Ten years ago, a seed-stage startup needed a product, a team and a pitch deck to raise capital. Today, that’s just the start. Technology and strategy have become inseparable, each fueling the other, and the rules that once defined success have quietly shifted under everyone’s feet.

Last month, my firm reviewed more than 2,500 inbound applications. Here are the key shifts we’re seeing in the startup ecosystem at the seed stage.

Broadening capital strategy

Equity is a powerful tool for building high-growth companies. But it’s no longer the only option. Non-dilutive growth capital is increasingly playing a strategic role for companies with revenue visibility and clear ROI channels.

For example, we recently financed a company with $1 million in growth capital it needed immediately to expand its team and infrastructure. Raising that through equity alone would have likely taken months, with significant time and execution cost along the way.

We’re now writing financing checks like this on a near-weekly basis.

Distribution focused

Leading with a “better” product isn’t enough to propel growth. The breakout companies are investing in building stronger distribution systems — aka what founders refer to as “traction.” Distribution is a critical moat for early-stage startups. Rapid scaling is no longer achieved by launching new products; it’s through distribution loops.

Distribution is something startups can now architect intentionally with social platforms, marketplaces and other ecosystems. One of the most common founder mistakes we see is delaying the distribution strategy until after the product launch. At that stage, the architecture is harder to retrofit. Strong startups design distribution before they scale their product.

For example, some of the fastest-growing startups now design their products around existing ecosystems from day one — building apps that tap into merchant marketplaces, AI tools distributed through or Teams integrations, or fintech products embedded directly into banking and payroll workflows. In many cases, the distribution channel becomes more valuable than the underlying product itself.

One of the most common mistakes we see is founders postponing distribution strategy until after the product is built. By then, the architecture is far harder to retrofit. The strongest startups design distribution into the company before they scale the product itself.

Learning over speed

“Move fast” is often dolled out as the best startup advice. Operating in a fast-paced environment remains a strategic asset, but it is not enough to maintain a competitive advantage.

Everyone is fast. It’s no longer a unique attribute. Instead, learning velocity is becoming the defining advantage in early-stage startups. How quickly can you reduce uncertainty? Competitive edge is achieved not by executing blindly, but by closing knowledge gaps faster than everyone else. Execution without learning equals wasted motion.

The founder focus advantage

Last year, my team reviewed close to 25,000 applications for our investment funds and bespoke accelerators. The ones that stand out are the companies doing the fewest things exceptionally well. The most-fundable companies can describe their business in one tight sentence. They can also defend exactly what they are not doing.

Disciplined constraint is one of the highest-leverage traits in venture-backed companies. When we review applications, this pattern consistently stands out.

When a company is focused, the residuals compound: stronger early retention, faster iteration cycles, cleaner capital deployment. In a capital-selective market, focus compounds faster than ambition.

Based on tens of thousands of applicants, close to 82% of the ones that stayed in business a year later had a strong go-to-market foundation in their deck. GTM is built on agility and learning fast.

AI as infrastructure, not experimentation

There’s no lack of interest in AI. But there is an implementation problem. We’ve seen companies struggle when AI is approached as experimentation rather than architecture. Rather than bolting tools onto already fragmented stacks and workflows, designing intelligent systems should be mapped from the ground up.

More than 78% of the founders applying to today are leveraging AI in at least one way in their startup.

The most successful playbook combines execution with operational clarity and emphasizes infrastructure over experimentation. We’ve seen successful implementations that center around two practical paths. The first is validation, with rapid prototypes and identifying market signal opportunities before investing in a full build. The second is system, designing and integrating custom AI agents directly into operating workflows for revenue-generating companies facing operational complexity. Both are required to move AI agents from concept to capability. A disciplined system design often matters more than flashy tooling.

Marketing is the moat

Marketing execution is one of the largest performance gaps we see across early-stage startups. Startups lose when they don’t distribute fast enough once there is something worth selling. Marketing is the propeller for the distribution engine.

Most startups fail at marketing because it is a business function that becomes a founder hustle with support from one junior hire. But breakout growth requires process, cadence and accountability. That’s not achievable without an experienced team and clear plan.

One of the biggest mistakes founders make is treating marketing as something that starts after launch. Founders must create unique strategies, test them and then analyze what works and what doesn’t. From there, they must keep iterating and creating to unlock the most product-market fit and traction.

If we see classic strategies in a pitch deck, it is an auto-reject. And beyond being unique, your strategies must have been tested by your team.

The key is simple: Test ideas early, measure what actually works, refine aggressively and scale the strategies that compound over time.

, a serial technology entrepreneur since age 12, is now a value-driven venture capitalist with a track record of backing more than 1,000 startups across the globe. He is a co-founder and general partner at , one of the world’s most active venture capital firms. Before becoming involved in venture investing, he built and scaled into the world’s largest debate-focused social network and edtech platform, reaching millions of users and serving students across more than 500 school districts, colleges and universities.

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Startups across sales, marketing and customer management have raised $7.5 billion so far this year, according to ���ϳԹ� data. The largest rounds span everything from advertising and customer data to sales software, e-commerce and customer support — reflecting just how many companies are still trying to build a better way to market and sell.

The broad trend: Investors are making far fewer bets on sales and marketing startups than immediately before and after the COVID-19 pandemic, but they’re still writing checks into the space.

