Blog Archive - F-Prime Capital

Stablecoin Cards: The Infrastructure Race for the Next $100 Billion

How stablecoin cards are turning a crypto-native asset into a mainstream payments rail.

A cardholder taps $5 at a coffee shop. During the ~400 milliseconds before the terminal confirms the transaction, the issuer processor must answer one simple question: does this account have sufficient funds?

Modern issuer processors such as Marqeta and Galileo answer it easily when the balance sits in fiat on a traditional ledger. They cannot answer it when the balance sits in stablecoins such as USDC, outside the systems they were built to read. Companies like Rain and Reap built that capability for new stablecoin card programs and already process billions annually.

This article maps the stablecoin card market as it stands, examines where the next $100 billion of volume comes from, and looks at the infrastructure that will carry it.

Stablecoin cards are working

Stablecoin-linked debit cards are one of the clearest examples of product-market fit in crypto. The demand is simple: access to digital dollars that can also be easily spent. For a stablecoin holder, a card is the shortest path from a digital balance to groceries, fuel, and everyday commerce. Visa estimates that stablecoin-linked card volume grew 319% to $5.2 billion in 2025, across more than 130 card programs in over 50 countries.

While crypto cards are not new, the underlying asset and infrastructure have changed materially. Coinbase and WireX enabled users to spend BTC at merchants as early as 2015, but adoption remained limited because users were still spending a volatile asset and often incurred meaningful conversion fees. Coinbase, for example, has charged 2.49% on purchases funded with non-stablecoin crypto assets.

Stablecoins make the card program more compelling. By placing a dollar-denominated stablecoin behind the customer balance or within the funding and settlement flow, the card avoids liquidating a volatile asset at the point of purchase and reduces conversion friction. When those dollar balances are spent in local currencies, the platform can also capture the FX economics. For wallets, exchanges, and neobanks, the card adds a new monetization layer through interchange and related financial services.

For merchants, however, the experience remains largely unchanged today. Rain’s CEO said stablecoin-funded payments have reached more than 100,000 merchants without them knowing it, as transactions still settle through traditional payment networks on T+3. The next step is moving stablecoins deeper into merchant settlement, with providers such as Stripe/Bridge beginning to enable merchants to settle directly in stablecoins.

Behind this growth, a new infrastructure stack is taking shape. The map below shows the key players at each layer, from the distributors that own the customer relationship to the networks that route each transaction.

Four observations define the stack today:

The strongest early adopters are platforms that already own the customer relationship. Exchanges, neobanks, wallets, and credit platforms begin with an existing base of crypto and stablecoin users. Adding a card lets them monetize that customer base through everyday spending and creates demand for every layer beneath it.
Full-stack still dominates. Much of today’s stablecoin-linked card market is powered by full-stack providers such as Rain and Reap. Their principal memberships with Visa and Mastercard give them direct network access, on top of which they bundle program management, processing, stablecoin conversion, banking relationships, and interchange revenue sharing. For customers, this is the fastest route to launch; for Rain and Reap, it keeps more of the economics across interchange, FX, and float in-house. The model has already reached meaningful scale, with Rain and Reap together processing close to $9 billion in annualized card volume.
A modular route is forming. Companies can increasingly assemble card programs from specialists across sponsorship, processing, liquidity and program management. Lightspark’s Visa card program, announced in August 2026, runs Lithic for processing, Lead Bank for issuance, and Lightspark for USDC settlement, with no full-stack provider in between. The approach could become mainstream as card products expand across markets with different banks, licenses, and payment rails, and as companies seek to reduce concentration. Kulipa’s abrupt shutdown in July 2026, which stranded card programs across 20 clients, and Rain’s August 2026 hack, which drained $1.1 million from card balances across its program partners, illustrate that risk.
Banks can become the anchor for a modular stack. Many established issuing banks such as Lead Bank and Cross River already hold direct Visa/Mastercard membership and provide BIN sponsorship, settlement and compliance oversight. Rather than being bypassed by full-stack players, they can extend that role into stablecoin cards and allow customers to choose processors, liquidity providers, and other infrastructure independently. A new generation of stablecoin-native banks such as Erebor and Pave Bank could push this further, combining a regulated banking layer with stablecoin custody and compliance from day one. The result would be a more modular, competitive market.

The next $100 billion in stablecoin card volume

Stablecoin supply grew from $124 billion at the end of 2023 to over $300 billion by mid-2026, creating a growing pool of balances that can be spent through cards. According to Paymentscan, cumulative spending on stablecoin-powered cards has now surpassed $10.9 billion, while RedotPay forecasts annual spending could reach $50 billion by 2028.

The market remains concentrated, with Rain and Reap accounting for most issuance volume. Consolidation has already begun: Reap has been acquired by Kraken for $600 million.

Despite the growth, stablecoin cards remain a small part of the broader card ecosystem. Global card purchase volume is ~$30-40 trillion a year. Marqeta alone processed $383 billion in 2025, while Galileo ended the year on 128.5 million accounts. Behind them sits an even larger base running on FIS, Fiserv, and TSYS, much of it built on batch mainframe systems never designed for real-time, on-chain money.

So where does the next $100 billion of stablecoin card volume come from? There are two sources.

Crypto-native issuers, whose rapid expansion is already visible and should continue.
Existing fintechs, neobanks, and brands moving some of their established card volume onto stablecoin rails.

