Payments as a Shadow System of Record
Case study on Camber Health — with Christophe Rimann, Co-Founder
The conventional wisdom in vertical software is that you need to be a system of record to own the customer. While many question whether that logic holds up in the world of Vertical AI, the advantage of systems of record (SoRs) remains clear — successful ones accumulate workflow depth, data gravity, and platform leverage that compound over time, creating true defensibility. In verticals where the payment process is complex enough to justify dedicated AI infrastructure and services, however, we believe the financial layer may become just as sticky — and those best positioned to own it may not look much like software.
On this week’s Verticals, we dug into how Camber — a Series B healthcare AI payments startup co-founded by Christophe Rimann and backed by a16z — is building exactly this. Episode here and full case study below.
When Vertical Fintech meets AI Services
Camber is a healthcare AI payments startup that has raised $44M from a16z, Craft, Zigg, and others. Their vision: durable, hard-to-replicate financial infrastructure a la Stripe, but with the defensibility of a Vertical AI platform intaking massive volumes of first-party data.
Does every vertical need its own financial rails? Perhaps not, but the evidence is compelling that many do. At minimum, healthcare is a prime candidate. It lives and breathes on payments between fragmented, complex, regulated parties. As healthcare shifts out of hospital systems and into outpatient settings — behavioral health, PT, ENT, cardiology — unit economics can quickly break down as the cost of financial execution balloons. A hospital, for example, can justify a human chasing the last 10% of a $10K claim. A behavioral health clinic submitting $150 claims by the tens of thousands cannot. The long tail of underpaid claims becomes structurally uneconomic. Providers think they’re collecting at 97–98%; the underlying data says 92–93%. They can’t staff their way to a higher number, so millions of dollars evaporate into deadweight loss.
Christophe Rimann — a former McKinsey healthcare consultant who previously built a licensed crypto broker-dealer — saw that gap and spent five years building a foundational model purpose-built for claims adjudication. Not an agentic wrapper on legacy RCM software, or even RCM software re-imagined for LLMs. Camber’s team, rather, envisioned a vertically-specific system trained on billions of dollars of expert-labeled claims data, capable of reverse-engineering payer denial logic before a claim is ever submitted. Today, Camber’s first-pass “clean claim” rate runs around 95%, compared to 80–85% for large clinics operating without it, and as low as 60% for some $500M+ providers. For larger clients, that delta can translate into millions in annual EBITDA uplift.
Our interview with Camber was made possible by Parafin. Gusto recently partnered with Parafin to embed a line of credit directly into their payroll workflow, so SMBs can cover cash crunches in seconds. Learn how Parafin’s embedded fintech can solve your problems here.
The ROI-First Future of Vertical GTM
Camber is strategically interesting not only because of its infrastructure play, but also because it is rethinking monetization for the AI era. The company prices on outcomes, not seats. This isn’t disruptive for customers since they largely compete with offshore BPOs, not software vendors. Despite the fact that adoption takes doing — Christophe estimates 30–40% of enterprise value lies in change management — their gross margins run at upper-quartile SaaS levels. As Christophe put it: “Most of our providers think of us as a services company.”
Like much of enterprise vertical AI these days, Camber takes many pages from the Palantir playbook. “Sell services, execute through software / AI” is potent in healthcare — like many other real-economy verticals — because the buyer doesn’t want to think about the technology. They want to know their collections number went up and they want it solved. Camber structured their initial customer engagements to prove ROI. That has enabled them to run a 60-day pilot-to-conversion cycle… in a market where RFIs run 18+ months.
This is one of many suggestive data points — across a growing number of Vertical AI startups in the current AI Services wave — that outcomes-based pricing can collapse sales friction when the pain is acute enough. In some sectors, the grip of traditional vertical SaaS cycles is loosening.
Healthcare’s Stripe Moment?
The Stripe analogy is Christophe’s own. It’s admittedly not perfect: much of what makes Stripe what it is comes down to its horizontal universality. Moreover, if something is truly “rails,” shouldn’t it be agnostic to outcomes, rather than predicated on them? But there are a few ways in which mental model is apt.
Thirty years ago, every large credit card purchase involved a back-room phone call to the issuing bank.1 Today, that complexity is fully abstracted and automated. Healthcare insurance claims (and the associated payments) are stuck in that pre-abstraction era — resolution requires dozens of steps, stakeholders, and manual interaction. Camber is betting it can facilitate a similar evolution in healthcare, and compress it into a few years.
Of course, none of that would be possible without the inter-connectivity and process automation LLMs have enabled. By layering AI on top of a proprietary data network, Camber now processes roughly 25% of daily claims volume in its beachhead vertical within behavioral health. Multiple EHR vendors already white-label Camber as their payments layer. One in three of their SMB deals involves the provider switching their entire system of record just to access Camber — a striking inversion of traditional thinking around the defensibility of SoRs and vertical moat-building assumptions.
Payments as a Shadow System of Record
Camber’s success to date is just one case study, and a developing one. But there’s an interesting emerging lesson for Vertical AI founders and investors in healthcare, and other deeply regulated, payment-heavy verticals.
We recently shared our concept of the “shadow system of record” — a strategy by which founders can grow a thriving business in verticals where dominant, controlling incumbent systems of record (like EHRs in healthcare) have historically sucked the oxygen out of the room. The concept is simple, even if identifying opportunities is hard: establish a net-new control point and grow unhampered in the incumbent’s blind spot.
The payments layer may be a prime candidate for shadow SoRs in some sectors. Could EHRs become the interchangeable commodity, while the claims & payments network becomes the stickier infrastructure? Certainly, that would be a meaningful structural shift from the traditional vertical SaaS playbook.
It does echo a pattern we’ve been tracking: the next chapter of vertical software is being written by companies that capture value from non-software budgets, leveraging wedges impossible before the current generation of AI.
Camber has raised $50M — with a Series B led by a16z last year — employs ~90 people and is expanding from behavioral health into five new verticals this year. The open question, as Christophe frames it, is whether they can scale the go-to-market — and whether the claims landscape itself shifts beneath them in the next 18 months. That uncertainty is real — as is the case in highly regulated markets. But the benefit of being more than just a pure Stripe-esque rails play or a pure external Vertical AI Services play, is that Camber drafts on real, rarefied first-party data as it scales. The data moat flywheel they’ve built over five years of expert-labeled claims outcomes2 is compounding — and that’s not something anyone can vibe-code.
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We beg you to listen to the Acquired podcast’s episode on Visa if you haven’t. It’s an eye-opening lesson on the history of fintech and the fundamental nature of moats.
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