Unsurprisingly, AI-focused companies are capturing a much larger share of funding than during the prior peak, with most sales, marketing and CRM investment going to companies in ���ϳԹ� AI-related categories.

The numbers: So far in 2026, startups in sales, marketing and CRM have raised $7.5 billion globally across 830 funding rounds, ���ϳԹ� data shows. At the current pace, funding could finish near the $9.3 billion raised in both 2023 and 2024, although potentially below last year’s $11.1 billion. Deal volume, meanwhile, is on track to fall for a fourth consecutive year — pointing to a market where investors are putting more money into fewer companies.

Funding in recent years remains far below past levels. In 2022, for example, funding in the sector topped $27 billion, and in 2021, it totaled nearly $41 billion.

Notable deals

The year’s largest funding recipient so far was, which raised more than $1 billion in a June Series E from , , and . The San Francisco-based marketing measurement company, whose products now include AI agents that analyze marketing data and automate tasks, was valued at $2.7 billion.

Restaurant financing and rewards platform announced $450 million in new capital in February. The Austin-based company did not identify a lead investor or disclose a valuation.

In January, AI-native customer service company raised a $350 million Series D led by . The Berlin-based company develops AI agents that handle customer conversations by phone and other channels. The financing tripled its valuation to $3 billion.

Meanwhile, , an online marketplace for digital products, communities and courses, received a $200 million strategic investment from in February. The deal valued the New York-based company at $1.6 billion.

Another larger deal went to Dubai-based property listings platform , which announced a $170 million equity investment in January. The company uses AI in products including home valuations and tools that help real estate agents improve and prioritize listings. led the deal, with participation from another UAE sovereign wealth fund and existing investor . The company did not disclose a valuation.

On Sept. 9,�� AI-powered sales automation startup announced it had raised a $115 million Series D at a $7.1 billion valuation. This was more than double the $3.1 billion valuation it achieved when it raised a $100 million Series C in August 2025. Wellington led the latest round, with participation from , , ’s a16z Perennial wealth management arm, , and others. The company says the raise followed 4x revenue growth in 2025. It also told ���ϳԹ� News that it’s on track to hit $200 million in ARR this quarter, and $240 million by the end of the fiscal year.

Exits

The sector has produced one notable public offering, but most exits are coming through acquisitions as larger companies buy specialized sales and marketing products to add to their existing platforms, ���ϳԹ� data shows.

, a Redwood City, California-based mobile advertising and app-marketing company, began trading on the in June. It initially sold 19 million shares at $23 each, raising $437 million. The IPO valued Liftoff at $3.83 billion, based on the outstanding shares disclosed in its IPO prospectus.

There have been a number of M&A deals this year in the sector, too, though in most cases, the acquisition price was not disclosed.

The largest known deal was Dutch payments giant acquisition of , a Berlin-based loyalty and promotions platform, in July for about $880 million. Talon had previously raised over $120 million in venture funding.

Other startup M&A deals in the marketing and sales arena in 2026 include:

• In July, acquired Seattle-based sales intelligence startup to add information about prospective buyers to its sales products.
• In June, agreed to acquire , whose software helps companies identify and contact people visiting their websites.
• Sales platform acquired , which helps sales teams identify prospective customers based on product use and other signals, in March.
• acquired the Estonian startup , whose software connects sales and marketing data, in August.
• acquired India-based marketing intelligence startup in September through a team and technology deal.

Funding is down from peak years, but it’s clear investors haven’t lost interest in sales and marketing startups. However, they are putting more money into fewer of them. Companies that help businesses find customers, increase sales, or retain existing business are still landing big checks and attracting buyers. But with acquisitions far more common than IPOs, a public-market exit remains much harder to come by.

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As a partner at Menlo Park, California-based venture firm Norwest, Jacobsohn focuses on enterprise software, drawing on his background in finance, sales and business development. His 15 active portfolio companies range from pre-revenue startups to businesses generating more than $300 million in revenue. Much of his portfolio falls within finance and HR software, although he also invests in supply chain and construction technology — often in companies building finance applications for those industries.

The common thread, he explained, is a focus on next-generation business applications taking on entrenched providers that have struggled to keep up. Jacobsohn has found particularly fertile ground in finance, where companies already have software budgets and many categories remain dominated by aging systems.

Norwest, founded in 1961, manages $15.5 billion and is investing out of its 17th fund, a $3 billion vehicle raised in 2024. Over time, the global venture and growth equity firm has backed more than 700 companies in sectors spanning enterprise, consumer and healthcare.

In an interview with ���ϳԹ� News, Jacobsohn discusses where he still sees openings in the crowded market for finance software, how far companies should trust AI with accounting work, why HR startups may be better off attacking the secondary products of large platforms, and why he tests a CEO’s sales ability before investing.

The interview has been edited for clarity and brevity.

���ϳԹ� News: The office of the CFO is an area where you’ve invested fairly extensively. Why is there still so much room for startups when finance software is already such a crowded market? Where is the opportunity right now?

Jacobsohn: I’m focused a lot on companies that are disrupting legacy players, and there are a lot of legacy players in the office of the CFO. We had more than 500 companies on our Office of the CFO market map, and probably three-quarters of those are legacy players.

