This tracker includes layoffs conducted by U.S.-based companies or those with a strong U.S. presence and is updated at least bi-weekly. We鈥檝e included both startups and publicly traded, tech-heavy companies. We鈥檝e also included companies based elsewhere that have a sizable team in the United States, such as , even when it鈥檚 unclear how much of the U.S. workforce has been affected by layoffs.

Layoff and workforce figures are best estimates based on reporting. We source the layoffs from media reports, our own reporting, social media posts and , a crowdsourced database of tech layoffs.

We recently updated our layoffs tracker to reflect the most recent round of layoffs each company has conducted. This allows us to quickly and more accurately track layoff trends, which is why you might notice some changes in our most recent numbers.

If an employee headcount cannot be confirmed to our standards, we note it as 鈥渦nclear.鈥�

Meanwhile, on Monday, details from AI giant 鈥檚 IPO prospectus, giving potential investors a peek into its financials.

Oura had planned to offer 50 million shares at $40 to $44 apiece and was expected to begin trading Wednesday. At the top of that range, the offering would have raised $2.2 billion. The company says it is delaying the deal despite strong demand and has not set a new date. CEO said Oura has 鈥渢he luxury of choosing our moment.鈥�

Anthropic is still moving toward an IPO, although its timing remains unclear. A prospectus leaked by Reuters showed that revenue climbed twelvefold to nearly $4.6 billion in 2025 with an operating loss of $8.06 billion. Its staggering nearly $42 billion net loss included roughly $34 billion in accounting charges tied largely to earlier financing.

The document also outlined an eye-watering $518 billion in future cloud, computing and infrastructure obligations. Reuters has reported that a listing is likely to come after the November midterm elections.

Anthropic, the world’s most valuable venture-backed startup, has indicated it plans to beat rival to the public markets. The company could debut as soon as October and raise up to $100 billion via the offering, according to a recent in , while OpenAI, which Reuters says filed confidentially in June, is reportedly now looking toward early 2027.

(颁谤耻苍肠丑产补蝉别鈥檚 predictive intelligence tools, meanwhile, point to a slightly longer timeline for an Anthropic IPO, saying it鈥檚 more likely to happen in six to 12 months.)

Who鈥檚 next

So far, the 2026 IPO class already has a record-setting headliner in .

There are some other candidates. -backed AI cloud provider filed publicly this month , reporting $140.6 million in first-half revenue and a $1.02 billion net loss. , a -backed specialty insurance underwriter, on Sept. 24.

Neither has announced a trading date.

Data center operator is another possible fourth-quarter entrant. Reuters that it had hired banks for an IPO that could raise as much as $10 billion, although the timing remains subject to change.

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From January through August U.S. tech layoffs reached at least 94,046, up 16.8% from 80,486 in the same period of 2025. Interestingly, and unsurprisingly, many of the cuts came as tech companies redirected spending toward AI and restructured operations to reduce costs.

The year started off on a busy note on the layoff front. After job cuts dropped sharply in December 2025 to 5,151, they surged in January to over 20,000. May was particularly brutal. The month drove the year-to-date increase, recording 31,513 layoffs 鈥� including 鈥檚 8,000-job reduction 鈥� the highest monthly count since March 2023, when layoffs reached 36,602.

Recent months indicate a slowdown. Layoffs fell each month after May, reaching 2,347 in August. Overall, June-August 2026 layoffs totaled 19,331, down 16.2% year over year. The decline suggests recent easing, though it is too early to establish a lasting reversal.

Artificial intelligence has become a much more common explanation for layoff decisions, noted , founder of AI was cited in 33% of tech layoff events this year, up from just 1% in 2024. His tracker attributes 92,913 layoffs globally, or 72% of this year鈥檚 total, to AI.

鈥淭here鈥檚 been little evidence that AI is actually replacing the work of the human employees let go,鈥� Lee said of this year鈥檚 largest AI-attributed layoffs. He believes established tech companies are spending heavily on AI and cutting costs elsewhere, hoping to increase productivity with smaller workforces.

Companies cutting

This year, we鈥檝e seen a number of Big Tech and publicly traded companies, as well as startups, make deep cuts.

But interestingly, as with last year, public tech companies have dominated layoff headlines in 2026 so far, led by and Meta.

