Hey — It’s Nico.

Welcome to another Failory edition. This issue takes 5 minutes to read.

If you only have one, here are the 5 most important things:

• Level, a benefits startup, shut down after 7 years — learn why below.

• YC’s guide on how to get AI Startup Ideas.

• OpenAI cancels its o3 model in favor of a “unified” next-gen release.

• QuEra Computing raised $230M to advance quantum computing technologies.

• OpenAI’s DeepResearch is a game changer for many industries — learn how to use it below.

Let’s get into it.

This Week In Startups

🔗 Resources

Three Observations by Sam Altman.

Deep Research and Knowledge Value.

How to get AI Startup Ideas.

What comes after coding, according to Vercel founder.

📰 News

OpenAI cancels its o3 model in favor of a “unified” next-gen release.

BuzzFeed is launching a new Social Media platform.

Elon Musk offered $97.4B to buy OpenAI but his offer was rejected.

Anthropic sees revenue potentially soaring to $34.5 billion in 2027.

💸 Fundraising

Chestnut Carbon raises $160M to turn old farms into forests.

Harrison.ai, a health tech startup, raises $112M.

QuEra Computing raised $230M to advance quantum computing technologies.

Archer Aviation raised $300M to accelerate the development of hybrid aircraft.

Fail(St)ory

Bigger Benefits for Less

A few weeks ago, Level, a startup offering flexible employee benefits, abruptly shut down. Despite its vision of modernizing insurance and the significant funding it had secured, Level couldn’t find a buyer in time to keep the business alive.

Interestingly, just five days after its closure, Employer.com attempted to purchase Level, marking its second bid in a month to acquire a failed startup. While Level ultimately did not survive, its technology and customer base still held value for potential buyers.

What Was Level: Level was founded in 2018 by Paul Aaron with the goal of making insurance payments as seamless as everyday transactions.

The startup focused on providing employers with customizable benefits plans, starting with dental and vision coverage. Companies using Level could offer 100% coverage for specific treatments, and claims were processed in as little as four hours.

The promise was clear: “bigger benefits for less”, without the bureaucracy of traditional providers.

The company positioned itself as a flexible alternative in the benefits space, emphasizing transparency and efficiency. Its tech-driven approach aimed to help both employers and employees get more value from their benefits spending. However, despite these ambitions, Level ultimately couldn’t sustain its business.

The Numbers:

• 📅 Founded in 2018.

• 💰 Raised at least $30.8M in funding.

• 📈 Secured a $27M Series A in April 2021.

• ❌ Failed to secure a buyer before shutting down.

Reasons for Failure: 

• Failed Acquisition Attempts: evel aggressively sought a buyer before shutting down, but its final deal collapsed at the last minute due to “external challenges”. Without a successful acquisition, the company ran out of options and was forced to close.

• Challenges in Employer Adoption: The employee benefits space is notoriously difficult to disrupt. Companies tend to be cautious when switching providers, prioritizing stability and reliability over innovation. Even if Level had a compelling product, convincing employers to change may have been a significant challenge.

• Regulatory & Compliance Complexities: The insurance and benefits industry is heavily regulated, and navigating compliance requirements can be expensive and time-consuming. If Level faced unforeseen regulatory hurdles, this may have added pressure to its operations.

• Limited Expansion Beyond Core Offerings: Level focused on dental and vision insurance but did not significantly expand into broader healthcare benefits. This may have limited its ability to scale and attract a larger customer base.

Why It Matters: 

• Level’s failure highlights the difficulties of disrupting the insurance space, where trust and reliability matter as much as innovation.

• The collapse of its acquisition deal shows how fragile last-minute buyouts can be—startups relying on a sale to survive may not always find a willing buyer in time.

• Employer.com tried to purchase Level just five days after it shut down, marking its second attempt in a month to buy a failed startup. This trend suggests that even struggling startups still hold value, but timing is everything.

Trend

DeepResearch

Last week, OpenAI dropped DeepResearch, an AI that does research for you. Give it a question, and it will search, read, and summarize sources from across the web. Basically, it's an AI-powered research assistant that works fast—minutes instead of hours.

Why It Matters:

• AI that works for you: DeepResearch isn’t just a chatbot. It actually browses, reads, compares sources, and builds detailed research reports. Last week, I mentioned Operator as an early sign of the ‘Agentic Era’ of AI—tools that don’t just respond but act independently. DeepResearch takes that idea further.

• Huge time-saver: If you do market research, track trends, or analyze competitors, this could cut hours off your workflow.

• Potential to shake up entire industries: Sam Altman thinks tools like DeepResearch could already handle a small but real percentage of all valuable tasks. If that’s true, this kind of AI could start replacing parts of knowledge work across fields like finance, consulting, and research.

What Is DeepResearch?

DeepResearch is powered by OpenAI’s o3 model, optimized for web browsing and analysis. You give it a research prompt, and it doesn’t just fetch links or summarize a few articles.

It actually digs into sources, reads through detailed reports, compares information across different sites, and pulls it all together into a well-reasoned, structured research document.

This isn’t quick-hit Google-style searching. It takes time—5 to 30 minutes depending on the complexity—because it’s doing real work. It looks at contradicting claims, pivots if it hits dead ends, and connects dots you might miss skimming on your own. 

The result is more like a research analyst’s report than a search result. Every claim is backed with citations, so you can check the sources yourself.

What Can It Do?

• It can do medical research (or any type of research really).

• Find a “needle in a haystack”. In this example, OpenAI researches ask the model to find a very specific scene from a niche TV show.

  

• And it even tells you the jobs it is going to replace:

Help Me Improve Failory

That's all of this edition.

Cheers,

Nico