What’s interesting about finance is that the CFO approves all software purchases across the organization, but CFOs also buy software for themselves. There’s actually one less layer of approval when they’re buying their own software, so it is a little easier to replace it when they’re the direct buyer.

I’ve found a lot of opportunities in both finance software that sells to every industry and software focused on specific industries. I’ve invested in a lot of horizontal applications, and so far the vertical solutions have been in construction and manufacturing. We’ve also invested in the healthcare space, but that’s not my area of focus. I’m also looking at companies in transportation and logistics.

Are there specific finance workflows that still strike you as surprisingly manual and therefore more ripe for disruption?

Jacobsohn: I actually think most workflows have been automated, but some are being automated by legacy solutions. Some could still be on-premise. Some could be companies making the transition from on-premise to the cloud that are still very legacy. You might even call them SaaS 1.0, because a company can be considered legacy and be only five to 10 years old now that a lot of the new generation is AI-native.

Every company wants to buy AI-native products these days. Some legacy companies have done a better job of reinventing themselves, and others are having more difficulty. Since most everything has been automated by someone, I’m focused on new-generation disruptors of legacy solutions.

What are some of the areas you think are ripe for disruption?

Jacobsohn: I have a portfolio company in some of these categories, and not in others.

One area where I do not have a company is ERP. I think there’s a potential opportunity to disrupt and Those companies have been around for a very long time. I’m seeing more disruption downmarket, and some of these companies will eventually move upmarket.

I think sales tax is another category with some ancient legacy players where there’s an opportunity to disrupt them. Treasury management also has some very old legacy players. Another area I’ve invested in is procurement.

Finance is particularly sensitive when it comes to accuracy and audits. Is that affecting how much work companies will actually hand over to AI agents, especially in accounting?

Jacobsohn: We think about this a lot. Finance people are risk-averse, and they need consistent answers. There’s some concern that there could be errors with AI, and there are.

It’s important to infuse AI into your finance products, but you have to be careful about what you’re giving AI to do. You don’t want AI doing calculations because it is not good at math. There are certain workflows it can handle where it doesn’t produce precise numbers. But when you need precision, accuracy and calculations, you can’t rely on AI for that.

In Norwest’s recent , you mentioned that categories including payroll, benefits and workforce management can be difficult to disrupt because of the time and expense associated with switching. If a startup wants to take business from Workday or ADP, how can it make switching more enticing?

Jacobsohn: I think it would be very hard to disrupt the core products of Workday, , SAP, and Dayforce. But it’s easier to disrupt some of their secondary products, where the category isn’t their core business. Those companies have really good distribution. Often, the best distribution wins, not necessarily the best product.

Workforce management is a category I’ve invested in through . UKG has a product in the space, but it started as an on-premise company and moved to the cloud. We’ve been a cloud-native AI player, and we’ve done well against it in the market.

Another company I invested in that complements these players is , which is in the benefits space. What’s interesting to me is that I worked at WageWorks, a legacy player in the space. Elevate is disrupting my old employer. Benefits isn’t the core business of the suite players I mentioned, but it’s a big enough market where a specialist can do well.

That’s how I look at it: What are some big markets where suite players aren’t putting much effort behind the product because they can only focus on so many things at once?

Is AI making it easier or harder to build a durable software company? Features and products can be built faster, but they can also be copied faster.

Jacobsohn: I do think it’s making it easier to build companies. We’re going from products that store data and automate some workflows to really smart solutions that understand, predict and execute work for you. It’s changing employees’ jobs. Employees can focus on higher-value work and automate some of their tasks with agents that can work really quickly.

As for whether anyone can vibe-code something, I think if you’re building a simple horizontal workflow for small businesses that isn’t very complex, it could be easy to build the product yourself, or it could lead to a lot of competition.

If you’re building something complex for the midmarket or enterprise, something that needs deep domain expertise or something vertical in nature, any of those areas would be really hard for a lot of people to build internally or for too many startups to compete in. Those solutions would also be really hard to maintain. I’m not seeing much competition from people wanting to build internally at my portfolio companies that are focused upmarket, where you need deep domain expertise.

The IPO market has improved, but it certainly isn’t where it was. How does the current exit environment affect what you’re willing to fund today, if at all?

Jacobsohn: It doesn’t impact our interest in funding. Our primary entry point is seed and Series A. I’ve done some Series B and C deals, so we can be opportunistic at the later stage.

We’re focused on backing entrepreneurs with deep domain expertise who are going after big markets with legacy players ripe for disruption, and we don’t worry about the exit environment. At some point, the IPO market will open up more, and maybe that will help us in the future. But more companies get acquired than go public.

I do want to invest in a company that, if it executes well, someday has the option to go public. But I’m realistic that most companies get acquired before that can happen.

How do you feel about an acquisition as an outcome?

Jacobsohn: You have to support your entrepreneurs and what’s in their company’s best interest. M&A can be a very good outcome, especially since we come in so early. If a company is acquired for less than $1 billion, it still could be a great outcome for us and the company.

The challenge is entering late, at a valuation above $1 billion. Not many companies will acquire another company for billions of dollars. We like to come in early so that if a company sells for less than $1 billion, which is where most buyers have budgets, it can be a really good outcome.

Is there a fundamental belief you have about funding or building startups that you think other investors might disagree with?

Jacobsohn: Something that’s different about me from most VCs is that I come from a sales background, and I think the CEOs I back need to be good at sales.