The second source remains nascent but represents the larger prize: bringing substantial non-crypto customers and payment flows into the market. The appeal is twofold: better backend economics by reducing the cost and friction of funding card programs across banks and geographies, and a compelling proposition in weak-currency markets, where users can hold a dollar balance and spend it anywhere Visa or Mastercard is accepted. This opportunity is becoming clearer as providers such as American Express have pulled back from international dollar cards, creating whitespace for stablecoin-native issuers.

This expansion beyond crypto-native users is what begins to turn stablecoin cards from a crypto product into mainstream payments infrastructure. Recent examples include Marqeta’s partnership with Zerohash, which enables fintechs to add stablecoin capabilities to existing card programs without rebuilding the core stack, and Revolut’s launch of EURR, a euro stablecoin integrated directly into its consumer app. Karta shows how the model can extend into traditional wealth channels, distributing its stablecoin-powered card through more than 80 private banks globally, including Morgan Stanley, Raymond James and Itaú.

The addressable market for stablecoin cards is an order of magnitude larger than the one being contested today. Fintech, neobank, and commercial card programs represent ~$5.5 trillion of annual volume. Moving just 1% of that volume would create a $55 billion market. At a 20-basis-point take rate, that is a $110 million revenue pool before accounting for any value captured from float, FX, or treasury services.

Where the stack remains underbuilt

Several missing pieces are starting to emerge:

Settlement platforms such as OpenFX and Hercle (an F-Prime portfolio company) provide 24/7 fiat and stablecoin conversion, removing the need to build internal trading, liquidity, and treasury operations. We expect regional winners in corridors where local banking relationships, liquidity, and FX expertise matter most.
Crypto-native regulated banks such as Erebor and Pave Bank, combine the charter and BIN sponsorship of a traditional sponsor bank with control of the stablecoin leg. Very few banks can do both today.
Credit could be the next big unlock. Credit monetizes better than debit because it adds lending income on top of interchange and other card economics. Most stablecoin cards today remain debit or prepaid, while early credit products are beginning to innovate on underwriting. This could be particularly valuable for global HNWIs whose asset span institutions and jurisdictions. The next opportunity is bringing more of these credit models onto stablecoin rails, potentially combining new underwriting approaches with established networks such as American Express.
Stablecoin-native issuer processors. These could become the Marqeta or Galileo of stablecoin cards: making an on-chain balance a native card-funding source by reading it at authorization, orchestrating conversion, and managing settlement behind the scenes. The critical feature is migration: letting existing issuers adopt stablecoin rails without changing BINs, card credentials, network relationships, or the customer experience. No provider has established this position at scale today.

What we’re looking for

The greenfield is beginning to be captured from both directions. Nium acquired Cypher, Marqeta and Galileo are developing stablecoin-backed card functionality, and fintechs such as Flex have raised $70m to put commercial payment flows onto stablecoin infrastructure.

We believe the next battleground is the $5.5 trillion market for fintech, neobank, and brand card programs, where little stablecoin-native infrastructure exists today. The winners will not ask issuers to rebuild around crypto; they will fit stablecoins into existing programs, integrate with incumbent processors and sponsor banks, and abstract the complexity of custody, liquidity, compliance, and settlement.

We want to meet founders who understand stablecoins as a new money rail and are building innovative business models on top of it, from cards and cross-border payments to settlement and treasury. We are also interested in teams rebuilding the credit stack, whether through underwriting, infrastructure, or the capital that funds these new credit products. If you are bringing deep payments expertise in a way that materially improves the existing system, we want to hear from you.

Views expressed are as of the date indicated, based on the information available at that time, and may change based on market or other conditions. Unless otherwise noted, the opinions provided are those of the speaker or author and not necessarily those of F-Prime or its affiliates. F-Prime does not assume any duty to update any of the information.

The third parties mentioned herein and F-Prime are independent entities and are not legally affiliated. Trademarks and logos used within are the property of their respective owners.

Bloomberg Acquires Canoe: What Does it Mean for Private Markets?

Exciting news today. Bloomberg announced it has acquired Canoe Intelligence. It’s a big outcome for everyone at Canoe and a punctuation mark on Canoe becoming the category leader in private markets data. Congratulations to Jason Eiswerth, Michael Muniz , Zack Helgeson, CAIA, CIPM , Chris Jones, Noel Calhoun, Josh Whitcraft, James Eliason, Nassim Bordbar, Brian Sadler, and the entire team!

When we first invested in Canoe, I wrote a post asking who would build the Bloomberg of private markets data, openly hoping it would be Canoe. With this acquisition, I suppose I have an answer.

With the acquisition of Canoe, Bloomberg gains unmatched access to analytics ready data with more than 15+ years of history to 44,000 private funds and $11T of AUA. Canoe serves 500+ customers across the value chain of investors/Limited Partners (LPs), asset managers, servicers, and advisors.

All of us at F-Prime were fortunate to be a part of Canoe’s journey and I cannot wait to see what the team builds with Bloomberg. Truly a great buyer for a great company.

With an industry event like this, it is worth asking what it means for private markets?

As a quick recap I envisioned three market phases:

Startups digitize the flat files (PDFs, spreadsheets) that General Partners (GPs) still use to report to LPs,
GPs modernize their own back offices and start distributing data digitally and in a standardized way, and
The winners of Phases 1 and 2 provide the analytics layer for private markets along with a de facto security master.

Canoe was winning Phase 1, and Bloomberg’s acquisition will strengthen that position. The other largest players in public markets data have made their bets: BlackRock acquired Preqin for $3.2B (13x revenue), MSCI acquired Burgiss for ~$900M all-in (12x revenue), and S&P Global paid $1.8B for With Intelligence (14x revenue).

