Athelas: Our Road from Hack to Product | Hacker News Reader

Athelas: Our Road from Hack to Product

blog.ycombinator.com

63 pointscraigcannon19 comments

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!

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

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.

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.

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).

If I buy a device now, can I upgrade it as you add more tests?

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.

Thanks!

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

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

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

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.

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

Definitely! Not all of what Theranos did is public, so I can only share from what I know, but our approach is highly focused on trained computer vision algorithms - whereas a lot of previous approaches have relied on coulter counting (mentioned in the post). You can check out how we performed in the data section http://Athelas.com/data

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.

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

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

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.

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

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