Just about every CEO I back comes from a product and engineering background, but that’s not enough. You need to be good at selling. You need to sell to customers, partners, investors and employees. Before I invest, I’ll go on a lot of sales calls I set up with the CEO to see how good they are at selling.

To me, that’s a big way of assessing the potential of a company.

Have you ever passed on a CEO or startup because you felt the founder didn’t have strong sales skills?

Jacobsohn: Yes. When I go on sales calls and people aren’t interested in a second meeting, and that’s a consistent theme, it often leads me to walk away.

Tell me about your Failure Museum. What are some of the biggest findings you’ve learned in building out the Failure Museum?

Jacobsohn: I have built a that includes more than 1,500 items from failed companies and products. I have them all on my website, where I study why they failed.

People are eager to share their successes and their failures. The museum evokes more optimism than one might think. People shouldn’t be afraid to take risks. Failure can be a springboard to success.

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After pausing his entire engineering team’s workload for two weeks to ship a requested fix, he discovered the effort made no difference. The customer still threatened to churn.

“We did a retro, and wouldn’t you know? The person who’s asking for the new request was the new decision maker [we] didn’t even realize existed,” said Kataria, co-founder and CEO of San Francisco-based , in an interview. “We missed the fact that the prior person had left, and the context had shifted hands, and no one had tracked that.”

That breakdown planted the seed for Centralize, an enterprise sales platform emerging from stealth today alongside a $15 million Series A funding round led by (NEA).

The financing includes participation from ,1 , , Ritual Capital, Adverb Ventures and high-profile angel investors including former co-founder and , CEO and founder of .��

Combined with a previous $4 million seed round led by Salesforce Ventures, Centralize has now raised $19 million since its 2023 inception to build what Kataria calls a “deal GPS” for enterprise revenue teams.

Engineered by Big Tech vets

Kataria and co-founder and CTO met more than a decade ago as engineering students at the .��

Both went on to build high-scale products across Big Tech. Kataria served as a founding engineer on Facebook Shops during e-commerce push during COVID-19, scaling the platform from zero to a quarter billion monthly active users in a year. Wang, meanwhile, created Slack Huddles, building the initial version alongside Slack executives (CTO), (VP of product), and Butterfield (CEO), and later leading engineering and product teams at Slack.

After honing their technical chops in big tech, Kataria joined Y Combinator-backed fleet card startup as a product tech lead. It was there, while working closely with go-to-market teams to save that churning enterprise customer, that he recognized a fundamental gap in modern revenue operations.

“It was just this sea of information that no one had a handle on. The deal was at risk because the relationship is what mattered most, and we didn’t have a handle on it,” Kataria told ���ϳԹ� News in an interview. “One of the things that we always say is that the one thing AI can’t commoditize is relationships.”

Solving the ‘multi-threading’ problem

Founded through Y Combinator’s Winter 2024 batch, Centralize aims to fix what Kataria describes as a lack of an actual relationship layer in modern sales platforms.

After bringing its primary product to market in December 2024, Centralize focused heavily on “multi-threading,” or the practice of identifying, engaging, and organizing all necessary stakeholders high and wide within a target company, from procurement and legal up to the C-suite.

Rather than acting as a static record, Centralize operates as a visual, multiplayer surface centered around automated org charts that function like a map. AI agents analyze first-party data, call recordings, emails, calendar events, and web sources to continuously construct a live picture of key relationships.

“It’s kind of like a deal GPS,” Kataria explained. “Or like a visual map, in which the people are the map. It’s the puzzle pieces. It’s basically like a landscape of who we know, who’s missing, how we get there, and then it’s the turn-by-turn navigation.”

Centralize’s AI assistant is named “Centra,” and answers questions such as “Who owns the budget?” or “How do we approach the CRO?” in seconds, the company claims. It also flags the moment a champion leaves, a new decision-maker joins, or engagement drops on a key deal.

Besides proactively flagging missing stakeholders, such as empty leadership seats or unengaged decision-makers, the platform also identifies warm entry points through mutual connections or past company overlaps.

Rapid growth and a bottoms-up launch

Centralize charges enterprise revenue teams based on “accounts under management” with unlimited seats, encouraging cross-functional teams, including account executives, sales development reps, and customer success managers, to collaborate on account maps in real time.

The approach is driving rapid momentum. Over the past year, revenue has expanded significantly, driven by adoption among fast-growing enterprise companies.

“Since last year, we’ve… almost 8xed the company in revenue,” Kataria said, noting that much of that momentum accelerated over recent months.

The startup’s client roster features notable tech names, including , , , , , and .

To accelerate expansion, Centralize is launching a free, single-player tier alongside its funding news. The move allows individual account executives to sign up, build real-time account maps, and introduce the platform organically to executive leadership.

, venture partner at NEA, noted that the investment in Centralize was driven by the founders’ “unique” vision and execution.��

“Rachit and Will have built something rare: a product that sales teams actually want to use, not just another system of record they’re forced into,” she wrote via email. “We led Centralize’s Series A because we saw a founding team with an unusually sharp read on how AI changes the day-to-day of enterprise sales.”

Koplow-McAdams also noted that buying committees have nearly doubled in size over the last decade. “The entire revenue tech stack was built around activity capture, rather than navigating buying committees,” she added. “That’s a structural gap, and it’s only widening as AI raises the stakes.”