Takeaway #1: several of the biggest players have declared private markets as the next frontier and have made their acquisitions. Others may still act, including Nasdaq, Dow Jones, NYSE, and Moody’s.

Takeaway #2: we have seen little progress on Phase 2. GPs are not sharing data in standardized digital ways like public markets. There are good, introductory steps like Daphne working with Apollo, Hamilton Lane, and EQT, yet in the time it took my daughter to start and finish high school, I still do not know a GP that has started sharing data digitally by default.

However, the tailwind driving Phase 2 forward is more evident than ever: evergreen funds. Unlike drawdown structures that have defined private markets for decades, evergreen funds are open-ended and semi-liquid with continuous subscriptions and periodic redemptions. Evergreen funds are a better fit for retail investors, and asset managers need retail investors to keep growing.

Over the last four years, Evergreen AUM has more than doubled to $600B today and is forecasted to represent 20%+ of all private markets AUM within a decade. Evergreen structures require asset managers to publish fund data, which over time will pressure them to publish comparable data for draw-down funds.

Takeaway #3: Firms like Morningstar see this coming and are trying to do for private funds what they did for mutual funds in the 1980s: build the standardized framework for evaluation. This is still difficult — Phase II must culminate in digitally distributed investment data — but it is the development I’m most excited about. Another F-Prime portfolio company, Monark Markets, is building the infrastructure to connect GPs of evergreen funds with the brokerage and wealth platforms that 23M accredited retail investors already use, enabling scalable omnibus clearing, model portfolios, and secondary liquidity. That is the retail distribution infrastructure this whole shift needs. Other startups like AltQ are building fund analytics and ratings for LPs, while Osyte, is building the portfolio and liquidity management layer for LPs to manage public and private data holistically.

Four years in, the question from my original post has an answer. The next one — who builds the analytics and workflow layer on top — is just getting started.

Originally published on LinkedIn.

Behind the Breakthrough: Q&A with AJ Loiacono, Chief Executive Officer of Judi Health

Twenty-six years ago, AJ Loiacono was a consultant helping pharmaceutical manufacturers upgrade their supply chain systems. He assumed drugs made it to consumers at a fair price. Then a friend handed him a claims file—and his entire perspective on the industry changed.

What Loiacono discovered was a pattern of inefficiency so widespread that it revealed deep structural challenges within the system: drug prices fluctuating hourly, vendors duplicating and distorting claims data, and an industry built on misaligned incentives and conflicts of interest rather than patient outcomes. After eight years auditing pharmacy benefit manager (PBM) contracts and watching the industry resist reform, he reached a conclusion: to fix the system, one had to become part of it – and rebuild it from scratch.

In 2017, AJ co-founded Capital Rx on two principles that ran counter to industry norms: never profit from drug spend and build technology so efficient it could sustain a business without hidden fees. Today, Judi Health manages care and processes claims for over 58 million covered lives, maintains a 99% client retention rate, and is setting a new standard for what healthcare administration can look like when built on transparency and technology rather than complexity and conflict.

You spent years auditing PBM contracts before founding your own company. What made you decide to build rather than continue to consult?

What I realized is that change was slow to materialize. The dominant PBMs in the industry had established ways of operating that seemed generally, albeit reluctantly, accepted, and meaningful innovation in the business model seemed elusive at the time.

I felt the only way to really move the industry in the appropriate direction was to first become part of the problem. I would need to become a PBM. And I would start a company based upon two principles: one, our incentives as an administrator would never conflict with the cost of medications. And two, we would operate more efficiently than our competitors and put plan members first, so we built a hyper-efficient technology platform that allows us to administer claims approximately 70% more efficiently than competitors.

Why is the “no profit on drug spend” principle so foundational for both a transparent PBM and what you’re building?

In our view, it’s paramount to align incentives in pharmacy benefit management so the administrator’s sources of revenue and interests are fully transparent and in step with the plan and its members. When organizations generate revenue based on the amount spent on medications, it can create competing priorities.

Our approach is to ensure that our earnings are independent of drug costs, allowing us to focus squarely on delivering value and removing any potential for misaligned incentives. This principle echoes back to earlier eras in our industry, when PBMs primarily served as service providers rather than as intermediaries capturing multiple revenue streams from each transaction.

Over time, the industry has evolved. Many organizations have expanded their portfolios to cover everything from health plans and provider networks to mail order and specialty pharmacy services. While this vertical integration created efficiencies in some areas, it also introduced new complexities and new models for compensation. Our founding principle is to keep things straightforward and transparent, reinforcing trust for everyone involved.

You’ve built something called “Unified Claims Processing.” What problem does it solve?

Processing a healthcare claim can be complex, often involving many different stakeholders. These include providers, health plans, third-party vendors, and members themselves – each of whom needs clear, timely information. Traditionally, the flow of a claim is supported by a series of systems and vendors, each responsible for different parts of the workflow, whether the claim concerns medical, pharmacy, dental, or vision benefits.

As claims travel between systems, updates and changes can occur rapidly – claims may be paid, adjusted, or re-coded in real time, making it challenging to ensure that everyone is always working from the same set of facts. With this in mind, we saw an opportunity to build a unified system that brings together all the moving parts of the claims process, providing a single source of truth and reducing unnecessary administrative complexity.

We realized, if we could be the first company to build Unified Claims Processing, we would reduce cost by reducing overhead and administrative inefficiencies. We aim to streamline the entire experience for patients, providers, and plan sponsors – helping to control costs, minimize redundancies, and ultimately make the healthcare journey simpler and more transparent for all.

