A HealthTech Failure

Astarte Medical shuts down after having raised $14M.

Hey — It’s Nico.

This is my weekly digest of startup failures, business ideas, and founders’ news.

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Today’s edition is brought to you by Ignite Digital.

Here’s what I got today:

  • A dive into why Astarte Medical failed 🔥

  • An analysis of YC’s “Request for Startups” 💡

  • A summary of OpenAI’s new AI, Sora 📰

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Astarte Medical

Astarte Medical, a $14M HealthTech Failure

In December 2023, Astarte Medical, a pioneering health tech startup, made the difficult decision to shut down after seven years of operation. 

Despite promising beginnings, including raising $14M in funding, the company faced insurmountable challenges. 

Earlier this week, Tracy Warren, CEO and co-founder of Astarte Medical did a fantastic interview in which she discussed the rise and fall of her startup.

Astarte Medical's Journey: Astarte Medical was founded in 2016 by Tracy Warren, Tammi Jantzen, and Katherine Gregory with the aim of improving care for premature babies.

The company developed healthcare software, including its flagship product NICUtrition, designed to monitor and analyze feeding and nutrition delivery to babies in intensive care units (NICUs).


  • In 2019, Astarte secured $5M in Series A funding.

  • In 2020, they signed their first hospital contract.

  • In 2021, they raised another $7.6M in funding.

Reasons for Failure:

  • No PMF: Astarte only got contracts with 4 hospitals during its whole existence, which wasn't as many as the investors hoped for. Warren says that hospitals were simply not interested in investing in digital solutions and did not have many incentives to innovate. In the beginning, they were unsure if this lack of interest was due to the pandemic or the market downturn but ultimately realized that there was no product-market fit for what they were building.

  • The pandemic: Although the pandemic did increase funding for health startups, it also severely decreased the hospital's margins, making them more interested in surviving the crisis than in investing in new software.

  • Operational Challenges: Operational challenges, such as integrating with the Electronic Medical Records (EMRs) and navigating the complexity of healthcare data, made delivering and expanding the solution more difficult.

Reflections on the HealthTech Industry:

  • Few incentives to innovate: Hospitals and other healthcare organizations lack significant motivation to invest in new and innovative products. According to Warren, unless hospitals are forced to by external forces (like the pandemic), they “are ok to not jump into new stuff.” Hospitals are not penalized for not innovating, so they usually prefer to avoid change since there is no risk to it. 

  • Devices are easier than software: Hospitals are used to buying medical devices all the time but do not frequently buy new software. This makes the process of selling digital solutions to hospitals a particularly painful experience.

  • Unexperienced HealthTech investors: During the pandemic, many investors rushed into the HealtTech industry without fully understanding the market dynamics, leading to premature capital dumping.

Approaching Shutdown: In her interview, Warren gives some useful advice on how to approach a business shutdown:

  • Be transparent about the challenges: Avoid surprising your investors and team with ugly news that they had no clue about. Be honest with the challenges the company is facing right from the start and let new hires know about the risks of entering your startup.

  • Pivoting is not always a good idea: Warren was pushed into pivoting the product to the AI field but decided that this was not a good idea. Using AI in her product could probably have helped in getting another round of funding, but ultimately, she did not see how this would make hospitals more interested in her product.

Go Deeper:

Your Next Startup

YC’s Request for Startups

Last week, Y Combinator unveiled its latest Request for Startups, a comprehensive outline detailing the various startup categories the accelerator intends to support. 

The list comprises 21 distinct categories encompassing a wide array of industries, ranging from healthcare and cryptocurrency to military applications.

Trends: Out of these 21 categories, there are several notable trends emerging that could shape the future of the startup landscape:

Interesting Ideas: Here are some of the categories that I found the most interesting:

  • Developer Tools Inspired by Existing Internal Tools: Internal tools developed by programmers within successful companies are often overlooked as sources of inspiration for startup ideas. These tools, born out of necessity to solve specific problems, have the potential to benefit a broader audience if productized. If it worked for one company, it might work for others. Encouraging the creation of startups based on these homegrown solutions could lead to valuable innovations in the developer tools space. Some successful products that were born as internal tools include React.js (by Facebook), Slack, and Trello.

  • Spatial Computing: Just a few weeks back, I wrote about the launch of the Vision Pro and the huge opportunities the VisionOS ecosystem has. YC seems to agree because they are looking to invest in startups building the software for this new era of computing. With only a couple hundred apps in the marketplace, VisionOS is in dire need of software that can fully harness the capabilities of the Vision Pro device.

  • AI to build enterprise software: AI could revolutionize enterprise software by simplifying the customization process. This could replace lengthy sales cycles with a simple starter product that customers can customize through AI interaction. Instead of having specialized developers customize your ERP or CRM, you could just ask AI for the changes you need.

In The News

OpenAI Launches Sora, Its Text-to-Video AI

In case you’ve been living under a rock and somehow missed OpenAI's latest announcement, here is a quick rundown of the important parts.

Last week, Sam Altman announced Sora, OpenAI’s newest video generation model. This model is capable of generating realistic-looking videos from text inputs.

This is not the first AI model to give video generation a try, but it is undoubtedly the best one.

Just for reference, this was the state of AI video generation one year ago, and this is where we’re right now:

Quite a difference, right?

It is scary to imagine what this technology will be capable of in one year from now.

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