Startups like Centralize that bring AI to bear on enterprise marketing and sales have seen a strong uptick in funding this year, ���ϳԹ� , with 2026 on pace to beat last year, which was the strongest year for venture investment into startups related to sales, marketing and CRM technology since 2022.

 

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1. Salesforce Ventures is an investor in ���ϳԹ�. It has no say in our editorial process. For more, head here.↩

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Last month, of , the corporate venture arm it launched in 2016 and grew to more than $850 million across three funds. The company hired to explore selling portfolio stakes on the secondary market, putting positions in companies such as and in play. The news also arrived weeks after .

Two corporate venture programs shutting down inside six weeks invites speculation that corporations are retreating from venture capital, but in fact the opposite is true.

Measured in dollars, corporate venture has never been stronger. According to , corporate investors participated in — venture’s strongest funding year since 2021.

, , , , and all led billion-dollar rounds into AI companies last year, per ���ϳԹ� data. Nvidia by itself made more than 40 startup investments and appeared in. Meta paid $14.3 billion for its stake in Scale AI. 1��and s venture arm backed Anthropic’s.

Amid this strength, though, corporate venture is also quietly splitting in two, and the proof is buried inside the record numbers. Bain attributes the elevated corporate participation , and the billion-dollar rounds trace back to the same short list of names.

Take that handful out of the data and the year looks very different. Venture capital itself went through the same sorting over the past decade, as mega-funds absorbed more and more of the capital while everyone else competed for allocation, and corporate venture is now following the same script. The people with the most at stake are the smaller funds and startups downstream.

And notice that the wind-downs are coming from serious programs. PayPal’s arm ran for a decade and , and Fidelity International manages hundreds of billions of dollars. Size never protected either one, and the dividing line runs through the mandate. For Nvidia, Alphabet, Salesforce and Cisco, startup investing is a core strategy, funded off enormous balance sheets, because their businesses depend on owning a position in the technology cycle. Nvidia backs the companies that build on its chips, and that commitment survives budget season. For most other corporations, venture is one strategic priority among several, competing for capital with the core business itself.

To be clear, there’s nothing wrong with that. When a new chief executive commits to finding , winding down even a well-run program can be the disciplined call, and disciplined capital allocation is what shareholders ask of public companies. Corporate venture has always moved in cycles, and the waves of closures after 2000 and 2008 said far more about parent balance sheets than about the returns on offer. Individual programs are mortal, but the asset class keeps growing.

When I started my career, technology drove roughly 2% of the American economy, and today it drives a double-digit share of GDP and nearly 40% of the stock market.

Who feels it first

For smaller funds and their portfolio companies, the split is already changing the math. ‘s finds corporate funds pursuing fewer, more targeted deals, and the share using the secondary market jumped from 15% in 2024 to 22% in 2025; PayPal’s Jefferies mandate takes that same path at the scale of an entire program.

When a corporate arm winds down mid-life, its portfolio companies lose a strategic backer and a source of follow-on capital at once, the smaller funds that syndicated alongside it lose their anchor for the next round, and a secondary sale replaces a committed partner with a financial buyer.

I spend my days working with early-stage venture funds, and I’m watching this pattern develop in real time: strong companies outside AI, with a departing corporate backer on the cap table, heading into rounds their existing syndicate can’t fill alone.

The lesson for startup management teams and VC fund managers is to plan for corporate capital to come and go. The pro rata rights that funds hold in their best companies become most valuable at exactly these moments, when a strategic investor steps back and ownership in a breakout company becomes available to whoever can fund it.

Smaller funds should line up committed follow-on capacity before their winners come back to market, so a corporate partner’s exit becomes a chance to buy more of a company they already know well. Founders should run the same exercise from the other side of the table and know today which investors on their cap table can carry the next round.

Corporate venture will keep growing because the forces behind it keep growing, and programs will open and close along the way, as they always have. What’s changed is the sorting: permanent capital consolidating at the top of the market, and everyone else learning to plan around that fact. The funds and founders who prepare for it will come out the other side owning more of the companies that matter.

is the founder and managing partner of , a growth-equity firm that co-invests in venture-backed companies by leveraging the unused pro-rata rights of more than 1,000 early-stage VC partners.

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But then you ask the only question that really matters: “Why are the numbers improving?”

That is where the actual strategic discussion begins.

Was growth improving because the company found a repeatable sales motion, or because it offered large discounts? Was retention strong because the product became deeply embedded in customer workflows, or because renewals had not yet come under pressure? Was gross margin structurally strong, or were infrastructure costs simply being pushed into the future?

Metrics and KPIs are useful. They give us a snapshot of the business. But they do not shine a light on strategy. They are the result of strategy — or sometimes the result of a lack of it.

Here are three areas where founders and boards should look deeper into unit economics and the strategies behind them.

LTV/CAC: Look at the quality of acquisition

LTV/CAC is one of the most important SaaS metrics. A strong ratio usually suggests the company can acquire customers efficiently and retain them profitably. But two companies can both report a 4x LTV/CAC ratio and still be very different businesses.