Can you share an example of the kind of confusion Unified Claims Processing is designed to solve?

I’ll share a story that illustrates the challenges here. An investor of ours – a highly educated professional – recently experienced some confusion after returning to work following the birth of her child. She received a bill from the hospital for her care, followed by a different amount from her insurance carrier, and then a third, different, figure from a separate payment integrity company. Despite her very knowledgeable background, even she found it difficult to reconcile these numbers, leaving her wondering how anyone could confidently navigate the process.

What often happens is that different organizations involved in the same episode of care are referencing slightly different versions of the same claim information at different points in time. This can lead to confusion for patients, frustration for providers, and additional administrative work for health plans.

That is exactly what Unified Claims Processing solves. It is one system, one source of truth, in real time.

How do you measure real-world impact?

For us, real-world impact starts with delivering cost savings for our clients. Many of the organizations we serve are sizable – on average, our clients’ plans cover around 20,000 lives. Achieving meaningful savings is imperative not just at the outset, but continually over the life of our partnership.

We are most proud to have supported long-term clients who have seen flat or even negative trends in their overall pharmacy spend, even as healthcare costs elsewhere in the US continue to rise year-over-year. Long-term cost containment is essential, especially when compounding can quickly double expenses.

Beyond the numbers, we put a strong emphasis on service. Our dedicated, in-house call center team, all full-time employees based in the US, helps ensure responsive, personal support. This commitment is reflected in the routinely high customer satisfaction scores our call center receives, as well as our 99% client retention rate.

Ultimately, our two most important measures of success are straightforward: clients who achieve sustainable savings, and members who are satisfied and well-supported in their healthcare journey.

What drives you to take on such an ambitious challenge in healthcare?

The scale of what we’re working on makes the mission even more meaningful. The broader and more complex the challenge, the greater the potential to improve outcomes across the system. I sometimes say this isn’t just a moonshot – it’s more like a Mars shot. Aiming even higher to create true, lasting impact in healthcare.

I also want people to understand who is hit hardest by inflation on drug spend or healthcare in general. It’s the most vulnerable parts of our population – the elderly and people who have lower incomes. This is not what healthcare should be. That’s precisely what keeps us focused on the mission at hand.

What are the most critical milestones for Judi Health in the next 12 to 24 months?

When developing Unified Claims Processing, we believed it was important to start close to home – so our first implementation was for our own employees and their families. Seeing firsthand how much our team appreciated the ease and clarity of this benefit gave us confidence to extend the offering to clients.

Within the first six months, we’ve welcomed both existing and new clients who are now using the platform for both pharmacy and medical administration. Their positive feedback has reinforced our conviction that a streamlined, unified system delivers real value.

Looking ahead, our ambitious goal is to help make Unified Claims Processing the new industry standard – where medical, pharmacy, dental, vision benefits, accumulators, and eligibility are all accessible in one place and in real time. Once organizations and members experience this level of integration and transparency, it’s hard to go back.

Ultimately, our mission is to help build the modern infrastructure that healthcare in this country deserves. True transformation depends on updating the foundational systems, and we’re committed to helping lead the way forward.

Science2Startup 2026

On May 13th, F-Prime, alongside 5AM Ventures, Atlas Venture, Osage University Partners (OUP), and RA Capital Management hosted Science2Startup.

Scientists, investors, and industry leaders gathered at The Engine in Cambridge for a series of presentations from entrepreneurs advancing promising early-stage science.

Science2Startup is a forum for leading scientists from around the world to present their ideas and engage with investors and executives across the Boston biotechnology hub.

Science2Startup continues to be a platform for academic innovators to share company-forming ideas across biotech and life sciences. This year’s program covered a wide range of areas, including stem cell-derived therapies for diabetes, as well as new approaches to osteoporosis, AML, pulmonary hypertension, neurodegeneration, kidney disease, uterine fibroids, and the opioid epidemic.

It’s encouraging to see early-stage science continue to move toward real-world application.

To learn more, visit the S2S website with this link.

Behind the Breakthrough: Q&A with Chris Johnson, Founder and CEO of Bluebird Kids Health

After helping advance value-based care for older adults as the CEO of Landmark Health, Johnson saw an opportunity to bring a similar model to children: a value-based pediatric primary care platform.

Bluebird Kids Health was born from a stark realization for CEO Chris Johnson: nearly half of America’s children receive care through Medicaid or CHIP, but many live in what he calls “pediatric care deserts” – communities where kids are far more likely to end up in the ER, because they can’t easily access primary care.

Johnson discusses why he’s bringing value-based care to pediatrics and how Bluebird is confronting structural inequities in children’s health. He also explores what it means to build a company designed not just to treat illness, but to help every child reach their full potential through equitable health care – one community at a time.

Was there a defining moment that crystalized the need for Bluebird?

Across metro areas, the lowest-income communities have only half as many pediatricians per thousand children as the highest-income zip codes. Many practices can only afford to have around 20% of their patients on Medicaid, which creates barriers to preventative care for millions of children. We set out to close that gap with an integrated model that brings physical, behavioral, and social services under one roof. Bluebird uses technology to make care more consistent and scalable, while aligning patient outcomes with payer incentives and reinvesting to expand services in pediatric care deserts.

Your mission statement is “to provide exceptional care so all children can thrive.” What does that look like day by day?

