SaaS Fundraising in 2026: Can a Non-AI Company Still Raise?

Yes, a non-AI SaaS company can still raise in 2026, but the proof bar is higher. More than 60% of venture dollars on Carta in Q1 went to AI, yet the median non-AI Series A priced at $55 million post-money, and only 11.4% of rounds were down rounds, the lowest in nearly four years.¹

I work with founders in the four industries I go real deep in: technology (AI and SaaS), healthcare and biotech, pharma, and pharmacy. This piece is for the SaaS founder who has a product and paying customers, no model of their own, and an investor asking about AI. I am not a CPA and the firm performs no attest work, and I do not give investment advice, so I describe the market and the decision stays yours. Every company number below is made up (illustrative, not a client) unless I cite it.

Picture a founder walking into a Series A meeting with $3 million of ARR, retention above 100% and a product that has no model in it. The partner across the table closed an AI round last week, and her first question is about your AI strategy. That question is the market in one sentence. By the end you will know what the data says, what to put in front of the investor instead, and what a lower price costs you.

Venture money is going to AI, and the share depends on who is counting

Mostly to AI, and the share depends on who is counting. Carta's own data says "More than 60% of all venture capital raised by companies on Carta in Q1 went to AI companies."¹ Fenwick's Venture Beacon, which draws on Carta data, puts the record share at 61%,² and Crunchbase has AI-driven startups at 64% of global venture dollars in the third quarter.³ In SaaS specifically, Carta found 83% of capital went to AI companies across the fourth quarter of 2025 and the first quarter of 2026.⁴ The PitchBook-NVCA Venture Monitor is higher still. Its H1 report puts AI at $355.9 billion, or 86% of all venture dollars, and its Q1 report put it at 88.8%.⁵⁶

Why do the numbers sit about 25 points apart? They count different things. The PitchBook-NVCA total includes the frontier labs. Rounds of $100 million or more made up 87.5% of the $412.7 billion deployed in the first half, and every deal below that line drew $51.4 billion among them.⁷ A news summary of the same data says over 81%, which is why I used the report's own figure and not the summary.⁸ My take is that for a typical raise of $5 million to $15 million, the useful number is the one that leaves out the mega-rounds. It still says AI took most of the money. I would just not read 86% as the share of startups that are AI.

The bigger risk is what the chart does to founders. At TechCrunch Disrupt in October, Index Ventures' Jahanvi Sardana said of founders: "It feels like [founders are] deciding what to build based on what's getting funded, which is really scary"⁹ I would take that warning seriously. A SaaS company that bolts a model onto its product to match the funding chart has changed what it sells to fit somebody else's market.

The valuation gap is wide at the top and narrow where SaaS companies raise

Wide at the top and much narrower where most SaaS companies raise. A post-money valuation is what the company is worth right after the new money goes in, so an investor's share is the check divided by it. Here is the Carta Series A comparison for Q1 2026, which is the cleanest AI versus non-AI table I found. The last two rows are my arithmetic from Carta's figures.⁴

Read that table before you read any headline. A non-AI Series A at $55 million sits about 18% below the applied AI median of $65 million. The enormous gap is the $300 million for foundation model companies, and no SaaS founder is raising against them. PitchBook-NVCA shows the same shape in deal size: the AI median is 12.5% higher at Series B and 7.5% higher at Series C, and only at Series D and later does it jump, to 56.7% higher.¹⁰ In my book the honest summary is a modest premium for applied AI, a very large one for the labs, and a gap that is still widening.

That last part is the warning. In a section it sponsored in the report, J.P. Morgan wrote: "The market's bifurcation is also reflected in a widening gap in valuation premiums between AI and non-AI companies."⁶ ICONIQ's September report sorts public software the same way. It says "The gap between high-growth, AI-forward companies and incumbent software companies is widening into two distinct tiers."¹¹ Its numbers have public software companies growing 20% or more at a median 9.2 times forward revenue in Q2 2026, against 2.7 times for slower ones.¹¹ The consequence reaches private rounds. SaaStr's Jason Lemkin tells founders their next fundraise will be priced off public comps, after software forward earnings multiples fell below the S&P 500 in early 2026.¹² Tomasz Tunguz noted last October that public SaaS multiples had barely left a narrow band since the 2022 crash.¹³

Down rounds are rarer now, and I still plan for one

They are less common than they were, and I would still plan for one. The down-round rate on Carta fell to 11.4% in Q1 2026, the lowest in nearly four years, from 22.2% in Q1 2024.⁴ An average is no comfort when you are the company in the 11.4%, so here is the back of the napkin on what price does, on illustrative numbers (not a client). Say a SaaS company raises $7 million, the Carta median Series A round for a non-AI company. At a $55 million post-money, the investors own 12.7%, which is $7 million divided by $55 million. At $40 million they own 17.5%, and at $30 million they own 23.3%. A founder who owns 60% before the round keeps 52.4%, 49.5% or 46.0%. Going from $55 million to $40 million moves about 5 points of the company to the investor, and going from $40 million to $30 million moves almost 6 more.

Carta's 2024 study of more than 9,600 US software priced rounds found the median company sells about 20% at seed and again at Series A,¹⁴ so I treat 12.7% as the good version of the story, not the base case. The price is also only one line of the term sheet. If a company later raises at a lower price, earlier investors with anti-dilution protection get more shares to make up part of the difference. Brad Feld, explaining term sheets, writes that "the most common anti-dilution provision is based on the weighted average concept"¹⁵, which counts how many shares sell at the lower price and not only the valuation, while a full ratchet reprices all of the earlier stock to the new, lower price.¹⁵

I learned to read terms from the receiving end. When I worked in the accounting department of a specialty pharmacy, a private equity group bought the company, did what private equity does and cut middle management, and I left along with a pharmacist who asked me to help build a new pharmacy from concept. About 4.5 years later that company sold to private equity too, and I had no equity in either exit. That is why I tell founders to read who gets paid first before they read the valuation, and to model the exit at today's price and at a lower one.

