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
this can cause over- or under-treatment
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
Amnon Bar-Lev (prev. MDClone, President @ Check Point)
Varda Shalev (Family Medicine Physician, Prof @ Tel Aviv University, Director @ BATM, prev. Maccabi Health Care Services)
Ohad Zadok (prev. EverCompliant, sPARK, Intel)
comps
why Alike:
by unlocking the power of crowdsourcing and patient similarities, Alike’s platform will allow individuals to fully and accurately asses health conditions ✅