For us, exceptional care begins by giving our providers the support they need to practice at the peak of their ability. We invest in training, technology, and team-based support, allowing providers to focus on families and not paperwork. It means partnering with behavioral health providers and community organizations to fill social care needs that fall outside traditional medicine.

The “Every Child” aspect means we never want to turn away a child who comes to our door. We contract with all health plans and offer a self-pay option to ensure every family can access care. We identify primary care deserts by running analytics to pinpoint areas where children have limited access to pediatric practices. In areas with the greatest need, we open clinics in retail spaces (e.g., near grocery stores or laundromats) to meet families “in the flow” of daily life, with extended evening and weekend hours.

Finally, “so all children can thrive” is our long-term measure of success. We aim to create more happy, healthy days for kids. It’s not just about clinical outcomes. It’s about helping children stay in school because they’re now getting the care they need or catching vision issues early to support them as they learn to read. Ultimately, it is about building the foundation for lifelong health.

You brought value-based care principles from adulthood into pediatrics. Why hasn’t this been done before – and why now?

Sometimes problems persist simply because no one has really focused on them. In 1987, only about 16% of children in the U.S. were covered by Medicaid; today, that number exceeds 50%. That means more than half of America’s pediatric population now relies on a system that has historically lacked the innovation and coordinated care models seen in adult medicine. Millions of children still face inequitable access despite having insurance coverage. It’s a massive and growing need, and it’s time the innovation ecosystem caught up to it.

You applied lessons from Landmark Health to this new model. What are some of the biggest takeaways?

The biggest lesson was that you need a mission-aligned culture that truly believes in doing what’s right for patients, paired with a business model that rewards it. When those align, everything else follows.

We’ve also leaned heavily into technology and AI at Bluebird. At Landmark, we used technology because we had to, mainly to process claims and manage data. At Bluebird, we see technology as a driver of the experience itself. We’re building what we call a “pediatric operating system,” which is AI-enabled infrastructure made specifically for this population. It makes back-end operations more efficient and the front-end experience more consistent, from the parent app to the clinical workflow.

What’s your approach to growth, and where do you go from here?

We’re currently operating six Bluebird clinics and expect several more by year’s end. We plan to continue expanding in Florida, then into new states. Our goal is to go deep and truly integrate into communities. In a place like Tampa, for example, we’d rather build half a dozen practices so we can truly serve as a meaningful part of the local health infrastructure and be a reliable partner to hospitals and OBs. Instead of opening a single location in many markets, we focus on building multiple practices within a city so we can become embedded in the community and part of the local health ecosystem.

You’ve mentioned technology as a differentiator. How is AI changing your model?

We use AI to streamline areas across the organization. Things like scheduling, insurance verification, and revenue cycle management become far more efficient with AI, allowing our teams to focus more time and energy on patients. On the care side, we leverage data and analytics to identify children who need proactive interventions, such as closing preventive care gaps. We are also designing digital care management tools that support parents at home.

The key for successfully using AI is integrating it intelligently into the workflow to actually drive outcomes, which is what we’re building our systems to do.

Looking ahead to 2030, what impact do you hope Bluebird will have?

Our north star is to be a meaningful contributor to the health and well-being of children in every community we enter. If you look at why the U.S. lags other wealthy countries in life expectancy, most of that gap actually stems from outcomes for people under 18.

We want to help change that trajectory by reducing preventable mortality, improving health equity, and supporting children as they grow into healthy adults. That’s what “so all children can thrive” truly means for us.

Fazeshift: Transforming Accounts Receivable For An Autonomous Finance Future

At F-Prime, we have long tracked the transformation of the CFO stack as one of the biggest opportunities in fintech today, an active space with plenty of greenfield. In our 2026 State of Fintech report we observed that AI adoption has lagged across financial services — but with the rapid pace of technological advancement, we expect that to change quickly.

Accounts receivable (AR) is especially overdue for AI-driven transformation: the workflows responsible for collecting revenue remain stubbornly manual, relying on spreadsheets, back-and-forth emails, and human judgment to match payments, chase collections, and reconcile mismatches. There are nearly 1.6M accounts receivable clerks in the US today, earning a median salary of $47K and representing a $76B labor market — a testament to this function’s labor-intensivity. The problem is especially acute for businesses in traditional industries like staffing, professional services, and wholesale, where cash flow makes the difference between making and missing payroll.

The first wave of AR software relied on rigid, rule-based systems that only achieved around 40% automation. These systems broke down on exceptions and required enough manual intervention to limit overall adoption. Given the choice, businesses typically chose to solve the problem through labor alone.

But rapid advancements in LLM and agent capabilities now make it possible to automate the messy, judgment-intensive exceptions that broke historic rules-based automation. For the first time, a truly AI-native AR platform can serve the businesses that need it most.

We first met Caitlin and Timmy in September 2024, when they were going through Y Combinator. We fell in love with the team immediately; Caitlin’s sharpness and drive were obvious from the first conversation, and Timmy’s technical depth and customer empathy left a lasting impression on everyone who met him. Having experienced the pain of broken AR workflows firsthand when building their last company, they set out to build the platform they wished they had.

The result is Fazeshift: an AI-native AR automation platform that replaces manual invoice-to-cash workflows with autonomous agents, purpose-built for traditional industries with deep integrations spanning staffing, professional services, wholesale, construction and beyond. Over the past year we stayed close, watched them execute against major milestones, and heard glowing feedback from customers who described Fazeshift as transformative for how they ran their financial operations.