鈥淏ig companies [have] made up about 87% of everyone laid off in 2026, which is similar to last year, when they made up 85%,鈥� Lee said.

Amazon accounted for 17,388 cuts this year so far through August. Those included a 16,000-worker RIF announcement in January and several smaller subsequent rounds. Meta was next with 10,400 layoffs, including an 8,000-job reduction carried out in May that represented 10% of its workforce.

and recorded the next-largest totals, letting go of 4,800 and 4,760 employees, respectively. , and each recorded 4,000 layoffs, followed by with 3,000, with 2,900 and with 2,600. Notably, the Top 10 list spans a variety of sectors, including cloud computing, social media, payments and enterprise technology.

We should also note that according to reports, 鈥檚 workforce fell by about 21,000 employees in its fiscal year ended May 31, 2026, but the worker count and exact timing for each of聽 those reported cuts was unclear, so we did not include that total in our tracker.

Among privately held companies in the tracker, recorded the largest disclosed total at 1,000, followed by HR software provider with 950 and with 500. Those figures were substantially smaller than the largest public-company reductions, although undisclosed layoff counts limit comparisons between the two groups.

And in early September, reportedly laid off 3,300 workers, or 10% of its workforce.

An AI focus

, of , says AI is affecting jobs in two ways. Some work, including coding, can now be done with fewer people. 鈥淭here are jobs that are literally being replaced by artificial intelligence,鈥� he told 兔子先生传媒 News.

But companies are also changing their priorities. They鈥檙e putting more money into AI and cutting teams working on other parts of the business. 鈥淭hey鈥檙e letting people go from one area of their organization while they might even be hiring in an area that is focused on AI,鈥� Challenger said. That鈥檚 why a company may lay people off and advertise new jobs at the same time.

Tech has announced more job cuts than any other industry this year, Challenger said. Across the U.S. economy, layoffs are down somewhat from last year, though that comparison is skewed by the large number of federal job cuts in 2025. When compared with the period just after the pandemic, when employers struggled to find workers, layoffs remain elevated.

Few companies outside tech have blamed job cuts on AI so far, Challenger said.

It鈥檚 not all negative though, in his view. There’s potential upside for programmers, he said. If AI makes software less expensive to build, companies in other industries might embark on projects they couldn鈥檛 afford before. That could mean new jobs outside tech, though it鈥檚 too early to know whether those jobs will make up for the ones being cut.

Also, it appears that some companies might be regretting their layoff decisions. Amazon is reaching out to eligible former employees about open roles across the company, including in its cloud-computing and AI businesses, according to a聽 report.

Methodology

Layoffs figures are from The 兔子先生传媒 Tech Layoffs Tracker, where we record reported job cuts at U.S. tech employers. The tracker includes layoffs conducted by U.S.-based companies or those with a strong U.S. presence 鈥� both privately and publicly traded 鈥� and is updated at least bi-weekly. Layoff and workforce figures are best estimates based on reporting. Actual layoff figures are likely much higher than reported as many companies do not disclose the number of jobs cut when announcing layoffs. For more about our methodology for tracking layoffs, refer to the tracker鈥檚 methodology section.

Related reading:

• The 兔子先生传媒 Tech Layoffs Tracker

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U.S. venture-backed technology聽1 companies have secured nearly $90 billion in domestic public offerings this year, per 兔子先生传媒 data. That鈥檚 already the second-highest annual tally on record, and we鈥檝e still got a few months to go.

However, virtually all the money went to two companies. alone accounted for 83% of the $90 billion raised this year, while AI infrastructure company scooped up another 6%. A potential offering from , meanwhile, could be even bigger.

The remaining field is comparatively modest. Just 21 other venture-backed technology companies went public this year in sizable or offerings 2, per 兔子先生传媒 data. Collectively, their offerings, which include traditional IPOs and SPAC deals, pulled in less than $10 billion.

This small cohort is intriguing for what it excludes as well as what it includes. Enterprise software, long a staple industry among venture-backed IPOs, was essentially a no-show this year. Energy, defense and space tech, by contrast, were well-represented. We also saw smaller offerings from other sectors, including medical devices and consumer-facing startups.