One may reach that ratio because it has strong positioning, low acquisition costs through partner programs, viral marketing, high retention through workflow integrations, and expansion revenue from additional products or services. Another may reach the same reported ratio because it charges higher upfront prices, assumes a longer customer lifetime, or has not yet seen churn show up in the data. On paper, both look efficient. In practice, one may have a healthy acquisition engine while the other may be relying on assumptions that still need to be proven.

When reviewing LTV/CAC, boards should ask:

• Is the company clearly positioned?
• Is it focused on the right customer segment?
• Are customers coming from scalable channels or expensive paid acquisition?
• Is pricing strong enough to justify the sales effort?
• Do we have cross-sell and upsell opportunities baked into the offering?
• Is the payback period reasonable?

A weak LTV/CAC ratio is not always a sales problem. Sometimes it is a positioning problem, a pricing problem or a market-selection problem.

GRR and NRR: Understand why customers stay

GRR and NRR are critical because they show whether customer revenue stays and expands. But they do not explain why customers stay or expand. Strong dollar retention usually comes from becoming embedded in the customer’s workflow.

The product delivers fast time-to-value, integrates with important systems, becomes part of a daily process, and becomes difficult to replace.

That is when expansion becomes easier. More seats, more usage, more modules, more geographies, more products. This is why setting a board goal to “increase NRR” is not enough. The real discussion should be around onboarding, integrations, product depth, customer success, pricing tiers and expansion paths.

Dollar retention improves when the product becomes more valuable, more embedded and more scalable within each customer.

Rule of 40 and Rule of 4: Check the quality of growth

ARR growth matters, but the board should ask what kind of growth it is. The Rule of 40 shows whether the company is balancing growth and profitability.

But a better number can come from real efficiency, or from cutting too deeply into product, customer success and future growth. The Rule of 4 adds a simple durability check: ARR growth divided by annual customer churn should be above four. If it is low, growth may be hiding a leaking bucket.

So the board should ask two questions:

Are we becoming more efficient, or simply underinvesting?

Are we growing on top of a loyal customer base, or replacing customers we should have kept?

Let’s use these metrics to dive deeper into the core long-term strategy.

is a strategic adviser to tech companies, investors, CEOs and boards, specializing in strategy, growth and M&A. He is a guest contributor to ���ϳԹ� News and a university lecturer on strategy, finance and entrepreneurship. Learn more at and connect with him on .

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

This week, most of the largest U.S. startup funding rounds centered around the sector one would suspect: artificial intelligence. This was true for the week’s largest venture financing, a $1.5 billion Series F for AI inference technology provider , as well as a majority of rounds in the Top 10. Beyond that, the next-biggest area for startup funding was biotech.

1. , $1.5B, AI inference technology: Baseten, a provider of systems software to run AI applications workloads, raised $1.5 billion in Series F funding, its fourth fundraise in 18 months. , , , and co-led the round, which set a $13 billion valuation for the San Francisco-based company.

2. , $1B, digital marketing: AppsFlyer, a San Francisco-based provider of data analytics with digital marketing as a core use case, reportedly secured more than $1 billion in a Series E funding round at a post-money valuation of $2.7 billion. Backers reportedly include , , and .

3. , $650M, AI inference technology: San Francisco-based Groq closed on $650 million in new funding led by and that it says will be used to scale its AI inference cloud technology and infrastructure. The investment comes just over six months after an acquihire-type transaction in which hired away its founder and key team members and licensed its technology.

4. , $330M, ophthalmic therapies: Ollin Biosciences, a developer of therapies for vision-threatening diseases, picked up $330 million in Series B funding. and led the financing for the Austin-based company.

5. , $320M, foundational AI: General Intuition, developer of a foundational AI model based on gameplay, secured $320 million in Series A funding at a $2.3 billion valuation. led the financing for the New York-based company, while backers including and participated.

6. , $250M, government software: Peregrine Technologies, provider of a platform used by public safety agencies and other government entities, secured $250 million in Series D financing. , , , , and led the financing, which set a $6.8 billion valuation for the San Francisco-based company.

7. (tied) , $200M, risk intelligence: Palo Alto, California-based Quantifind, developer of a risk intelligence platform for financial crime detection and national security operations, closed on $200 million in growth financing led by .

7. (tied) , $200M, foundational AI: San Francisco-based Mirendil, a frontier lab building systems that excel at AI R&D, says it raised a seed round of $200 million led by and . The startup also counts as a backer.

9. (tied) , $190M, AI infrastructure: AI networking infrastructure startup Upscale AI raised $190 million in Series A extension funding, bringing total financing to $500 million. led the round, which set a $2 billion valuation for the Santa Clara, California-based company.

9. (tied) , $190M, biotech: San Francisco-based Osanni Bio, a therapeutics platform focused on ophthalmic therapies and other treatments, secured $190 million in Series B funding led by .

Large non-US deals:

The week also brought some large European rounds:

, $569M, defense tech: Berlin-based defense tech startup Stark reportedly raised $569 million in a financing led by and .

, $546M, insurance: Paris-based health insurance startup Alan secured $460 million in new investment in primary and secondary equity led by .

Methodology

We tracked the largest announced rounds in the ���ϳԹ� database that were raised by U.S.-based companies for the period of June 18-26. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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The company is a marketing analytics platform that acts as an independent referee of sorts to track which digital ads actually drive mobile app downloads and in-app purchases. It helps companies measure their return on ad spend while claiming to protect user privacy and block ad fraud.

