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Alike 👩🏻‍⚕️

a new take on self-diagnosing

a note from us

  • “ow my ankle hurts!” is usually followed by whipping out the phone and going down the self-diagnosing rabbit hole 🐇
    • “do i have flat feet, tendinitis, a fracture, a break, arthritis…am i dying?!”😳
  • after diagnosing yourself with ankleitis-hypochondriacitis syndrome, you rush to the doctor
    • turns out it was just an ankle sprain
  • online browsing can be a blessing or a curse when it comes to your health
  • this week’s company has a better, more trustworthy way to track symptoms

in a sentence

Alike is a digital healthcare company that uses crowdsourcing, artificial intelligence, and machine learning to give patients access to personalized health data

  • crowdsourcing: provides insights into treatments and symptoms missing from one-size-fits-all platforms
  • machine learning & artificial intelligence: groups individuals based on shared medical characteristics
  • personalized: get an Alikeness score to other users and discover treatments you may be missing from those who share symptoms or medical experiences

bulleted version:

can’t figure out if you have a cold or covid? Alike allows users to make a better diagnosis based on how their symptoms compare with others🤧

the basics

  • industry: healthcare technology, artificial intelligence, crowdsourcing 🩺
  • headquarters: Tel Aviv, Israel 🇮🇱
  • year founded: 2020
  • company size: < 20 🧳
  • investors: Pitango Venture Capital, WellTech Ventures
  • amount raised: $5m
  • latest stage: seed round 🌱

due diligence

what we like

  • combating misinformation: trying to understand symptoms on your own is overwhelming
  • building community: while this has become a buzz word in today’s tech world, connecting with others going through shared medical experiences could make a real difference
  • crowdsourcing is the future: through 2025 the crowdsourcing market is expected to grow 14% each year
    • crowdsourcing is effective because it gives vast information and is less expensive and more accurate than outsourcing/hiring

potential risks

  • 💻 algorithm bias: machine learning may contain inherent bias from the person who designed the algorithm, skewing the data
  • 🔒 privacy information: while Alike has clear statements regarding user privacy, combining “health data” and “social network” may not sit well with everyone
  • a place for hypochondriacs to convene: internet diagnosing causes users to get paranoid on their own, but could a diagnosing network make people even more paranoid?

founder profiles


why Alike:

  • by unlocking the power of crowdsourcing and patient similarities, Alike’s platform will allow individuals to fully and accurately asses health conditions ✅