Across our global platform, we are proud to have backed foundational companies that are innovating in the CFO Suite, such as Toast, Flywire, Spendesk, and Icertis. Today, we are thrilled to announce that we are leading Fazeshift’s $17M Series A, bringing total amount raised to $22M. Congratulations to Caitlin, Timmy, and the entire Fazeshift team on this milestone — we could not be more excited to partner with you as you transform financial workflows and bring us closer to an autonomous finance future.

Originally published on LinkedIn.

Robotics Report: China Edition

Behind the Breakthrough: Q&A with Scott Bratman, Chief Innovation Officer of Adela

For more than a decade, Scott Bratman has worked at the forefront of liquid biopsy innovation – developing noninvasive approaches to cancer detection that rely on a simple tube of blood.

Bratman’s research began at Stanford University, where first-generation tests focused on identifying mutations in circulating DNA. These were revolutionary at the time, offering a new window into advanced cancer biology, but the tests struggled with early detection and provided limited tissue specificity.

Bratman joined forces at the University of Toronto with Dr. Daniel De Carvalho, now CSO of Adela, , at University Health Network in Toronto to explore a more powerful biomarker: DNA methylation. Unlike mutations, methylation patterns offer a broader and more contextual signal—capturing not just the presence of cancer, but clues about where it originates and how it evolves. Their collaboration produced a breakthrough: a test capable of picking up on multiple early-stage cancers that became the foundation for Adela. Adela’s proprietary approach avoids chemical damage to DNA, allowing for a new generation of high-resolution diagnostics. Bratman shares how this technology moved from bench to bedside and is helping to usher in a new era for cancer diagnostics.

You started in cancer diagnostics during your training. What led you to found Adela?

I am a clinician scientist with a background in oncology and have worked in the liquid biopsy field for the past 15 years. My training began at Stanford University, where I studied approaches to detect cancer in the bloodstream. I later established a research lab in Toronto, where I partnered with Adela’s CSO Daniel De Carvalho, to address the limitations of first-generation liquid biopsy tests. Our work focused on leveraging DNA methylation to improve detection performance, laying the scientific foundation for the founding of Adela.

Was there a specific “a-ha moment” where you knew you had found something viable as a company moving forward?

Yes. In those early days of liquid biopsy, we could basically detect advanced cancers and find specific mutations linked to resistance or sensitivity to targeted therapies. That was a breakthrough back then, but we lacked the tools to address the full spectrum of cancer, particularly early detection and molecular residual disease after treatment. We focused our efforts on unlocking new technologies using DNA methylation to expand the clinical utility of liquid biopsy.

The “a-ha” moment came from early work in our labs. We saw the potential for detecting not just one, but seven different cancers at early stages from a small blood sample and with a single

test. That was unprecedented at the time. It got us thinking about how far this could go in cancer diagnostics across the full spectrum of disease.

Why methylation patterns? Why are they such powerful biomarkers for cancer?

DNA methylation underlies the development of cells at the earliest stages of differentiation into tissues. Dysregulation of this process can lead to cancers. Because we see this across cancer types and tissue types, DNA methylation in the blood can be used to detect the presence of cancer and identify which tissues are shedding DNA into the bloodstream.

Prior to this, most work focused on DNA mutations, which don’t have that same tissue-type specificity. The challenge historically was that profiling methylation required chemical treatments that degraded the DNA, resulting in a lower signal-to-noise ratio. The platform technology we developed focused on preserving that precious material within a small tube of blood so we could analyze it accordingly.

What makes your approach distinct from peers in your field?

What makes our approach unique is that we use a signal-preserving assay. We do not degrade DNA; instead, we simultaneously enrich the informative, methylated regions within a blood sample and target those for sequencing and analysis.

By having a single assay platform, we can generate data that feeds into analytical models for machine learning to develop signatures for different diseases. We think of it as an engine. We maintain a single platform, derive insights from every sample, and feed a continuous learning machine that gives rise to different products. That is a massive differentiator compared to fixed panels or specific biomarkers.

Adela originally focused on multi-cancer early detection (MCED), but molecular residual disease (MRD) has been a major emphasis recently. How are you balancing those ambitions?

We believe our platform has broad potential across all areas of cancer diagnostics, but we have chosen to strategically focus on applications with strong demand and immediate clinical utility. MRD represents a particularly tangible, near-term opportunity, as it pertains to patients who already have a cancer diagnosis and require rapid, informed clinical decision-making.

Today, therapy response is primarily monitored using medical imaging, such as CT or MRI scans, which have limited sensitivity, are expensive, and often require patients traveling to specialized centers. A blood test that can complement or even replace standard imaging offers a powerful advantage for both patients and physicians.

You mentioned patients traveling to specialized centers. Can you talk about the impact this technology could have on accessibility?

This technology was invented in Canada, a vast country where most of the population is concentrated in a few cities, leaving large regions with sparsely populated communities. These communities often have poor access to specialized medical imaging. Improving accessibility is fundamental to the origin story of Adela, as we believe a blood test can bring advanced cancer management closer to patients in these disparate communities.

Another key challenge is “tissue accessibility.” Many existing MRD tests require a tumor tissue specimen, adding time, cost, and often making testing impossible for patients without sufficient tumor material. For example, in head and neck cancer, over a third of patients are estimated to lack sufficient tissue for these tests. A tissue-free test removes this barrier, enabling accessible cancer management for a much broader patient population.

What are some of the most important lessons that you’ve learned building a company in this space?