While AppsFlyer CEO and co-founder declined to comment on specific deal details, he did confirm to Axios that , , and each took a minority stake in the San Francisco-based startup.

AppsFlyer’s most recent raise before this was in 2020. With the latest round, the company has now raised $1.3 billion in known funding since its 2011 inception, per .

Previous backers include , 1, , and .

“They believe what we believe: that attribution and measurement must be independent, unbiased and trusted,” Kaniel was quoted as saying of AppsFlyer’s newest investors. “As AI takes over more of how advertising gets bought and optimized, the signals feeding those systems become the most consequential infrastructure in the industry.”

He added that the company is eyeing the public markets, calling the financing “a step on that path.”

So far in 2026, companies in sales, marketing and CRM categories have pulled in around $4.1 billion globally in seed- through growth-stage funding, per ���ϳԹ� . That puts the space on track to come in roughly flat with or a bit up from the prior three years — when annual funding hovering around the $8 billion mark — though still far below boom-era levels, when sales and marketing investment topped $20 billion. Notably, many of the startups funded in recent quarters have been AI-focused, with many of them offering agentic tools and automation in areas such as sales, marketing and customer experience management.

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For more than a decade, customers spent their software budget procuring vertical SaaS products. ACVs, or annual contract values, were modest, customer acquisition cost had to stay below a ceiling, and the resulting go-to-market playbook was product-led growth, SDR-led and content-driven.

With AI, many products are no longer SaaS but usage and outcomes based. They are replacing labor, not software. At my investment firm, , we call this new category of companies vertical AI. Vertical AI spend doesn’t just come from a customer’s software budget. It often comes out of headcount as well, a much larger line item. As a result, ACVs have jumped meaningfully to 6- and 7-figure deals.

I’ve written before about how AI for vertical SaaS, and how the value framing shifted from subscription pricing to. As ACVs have grown in vertical AI, the go-to-market motion is changing too. We’ve explored tactics to drive a more efficient sales process.

Here, I’ll explore how the channels are changing as well.

Why direct sales is back

Direct sales has historically only worked at true enterprise scale. The cost of an AE’s time wasn’t warranted for smaller ACVs. Below a certain deal size, the math didn’t work for high-touch sales. That’s why SaaS GTM became PLG and SDR-led.

With vertical AI ACVs frequently landing in the 6- or 7-figure range, founders now have room to invest meaningfully in winning each logo. We’re also seeing these smaller businesses spending relatively more with quicker sales cycles which is enabling higher volume.

AEs, in-person sales motion, and other tactics that didn’t pencil at scale under old SaaS economics now do. Direct sales now works further down market where prior SaaS economics didn’t allow it.

Two channels in particular have driven a lot of distribution and success for vertical AI companies recently. They are distinct from each other but we’ve seen companies have success with both.

No. 1: Private equity and heads of AI

Many PE firms are actively pushing their portfolio companies to drive efficiency with AI. Some have even created a new role internally to spearhead these initiatives. These AI partners are often tasked with collecting and disseminating learnings, finding good AI tools, and connecting them into the portfolio if there’s a fit.

The motivation is sometimes EBITDA driven, but can also be softer than that. Many of these execs are focused on adding value across the portfolio, helping companies build AI competency, and coming up with an execution plan.

The decision making structure also varies. Sometimes the and push adoption down to the portfolio. More often, the firm will forward information to relevant company executives and leave the decision making to them. If executed well, this can be a very efficient channel for vertical AI companies. One introduction to the PE firm surfaces many qualified leads across their portfolio companies.

Usually, companies will land one customer initially. Positive feedback then travels in two directions. Laterally to peer companies within the portfolio, and back up to the PE investor, who introduces the vendor to others in the portfolio. We’ve seen this be particularly successful in industries where rollup strategies are popular like healthcare services, dental, MSP, accounting, legal, financial advisory, insurance brokerage, home services and industrial.

No. 2: Conferences

We’ve also seen sector and function specific conferences be incredibly valuable in driving distribution for vertical AI companies. The advantage is concentrated attention and self selection by the right buyer. Buyers are captive and open to learning.

They come to these events curious to hear what’s new in their sector. Attendance allows companies to meet the right buyer, showcase the product live, and collect leads at scale. Sponsoring and attending dinners is another opportunity to meet prospects.

I’d argue that scalability of lead generation and brand awareness matters more now than ever. That requires getting the word out about your own company but also cutting through the noise of others in the market. Buyers are actively building out their AI strategies so vertical AI companies should be sprinting on GTM. Companies need to be top of mind when potential buyers are open to evaluating new tools.

Whether that becomes a sole source decision or an RFP, the prerequisite is being part of the consideration set. In order to do that, your buyer needs to know you exist, and this is a great way to spread the word efficiently.

What this means

The GTM playbook for vertical AI now looks meaningfully different from the SaaS playbook it grew out of. Distribution, pricing and sales motion have all shifted in tandem, with each piece reinforcing the others. Buyer pull justified larger ACVs, larger ACVs justified deeper investment in the sales motion, and the new economics opened up channels that didn’t work under the old model.

The companies pulling away are the ones pairing a great product with the right GTM motion. They have recognized that bigger ACVs demand a different playbook, and they have adapted before their peers.