Investors want proof the business works without a story attached

Proof that the business works without a story attached, and the investors are fairly direct about it. CRV's July guide to the KPIs VCs track says "Capital efficiency and path to profitability have replaced growth rate as the primary investor filter"¹⁶ outside of AI mega-deals.¹⁶ Justin Gray, writing in Fast Company in July, makes the same point from the revenue side: "Revenue was once a late-stage expectation, but it is now table stakes."¹⁷ On size, CRV puts a competitive B2B SaaS Series A at roughly $2 million to $5 million of ARR.¹⁸

Here are the 4 numbers I would lead a non-AI SaaS deck with, and the bar each one has to clear. First, burn multiple, the cash you burn for each new dollar of ARR. CRV says investors expect it to fall below 2.0x by Series A.¹⁶ I wrote the long version in What Is a Good Burn Multiple for a Startup?. Second, net revenue retention. CRV's Series A ranges treat 100% as a baseline, 110% to 120% as competitive and 120% or more as premium.¹⁸ SaaS Capital's survey shows why it matters, because growth is positively and exponentially correlated with it.¹⁹ The other metrics investors ask before a raise are in the SaaS metrics investors ask for.

Third, gross margin, which is the number an AI company cannot copy. CRV notes AI native companies typically run 50 to 60 percent gross margins against 70 percent or more for traditional SaaS,¹⁶ and Bessemer's math is that the gap between an 80% and a 60% gross margin cuts the value of a business by at least half.²⁰ If you run a traditional SaaS product, I would put gross margin on the second slide of the deck. Fourth, CAC payback, which CRV puts at around 20 months for typical private SaaS companies.¹⁶ Investors will still ask about AI, and I would answer with numbers and not a slide. ICONIQ's survey of software builders has AI products growing from 32% of revenue in 2025 to a projected 42% this year, so your competitors are adding it.²¹ If you add a feature, price it, measure its gross margin and show the revenue it earned. If you do not, say which customer problem you chose to solve instead.

I would never invent an AI story to raise

No, and I would say so even in a friendlier market. My take is that a story you cannot support is the most expensive shortcut in this market, and there is a documented case. The SEC's April 2025 complaint against Albert Saniger, founder of the shopping app Nate, alleges he told Seed and Series A investors the app used automated technology that "relied on AI to complete purchases made through the app without human involvement"²² and that it relied in large part on contract employees to enter orders by hand.²² The SEC adds that he raised over $42 million. The Justice Department's parallel release alleges the app's actual automation rate was effectively zero percent, and notes that the defendant is presumed innocent.²³ Those are allegations as of April 2025, and I have not checked how the cases ended.

Debevoise's partners wrote that the care companies should take with investor-facing materials applies to startups and smaller private companies raising outside the public markets.²⁴ I would rather a founder tell an investor plainly that the product is not AI and show the retention and the margin than make a claim the diligence team will test and the books cannot support. That is why I want every number in a data room tied to a source document. For the process, see what diligence looks for in a fundraise.

A priced round is not the only door

There are four other doors, and I would look at all of them before choosing. The first is a bridge or extension from existing investors. Carta's report notes that bridge rounds make up more rounds than capital invested across stages.⁴ The second is venture debt, and it follows equity. Founderpath, a vendor that sells alternative financing, says facilities usually run 20% to 35% of the latest equity round, at roughly 8% to 15% a year, and that nearly every lender requires an institutional equity round with a named lead investor.²⁵ Treat those as one vendor's ranges. PitchBook says venture debt reached $64.7 billion in the first half but was spread across just 280 loans, with a single $20 billion refinancing accounting for much of it, so that headline is not your market either.⁷

The third door is a slower, profitable path. AngelList's Avlok Kohli says the standard is relative: if your growth is not among the best of its batch, fundraising will be brutally competitive, and founders who want a profitable, steady company should not raise venture capital.²⁶ M13's Morgan Blumberg expects many successful startups to be built on only one or two rounds of capital.²⁷ The fourth is a sale or growth equity, and the Fast Company column above says a company with over $2 million of ARR and a path to profitability has those options open.¹⁷ I launched Island Waters on July 1 and funded it myself, so I have lived the profitable path. It is slower and I set the pace, and that is a trade I would ask any founder to price before they shop a term sheet. I would run the 13 week cash flow with the raise and without it before answering any offer.

Your industry changes the plan

For an AI company the premium is real and the margin question comes first, so start with AI Gross Margin: Why Yours Isn't 80%. For a biotech or pharma company, Fenwick says healthcare, biotech, consumer and edtech remained comparatively more moderate than AI on round size and valuation,² so I would build the plan on milestones and runway, not on the AI chart. Through a High Rock Accounting engagement, I served as the sole accountant on a clinical-stage biopharmaceutical client's month-end close, owning its preclinical, clinical, manufacturing and general accruals through its Nasdaq IPO. For a pharmacy, I would expect inventory and payer reconciliations to carry the weight, and that is my instinct from over a decade across two specialty pharmacies, not data.

If you only do 4 things after reading this, do these, in this order, and bring the answers to your next investor meeting or board call:

1. Price your own round at three valuations. Run your raise at your best case, a middle case and a hard case, and see what you keep before a term sheet arrives.
2. Lead the deck with four numbers. Burn multiple, net revenue retention, gross margin and CAC payback, each tied to your books.
3. Decide your AI answer in advance. A feature with revenue and margin, or a reasoned no. Never a claim you cannot support.
4. Run the 13 week cash flow with and without the raise. Know your runway on the profitable path before you answer an offer.