Given my background as a researcher and technology inventor, I have sometimes been at risk of tunnel vision. Early on in founding Adela, I quickly realized the importance of partnering with people whose expertise complemented my own. People who had successfully brought products to market and navigated the complexities of fundraising in a competitive space such as cancer diagnostics. I have learned a tremendous amount from mentors and partners along the way during this journey with Adela. Building the right team from the outset created a foundation that allows us to keep patients at the center of what we do.

What is the roadmap for the next 12 to 24 months?

We are very excited about the upcoming launch of our MRD test for use in head and neck cancer, which addresses a significant unmet need in monitoring for recurrence in patients who have completed treatment. Building on that momentum, we recently had a publication accepted on immunotherapy response monitoring. This second product is particularly important because it shows the continuity of our platform across both early-stage and more advanced-stage disease.

We plan to launch the immunotherapy product next, while continuing to advance MRD development for other indications. Simultaneously, we have a large multi-cancer early detection study underway, and we look forward to generating more data in that space as well.

What advice would you offer to others looking to translate a basic discovery into real-world impact?

Technology today is powerful, with seemingly limitless opportunities to push the envelope of what is possible. But at the end of the day, you must ask: What do the data mean for the patient? How does it improve the partnership between the physician and the health system? These questions serve as our guiding light in the development of every test we create.

2026 State of Robotics Report

The robotics investment market continues at its torrid pace. Investment in 2025 was at an all time high, public companies continue to outperform the market, and exits are slowly picking up. Led by the growth in General Purpose Robotics and Defense, the excitement and momentum is palpable. The future of robotics is more exciting than ever!

We invite you to download the report here, and reach out to authors Sanjay Aggarwal and Betsy Mulé.

In Defense of Software. In Defense of Humans.

Last year I wrote a post explaining why vertical SaaS companies could win against the core foundation model providers. A few months later, that argument feels quaint. Anthropic has shipped Opus 4.5 and Claude Cowork with enterprise plugins for finance, engineering, and HR. OpenAI launched Codex. The foundation model providers are not just building models anymore — they are building products…and products that build products.

Arguing against them increasingly feels like shouting from the castle ramparts while the barbarian hordes storm the walls.

And yet. The argument that the foundation model providers will not win everywhere still holds for me. Focus and specialization still matter and are dispositive.

But that is no longer the right question.

The new central question is whether vertical AI vendors can win against the rest of the world armed with powerful, general-purpose agents. You can outrun three to five giants, but can you do the same against an army of weaponized customers and developers?

Nicolas Bustamante, the founder of Fintool and co-founder of Doctrine, recently made the case that LLMs are systematically dismantling the moats that once justified vertical software’s premium multiples. If you do not have proprietary data that cannot be scraped or synthesized, regulatory lock-in, or network effects, then general-purpose reasoning agents will eat your lunch. It’s a great synthesis, and every vertical player should take it to heart.

I agree that the best vertical startups will have those moats. But a lot of enterprise software will be bought from startups that do not fit neatly into that framework, and some will be enduring businesses.

Here is why — and the answer has everything to do with where the barbarians actually are.

The Threat Is Inside the Building

The conversation about AI disrupting software usually imagines the threat coming from outside. But the more immediate and chaotic threat comes from inside the enterprise itself. General-purpose agents are now powerful enough that anyone in an organization can build one. A marketing manager spins up an agent that pulls customer data. A junior analyst automates a reporting workflow without anyone reviewing the logic. Three departments independently build agents that interact with the same CRM, creating conflicts no one anticipated.

For an enterprise, this is both beautiful and frightening. For CISOs, CFOs, and Chief Risk Officers, it’s mostly frightening. They will not sign off on a world where hundreds of ungoverned agents run loose across the organization.

And that is exactly why enterprises will buy software — not just to do the work, but to impose the structure, governance, and coherence that makes AI-powered work safe and reliable at organizational scale. The barbarians are not just at the gates. They are inside the building. And that is the problem enterprise software has always existed to solve.

The Answer: Packaging Complexity

Enterprises do not buy features. They buy solutions — and solutions require design, orchestration, governance, security, and accountability. Capability alone is not a deployable enterprise solution.

#1 Design addresses how humans and agents interact. It is paramount yet uncharted territory. SaaS codified enterprise processes into software. But one of the most profound changes coming with AI is that enterprises will move from buying automation to buying outcomes. Those who argue that workflow is dead are directionally correct, but incomplete. In its place, we will need well-designed agentic workflows that manage the handoffs between agents and humans — and those workflows will be reimagined from scratch around outcomes.

It’s early. Most startups are still wedging in with discrete task automation tackling the jobs to be done. That is smart for now and an easier sale to enterprises, but ultimately not enough. The saying “your mess for less” was common in Business Process Outsourcing (BPO) because BPO firms rarely re-designed and improved enterprise processes. Inserting Agent X for this task and Agent Y for that one, but doing the job the same way, will not create long-term winners.

Instead, AI startups need to begin with an outcome-design mindset. Consider commercial lending. A startup thinking in terms of task replacement would first gather all the borrower data, then have an agent automate the financial spreading and wait for a human to review, and finally have an agent create an underwriting memo and wait for a human to edit. A design built around outcomes will take advantage of the 24×7, scalable agent capabilities and create a real-time, iterative conversation with the borrower. Agents could request data as needed to qualify borrowers, show the borrowers how the lender will model their credit worthiness and match them with loan products, and allow the borrower to change variables like loan rate, points, or term. At any point, the borrower could request to speak with a loan officer, and when they do, the agents would prepare the loan officer with notes, recommendations, best next steps, etc. If this saves the loan officer 10 hours per loan, all of that can be spent on relationship building, cross-selling, and ensuring the customer gets the most value from the lender relationship.

