Spring Health

Magic AI

Spring Health

B2B employer benefit — similar model to Lyra Health but with a sharper focus on precision matching. Companies pay Spring Health a per-employee-per-month fee.

Employees take an initial assessment and Spring Health's algorithm recommends a care pathway: therapy, medication management, coaching, digital self-care, or a combination. The key differentiator is the precision — the algorithm claims to reduce treatment time by 50% by getting the right match first instead of cycling through options.

Spring Health also provides a therapist network, psychiatric services, and crisis support. Revenue scales with employer contracts and employee utilization.

Magic AI

Magic is building an AI that works like a software engineer, not a chatbot. The goal is a model you can hand a whole code base and a task, and it writes, reviews, and debugs like a teammate.

Their edge is memory. In 2024 they showed off LTM-2-mini, a model with a 100 million token context window.

To put that in perspective, that is about 10 million lines of code the model can look at in one shot, by far the biggest of any model at the time. The plan is to sell this as an AI coworker to companies that write a lot of software.

As of the 2024 rounds, the product was still not for sale.

Spring Health

April Koh was studying computational neuroscience at Yale when she encountered research on precision medicine for depression — the idea that you could use data to predict which patients would respond to therapy versus medication versus a combination. The existing system was essentially trial and error: try an antidepressant for six weeks, and if it doesn't work, try another one.

Meanwhile, patients suffer. Koh co-founded Spring Health in 2016 with Adam Chekroud, a Yale neuroscience PhD, to build a platform that uses machine learning to match employees to the right mental health treatment on the first try.

They started by publishing peer-reviewed research showing their algorithms could predict treatment response better than chance, then turned that research into a product that employers would pay for.

Magic AI

Eric Steinberger and Sebastian De Ro started Magic in 2022. Steinberger is an AI researcher who became convinced that the missing piece for a true AI software engineer was memory.

Chatbots forget what you told them a few thousand words ago. He wanted a model that could read your entire code base and remember all of it.

They raised a small seed in 2022, then a $23 million Series A in early 2023 led by Alphabet's growth fund CapitalG. From day one the pitch was not a chatbot.

It was an AI colleague that could handle real engineering work.

Spring Health

Enterprise sales to large employers, competing directly with Lyra Health, Headspace Health, and traditional EAP providers. Spring Health leads with outcomes data — publishing research showing faster recovery times and higher clinical improvement rates than industry benchmarks.

Celebrity advisor Apolo Ohno and high-profile board members gave early credibility. Series C at $2.5 billion valuation generated press coverage that opened doors.

International expansion to serve global workforces. Strategic investment from Kinnevik gave European distribution relationships.

Partnership with health plans to offer Spring Health as the behavioral health component within existing benefits.

Magic AI

Magic's strategy is research first, product later, which is both unusual and expensive. Instead of shipping an app and iterating in public, they raised huge sums to chase a technical breakthrough in model memory.

The headline move was the 100 million token context claim, which got the whole AI world talking. They also cut a deal with Google Cloud in 2024 to build two supercomputers, called Magic-G4 and Magic-G5, using NVIDIA chips, to train bigger models.

Star backers like Eric Schmidt served as validation. The bet is that if the tech is far enough ahead, the product and the customers follow.

Spring Health

Direct competition with Lyra Health, which is larger and better-funded. The employer mental health benefit space is crowded and increasingly commoditized — every startup claims better outcomes and faster ROI.

Therapist supply is the binding constraint across the entire industry. Proving that ML-driven matching actually produces better outcomes than simply having a good therapist network is a difficult clinical claim to substantiate at scale.

Employee engagement is everything — if employees don't take the initial assessment, the precision matching engine can't work. And the macro headwind: employer benefits budgets are under pressure, and mental health benefits are easier to cut than medical benefits when money gets tight.

Magic AI

Magic has raised close to half a billion dollars and, years in, still has no product the public can buy. That is the whole problem in one sentence.

A giant context window is a great demo, but rivals like Cursor, GitHub Copilot, and Cognition's Devin already have real users and revenue. Magic has to prove that more memory actually makes a smarter engineer, not just a bigger number on a slide.

And it has to do that while burning enormous sums on compute against competitors who are already shipping. The clock and the cash both keep running.

Spring Health

Precision mental health platform — ML-driven assessment that predicts optimal treatment pathway for each individual. Therapist matching engine connecting employees to the right provider by specialty, approach, and predicted fit.

Spring Health Moments — bite-sized digital exercises based on CBT for mild symptoms. Medication management through in-house psychiatric providers.

Manager and HR tools for supporting teams without violating privacy. Work-life coaching for non-clinical needs like stress and work-life balance.

Family support extending benefits to dependents. Crisis support including 24/7 access for emergencies.

Magic AI

The centerpiece is Magic's LTM, or Long-Term Memory, model family. In 2024 they unveiled LTM-2-mini, a model with a 100 million token context window, pitched as the key to an AI that can understand an entire code base at once.

The broader product is an AI software engineer, or coworker, that can write and change code across a whole project. The company also announced Magic-G4 and Magic-G5, two supercomputers built with Google Cloud and NVIDIA to train these models.

Much of it is still research rather than a shipping product.

Spring Health

Investors include Tiger Global Management, Kinnevik, Northzone, William K. Warren Foundation, and Able Partners.

Series C in 2022 valued the company at $2.5 billion.

Magic AI

Magic's backers are a murderers' row of AI insiders. It started with a $5 million seed round in 2022 and a $23 million Series A in early 2023 led by Alphabet's CapitalG.

Then in February 2024 came a $117 million round led by Nat Friedman and Daniel Gross, two of the most connected investors in AI. The blowout was August 2024.

Magic raised $320 million with checks from former Google CEO Eric Schmidt, CapitalG again, Atlassian, Jane Street, Sequoia, and Elad Gil. That pushed total funding to around $465 million, all for a company still building toward its first sellable product.