Here are some of the key findings in more detail:

Energy powers the most IPOs: About a quarter of this year鈥檚 tech startup offerings hail from the energy sector. The largest of these was from geothermal energy provider . Several nuclear power-focused startups also made their debuts, including and , developers of small modular nuclear reactors, as well as , focused on advanced nuclear fuel.

A dash of quantum, defense, aerospace, devices and consumer: Beyond energy, quantum computing company delivered one of the year鈥檚 larger debuts, as did equipment rental platform . Defense tech and aerospace were also strong performers, with offerings from satellite intelligence provider and spacecraft developer . And on the consumer front, e-bike and scooter platform finally made its market entrance, albeit at a valuation below its one-time .

An IPO SaaS-pocalipse: But what about SaaS? Mostly MIA. The paucity of enterprise software offerings this year isn鈥檛 entirely surprising given the impact of AI on the sector. VCs are pouring capital into a newer generation of AI-first platforms in legal tech, accounting and other enterprise software sectors. Existing SaaS unicorns are also moving fast to incorporate more AI in their offerings.

One end result is there are an awful lot of SaaS unicorns and former unicorns that have concluded this year is not the time to pursue an IPO.

Winner-takes-almost-all

Another end result is that investment returns are looking more concentrated than ever.

Of course, winning big or not at all is far from a new thing in the startup world. Tech venture returns have always been propped up largely by a few enormous wins, with the remainder of portfolio companies producing either losses or smaller profitable exits. But lately, the winner-take-almost-all-the-IPO-proceeds tilt is more pronounced than ever.

The pipeline of tech companies that have filed for future IPOs doesn鈥檛 offer much consolation that this pattern will change. Giant potential market debuts from Anthropic and still dominate IPO chatter. Enterprise SaaS offerings do not.

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One of the strangest things about the current AI cycle is just how fast the math changes for the people building it. You can be a 20-something founder who feels like you are still in the warm-up phase of your career, yet on paper your equity is already life changing. Or a mid-level engineer who went from holding startup options to staring at a substantial personal balance sheet practically overnight.

The gap between life experience and the sudden reality of managing serious wealth is widening as AI-native companies reach major valuations faster and private company liquidity arrives earlier.

A of more than 3,400 founders and senior leaders across 20 countries found that AI-native startups are reaching billion-dollar valuations in about 3.5 years, roughly half the time it took before generative AI. They are doing it with about half the staff.

We have seen an even more compressed version firsthand. We recently advised founders who went from launching their company to a major liquidity event in less than a year.

When the money outpaces the mindset

For decades, tech wealth followed a more predictable script. Significant personal wealth often accumulated alongside a long career. Equity vested over years, responsibilities grew and additional grants often followed. If everything went right, an acquisition or IPO marked a visible transition into a very different financial reality.

Today, that boundary is much less clear. AI capabilities allow companies to grow at a much faster pace.

A young founder can suddenly face questions that used to come much later in life. What are their long-term personal goals? What should the new capital be used for? What does financial independence mean for someone who may still be figuring out what they want their life to look like?

These are not always questions that can be answered overnight.

Compounding this is the fact that one doesn鈥檛 have to wait for an IPO to de-risk. Tender offers and secondary transactions allow founders and employees to turn part of their equity into cash while the company remains private.

Take as an example. While still only 3 years old, the company authorized a $100 million secondary sale for staff at a $6.6 billion valuation. By February 2026, it had at an $11 billion valuation.

For someone inside a company moving at that speed, the sequence can look very different from the traditional startup script. It is a dizzying loop of grants, valuations and a sudden liquidity window. All of this can happen long before an IPO.

Flexibility is the name of the game

A sudden liquidity event can make financial independence a realistic goal. It may make buying a home possible, even while someone is still single or has no idea where they want to live long term. It may allow them to take care of parents or fund another entrepreneurial chapter.

The pace of these cycles can also be contagious. Opportunities seem to be everywhere. At the same time, a founder may still be taking substantial risks with the current venture and have very little idea what life will look like in five years.

When we advise technology executives and founders in this position, we try to leave room for several possible paths while the broader picture is still developing. Some capital may eventually support long-term family security. Some may need to remain available for opportunities or life changes that do not exist today.

