
Athelas: Our Road from Hack to Product - craigcannon
http://blog.ycombinator.com/athelas-our-road-from-hack-to-product/
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mifeng
As a product geek, I love this. It's an awesome application of computer vision
to solve an ancient and expensive problem in a new way. Just building the
product and getting enough labeled data to a level when you can demonstrate
proof of concept must have been a monumental achievement. Kudos!

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ttandon
Hi HN! Athelas cofounder Tanay here. Happy to share any more stories/answer
questions about the post.

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mifeng
From the website, it looks like you're taking a direct-to-consumer approach by
selling a $250 device and a $15 monthly subscription service (Uber for blood
testing!?).

Can you explain why you chose that go-to-market strategy? I don't know much
about this market, but it seems non-traditional, to put it gently.

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ttandon
There are a lot of people we've started working with (elderly populations, old
age homes) for whom a monthly test is really useful (at-risk for a lot of WBC
screenable conditions), but who don't want to buy an entire device/learn to
use with app and related software. The monthly screen came as an offshoot of
this population's use case.

While the front-facing website is a direct to consumer device, the majority of
our deployed devices will be partnerships formed with clinics - this just
enables anyone who wants to use the tech to be able to without the long email,
custom quote, phone call, partnership process.

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mifeng
Just like in engineering, the initial investment into a go-to-market strategy
is only the tip of the iceberg; it's the maintenance and support required to
make it successful that kills you.

At both my former and current company, I've experienced firsthand how
distracting splitting your focus on multiple customer segments can be.

I would advise you to recognize upfront that the consumer and clinic
partnership channels entail vastly different motions for acquiring and
supporting customers. If you're investing resources into pursuing both
channels simultaneously, make sure that you are measuring ROI for each one.

Hopefully you're getting good go-to-market advice from YC and your investors.
If not, consider applying to StartX, where there's a solid community of AI-
for-med startups (caveat: I'm an alumnus).

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eps
This is easily one of the most impressive products that came out of YC in a
while. Fantastic work. Break a leg with the FDA approval.

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ttandon
Thanks!

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eps
PS. "See the demo here" links to
[https://www.youtube.com/watch?v=fEcx3hx-398](https://www.youtube.com/watch?v=fEcx3hx-398)
that says "private video."

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avip
I'm confused. You've submitted a 510K, you call the device "pre cleared", and
you're distributing? Please elaborate.

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ttandon
We have two versions of our device - one that's fully automated (the one
requiring a 510k), and another where results are manually confirmed post
computer vision in-house before being tabulated (this is classified as a
"manual count" or hemacytometer). To start off distributing, we're shipping
with the Class 1 version to beta users and early locations. Once the FDA
clears our algorithms to be fully automated (under class 2), that won't be
needed anymore. Let me know if that makes sense

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avip
I see, GHO exemption. Yes that makes complete sense.

So Malaria test is off table for now right? That can't fall under class 2.

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bcatanzaro
Would love to hear about how this is different from Theranos.

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dude01
The article says it uses computer vision to detect parasitical cells like
Malaria or Trypanosoma. No black magic, they explain their techniques in
detail. I think the difference between them and Theranos is that Athelas is
detecting things in extremity blood which is valid to test for, whereas
Theranos was looking for things that needed rich heart blood from veins.

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dsuchr39
The applications are quite far ranging. I am really impressed by the
transparency of the Athelas founders.

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fasteo
Constructive criticism

This seems like a great product - it is for sure a great technology - but
their intro video[1] is taking people's hopes an fears way too far. For
example, at 02:53, they say:

"Identify early patients who come into the office could have their illnesses
diagnosed at a earlier stage when they are still curable"

This is a pretty strong statement. I would recommend to be less aggressive
with their positioning. Their target market are people with potentially
serious health problems and false hopes are that last thing they need.

[1]
[https://www.youtube.com/embed/shhOy2OzGIc?autoplay=1](https://www.youtube.com/embed/shhOy2OzGIc?autoplay=1)

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mifeng
100% agree. The biggest mistake that Theranos made was over-promising.
Startups in other vertical do it all the time, but you can't get away with it
in consumer healthcare because lives are at stake.

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ttandon
Interesting - thanks for the feedback! have been internally chatting about
making the video beginning/in general more technically focused as opposed to
overly emotional (something we noticed was coming about), helpful to hear that
here as well. I think the direction we were taking was based on clinical fact
(lower cost, earlier testing esp for baseline metrics strongly associated with
better clinical outcomes), but I can see how it comes across with that over-
hype vibe.

will work on fixing