Design will be the most durable form of domain advantage. General-purpose agents will probably, eventually learn every domain. An agent can learn the rules of commercial lending or insurance underwriting. But knowing the domain is not the same as knowing how to redesign the work. Designing the right interaction between agents and humans — where to automate, where to hand off, where to keep a human in the loop not for compliance but because it genuinely produces a better outcome — requires the kind of judgment that only comes from deep, sustained focus on a problem space. That’s not a knowledge gap. It’s a design gap.

Get the agent-human interaction design right, and you will have an early advantage that compounds. Reflecting on the birth of ecommerce, Amazon nailed the checkout flow while countless merchants had obtuse, high-friction checkouts. The underlying capability was the same, but Amazon’s design of the end-to-end experience created an early competitive advantage that compounded. Seems obvious now, but it was not at the time.

#2 Orchestration is about how agents work with each other. Any meaningful enterprise process involves multiple agents — one that extracts data, another that analyzes it, another that drafts a communication, another that checks compliance. Someone must decide the architecture: which agents manage the workflow, when to use specialized agents, and when to invoke a skill versus spinning up a separate agent. Think of it like staffing an investment team — you need a leader who knows when to pull in the tax expert, the industry analyst, or outside counsel, in what order, with what context passed along. Knowing the industry vertical and the function is critical to optimizing specialist agents vs. general-purpose agents, pre-built integrations vs. as-needed API calls, and agents vs. humans. All of this will affect cost, reliability, and speed.

#3 Governance means the policies, approvals, and controls that determine who can deploy an agent, what it is allowed to do, what happens when they are duplicative, how decisions are reviewed, and the imposition of security and data requirements. In financial services, a model that generates investment recommendations may need to be validated, documented, and approved before it goes live. Some payments may be initiated by agents; others require human approval. In healthcare, an agent might read the radiology report, and even provide the results, yet not have authority to order prescriptions.

#4 Security in the enterprise is table stakes. It means data isolation, access controls, audit trails, and compliance with industry-specific regulations like HIPAA, SOX, or GDPR. A general-purpose agent can be powerful, but an enterprise buyer needs to know exactly what data it can access, who can see its outputs, and how to prove that to a regulator. Security may not strongly favor vertical software over foundation model providers in all industries, but it can in industries with industry-specific regulations like healthcare, financial services, and public sector.

#5 Accountability means having a throat to choke. When an agent makes an error that costs money or creates risk, enterprises need a vendor who owns the outcome. They need SLAs, incident response, and a product team that understands the domain well enough to diagnose what went wrong. A general-purpose agent does not come with a customer success team that knows your industry.

The companies that package all this together — the design, orchestration, security, governance, and accountability — are building something that a general-purpose agent with plugins simply does not replicate. Packaging complexity is a real and enduring source of value.

Vertical Software Players Can Succeed, But the Race Is On

This case for packaging complexity IS the defense of software, and especially of vertical software that brings domain knowledge to every decision. However, it’s not yet clear how enterprises will buy and deploy all this needed governance, security, and accountability.

Three categories of players are competing for the enterprise AI stack.

Foundation model providers. Anthropic, OpenAI, Google are solidly individual productivity tools today, but the trajectory makes clear they are moving towards this orchestration layer. Anthropic shipped Cowork in January, added plugins two weeks later, then added enterprise connectors, private plugin marketplaces, and admin controls two weeks after that. And the February launch explicitly featured orchestration across Excel and PowerPoint — context flowing between tools, not just a human chatting with an agent. The pace is extraordinary and moving toward the orchestration layer. What keeps them from being the default orchestration layer – risk of model lock-in for one. But some buyers will accept that.

Purpose-built horizontal orchestration platforms. Stack AI, Thread AI, Copilot Studio posit the enterprise wants a single neutral orchestration layer across all business functions: visual workflow builders, multi-agent coordination, governance dashboards, deployment infrastructure. This looks a lot like how enterprises have bought for decades, and frankly it is hard to imagine not having some layer like this because enterprises need to manage complexity across all their functions.

Vertical software vendors — Harvey in legal, Fazeshift in accounts receivable, Abridge in healthcare — these kinds of players own the domain expertise, workflow design, and customer relationship for a specific function. This is the category that needs to change the most and get the packaging right to survive. The best will absorb security, governance, and orchestration into their own products because their customers will demand it.

Realistically, all three will find buyers in the enterprise along lines of size/scale and technical sophistication. JPMorgan will build a lot more software in-house than it did before because the cost of doing so will fall. They will absolutely have their own horizontal orchestration platform. Small and midsize companies like a community bank or domestic manufacturer will buy a lot of individual vertical software products and need orchestration built in.

These are genuinely open architectural questions. What I believe is that vertical vendors are best positioned to solve the hardest part: designing and packaging the domain-specific work that produces outcomes. Whether they build, buy, or integrate the horizontal infrastructure is a strategic question each will answer differently. But domain expertise comes first, and that is not something a horizontal platform or foundation model can easily replicate.

Conclusion

Making the case for vertical startups may look crazy right now. That’s fine. The foundation model providers are building governance, orchestration, and enterprise packaging at remarkable speed, and the window for startups is not infinite. But the high-probability scenario is that the greatest problem to be solved is the hard, domain-specific work of designing how agents and humans should interact, how agents work with each other, and how all of it operates safely within the constraints of a real enterprise. That work favors the focused over the general. The opportunity is decades long, but the window to establish yourself is right now.