsApp groups.

Colton: For the future what do you guys have planned do you have anything major planned uh for the near future?

Hazim: I mean of course right we're preparing for Tech Crunch. Some of the things we're working on in house is of course is improving the algorithm itself right. That is a consistent thing, a continuous process we are doing but there are three main phases to it. The first one is what we already have on the app is called the Boolean level, are you within 50 miles of me, are you technical or not technical, are you open to an equal split or like you're fully negotiable equity wise. So these are like just yes no parameters, but the next level is what we are now able to start exploring because of Proxycurl actually. This is what we call the social bar level. With LinkedIn information I can actually start defining what are the similar people to those you're swiping right on. As you swipe we can actually now you swipe data to say, hey you've been, you haven't told us this preference within your profile setup but you keep swiping on people with seven plus years experience in Fintech. This is a data point we will use to further self teach the algorithm to get better, to learn what what is relevant to you. So this is the second level.

The third level is what we call the semantic level. This is where we're going to use some OpenAI embeddings to start defining the semantic level. If you and I are both building in travel, we define our ideas, we post this information through the OpenAPI and these are the two statements of our ideas. If our ideas are 90% match we should be ranked higher than just some random non-matching ideas etc. But yeah we can do the same for working style, this is my motivation to build start up, this is my working style, this is what I want to devote my life to. So the algorithm will be a big part of what we continue to do to make this better as the number of user scale because we need to guarantee, I mean, we need to ensure relevance as this thing scales. Otherwise you have a million people on it, it's going to be much harder for you to find the right person if it doesn't learn from you. Second is basically exploring, this second or third problem space, co-founder matching will be our focus at least for the next year, year and a half, up to Series A most likely but beyond that like it's these two problems spaces, it's either the early hire space or the one we feel is more synergistic immediately is just basically unlocking the value of the data. Because accelerators, early stage investors have already told us, Hazim you have information that is very valuable within your database. Essentially you know before anyone else when someone wants to build, before they apply to VCs, because we people only apply to VCs when they have a co-founder. But we know before they have that. If I want to be the first check to these founders that is very valuable information. So it's basically creating a backend equivalent where investors will be able to see profiles of users who opt in for this. So users will be triggered a notification, hey there are investors who might want to look at your profile, would you want to opt-in. I've interviewed dozens of users, there's this the time as share my, you know, share my information with them, if you tell me five people 5 VCs view my profile this week I'm going to be very motivated to check my profile. Not only that but make it updated.

Colton: That is very valuable data for sure.

Hazim: It's a living network instead of Crunchbase Pitchbook which is more passive data. Why LinkedIn is so available is because it's active data is a network but that is the equivalent we will do on CoffeeSpace essentially because it is a living network.

Colton: Is there anything else you'd like to like to share?

Hazim: There is of course, there's a lot of uncertainties maybe even stigma against people finding co-founders on such a platform. The general perception is that you must know your co-founder through school, through like you know this history right because there is trust, you know the startup journey is very difficult so you need that strong bond, at least that is the perceived. But it's the same thing as online dating, I would say 10 years ago no one would believe online dating could be a thing, should be a thing. Now 30% Americans find their long-term partners online, and it's the same for co-founder matching.

Colton: Actually I'm part of that statistics.

Hazim: Exactly my co-founder found her partner on Hinge herself. It's just yeah it's a stigma before it becomes mainstream, it's the same thing here, like YC has already funded 28 companies, 28 pairs who met through their co-founder matching platform. If you do the math they're only taking in 1-2% of people which means hundreds if not not more than a thousand, 2,000 pairs have formed just through YC's co-founder matching. And as this becomes more mainstream we feel like what Tinder, Bumble. Hinge did for online dating, that is what we want to do for people starting companies globally. So that is what CoffeeSpace, that is the long-term vision of CoffeeSpace essentially and that's what makes us excited each day to work on this everyday.

Colton: Awesome, honestly I love the idea. I really like the Tinder for startup founders twist. angle. I think it's really cool, I wish you the best best of luck, thanks for watching guys.