When the gates of distribution opened, everyone walked through. The companies winning now have figured out what to do once they were inside.

If you’re a founder building vertical AI and rethinking GTM, I’d love to hear from you.

�� is a general partner at , where she invests in and partners with early-stage founders from inception through Series A across sectors including AI, fintech, healthcare and enterprise software. Prior to joining Defy, Agarwal spent seven years at and began her investing career at . A former founder and operator, she previously co-founded two startups and started her career at

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led the round, which included participation from , , , , and others.

Founded in 2020, New York-based Capchase initially made a name for itself by providing revenue-based financing for SaaS companies. However, by late 2022, the company began to evolve into its current iteration: a vendor-financing technology platform. Capchase embeds itself directly into the sales workflows of companies such as original equipment manufacturers, software vendors and cybersecurity providers.

It has entirely discontinued its revenue-based financing, and instead now focuses on B2B buy now, pay later tools that help software and hardware vendors offer flexible payment terms while getting paid upfront.

The concept addresses a longstanding friction point in enterprise sales: vendors want cash immediately, while buyers want to preserve capital. Rather than forcing a buyer to pay $1 million upfront in 30 days, Capchase allows a sales rep to offer more flexible terms — say, $15,000 per month for up to five years. When the deal is signed, Capchase pays the vendor the full amount upfront, net of a financing fee.

“We started to see that there was a very big pull in the market,” , co-founder and CEO of Capchase, said in an interview. “We saw that sales cycles were expanding, CAC was going up, and all of this was driven by the high interest rates. Buyers wanted to pay as late as possible and pay installments.”

He added: “We shipped a product quickly to solve that need, and we started to get very strong market pull to the point that that ended up eclipsing the other product lines, and we decided to focus everything there.”

Displacing a legacy market with AI

The pivot has unlocked impressive growth. Capchase says it has a 400% growth rate over the past 12 months and forecasts another 200% growth in the upcoming year. Its workforce has scaled alongside this momentum, expanding to 75 employees, up from 50 a year ago.

While legacy banks, independent financing firms and captive financing arms have dominated the $1.3 trillion equipment financing market for decades, Capchase says it differentiates itself by replacing 1980s-era workflows with real-time automation.

Traditional financing approvals often require an email-driven back-and-forth that can take four to 17 days, according to Fernandez. Capchase claims to compress that timeline into seconds.

Capchase uses artificial intelligence and machine learning agents across its platform. For example, an “order generation agent” parses uploaded quotes or purchase orders to create flexible payment links in under 60 seconds — down from a manual process that typically took eight hours — according to Fernandez. As another example, an AI email agent automatically handles multiparty coordination between vendors, resellers and buyers, all without human intervention.

“What makes us different is that we are both the lender and the technology. And AI is what makes the combination work at the speed enterprise tech sales demands,” Fernandez told ���ϳԹ� News in an interview. “We built the credit decisioning engines that allow us to look at all the data these other players look at as well, but we were able to do it and infer it in just seconds.”

Moving upmarket and expanding globally

The new capital will primarily support Capchase’s rapid transition into the enterprise space.

“In the past 24 months, we went from serving vendors in the tens of millions of revenue to in the last 12 months in the hundreds of millions in revenue, and now in the multiple billions of revenue,” Fernandez said.

The startup’s platform now underwrites more stable, established borrowers. The average buyer utilizing Capchase has roughly $80 million in annual revenue, has been operating for over 20 years, and is profitable, he added. This profile has allowed Capchase to maintain a highly controlled risk environment and what he described as a “spectacular” default rate.

Capchase currently supports hundreds of tech vendors and tens of thousands of buyers. Its customer roster features enterprise tech giants, public cybersecurity firms and massive distributors, including , , , and .

Though Capchase keeps its specific financials, valuation and cumulative funding figures confidential, Fernandez confirmed that the latest capital injection represents a valuation step up from its 2021 $80 million Series B round. At the time of that raise, the company had raised more than $400 million in equity and debt.

Looking ahead, Capchase will use its fresh capital to scale beyond its core markets in North America — the U.S. and Canada — and Europe, including the U.K., Ireland, Belgium, Netherlands, the Nordics and Spain. Driven by direct demand from its enterprise partners, the company is officially entering the Australian market this year.

Reducing friction with flexible terms

, co-founder and managing partner of 01 Advisors, said he was drawn to Capchase primarily because of how AI has helped it disrupt traditional vendor financing.

Incumbents possessed plenty of capital but “have never been forced to build real technology because their customers had nowhere else to go,” he wrote via email.

AI fundamentally shifts this dynamic, allowing Capchase to “underwrite a buyer and create accurate docs in 30 seconds,” he said.

This solution hits close to home for Bain, who previously ran the sales team at and says he intimately understands the friction Capchase aims to eliminate. In traditional enterprise sales, momentum frequently stalls when a ready-to-buy customer hits a roadblock over payment terms, forcing sales leaders to either “discount to close, wait for the next budget cycle, or spend weeks negotiating.”

Those outcomes drain margin or time. Capchase completely removes that friction, Bain said, by offering instant approvals and flexible terms.

Fintech startups, particularly those that apply AI to traditionally manual or burdensome processes, have benefited from increased investment in recent quarters. Global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per ���ϳԹ� . That’s a more than 29% increase from 2024’s total of $41.6 billion raised.

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