A future business endeavour, a career change, a relocation to another country, or other less conventional ideas can change the picture again. Some of these moves can be made today, but others need time to develop.

A company may compress 10 years of growth into three, but people cannot compress 10 years of life into three. Ignoring that gap is where real risk can build.

Valuations and liquidity can move incredibly fast. Decisions about family wellbeing, security, career and the future still move at a human pace. Your financial architecture needs to respect the difference.

is co-CEO of , where he works with founders, senior technology executives and families on wealth strategy, liquidity events and long-term financial planning. Before moving into wealth planning, he spent many years in the technology industry and writes about the intersection of technology, equity and personal wealth.

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Startups across sales, marketing and customer management have raised $7.5 billion so far this year, according to 兔子先生传媒 data. The largest rounds span everything from advertising and customer data to sales software, e-commerce and customer support 鈥� 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鈥檙e 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 兔子先生传媒 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, 兔子先生传媒 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鈥檚 $11.1 billion. Deal volume, meanwhile, is on track to fall for a fourth consecutive year 鈥� 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鈥檚 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,聽 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 , , 鈥檚 a16z Perennial wealth management arm, , and others. The company says the raise followed 4x revenue growth in 2025. It also told 兔子先生传媒 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, 兔子先生传媒 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鈥檚 clear investors haven鈥檛 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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The highest-valued new entrants were China-based humanoid robotics business , valued at more than $6.3 billion; San Jose, California-based photonics company , valued at $5.5 billion; and Palo Alto, California-based AI model platform , and San Francisco鈥檚 semiconductor manufacturing startup , both valued at $5 billion.

AI software featured prominently across model training, assistants, agentic and enterprise workflow automation, coding and voice transcription.

Semiconductors was the second-largest sector, with five new unicorns. Robotics and financial services each added three, while data centers, security and energy each added two.

The U.S. accounted for 16 of August鈥檚 new unicorns. China followed with four. South Korea, India, Singapore, the United Arab Emirates, Switzerland, Germany and Turkey each added one. Nigeria and Indonesia also each added one new unicorn 鈥� for both, their first new unicorn of the year.

Nine companies exited the 兔子先生传媒 in August, per 兔子先生传媒 data: Three that went public 鈥� the most notable being 鈥� and six via acquisition, including , and .

New unicorns in August

Here are August鈥檚 new unicorn companies:

AI and software

• , a Palo Alto, California-based platform for training, fine-tuning and deploying custom AI models based on proprietary data, announced $1.1 billion in funding led by and . The less-than-1-year-old company, founded by former co-founder , was valued.
• San Francisco-based , an AI assistant that executes personal tasks, raised a $250 million Series B led by and . The 1-year-old company was valued at $2.5 billion.
• Shanghai-based , a builder of agents for digital and physical environments, raised a $220 million seed round led by and . The less-than-1-year-old company was valued at $2 billion. Its founder, , a researcher, left earlier this year.
• San Francisco-based , which builds AI-powered voice-writing and meeting-transcription tools, raised a $280 million Series B led by , who also led its Series A in 2025. The 5-year-old company was valued at $2 billion.
• San Francisco-based , which provides AI-powered code review and change-management tools, raised a $143 million Series C at a $1.5 billion valuation. and co-led the round. The 3-year-old company said it would commit more than $10 million to keep its tools free for open-source projects over the next year.
• San Francisco-based , which deploys AI agents across calls, email, documents and enterprise systems, raised a $150 million Series C at a $1.2 billion post-money valuation. and led the round. The company is 4 years old, started in logistics and has expanded to insurance, energy, telecommunications and airlines among others and counts 150 enterprise customers.
• Turkey-based , a developer of consumer mobile applications, raised a $50 million Series A led by . The 4-year-old company was valued at $1.25 billion. Its apps include AI chatbot Nova, diagnosing plants with PlantApp, and art generator DaVinci.

Semiconductors

• , a San Jose, California-based developer of photonic interconnects for AI computing infrastructure, raised a $700 million Series C at a $5.5 billion valuation. , , , and led the round. The 2-year-old company is already deployed within data centers.
• raised $400 million in funding led by hedge fund . The 1-year-old company was valued at $5 billion. The San Francisco-based company creates tooling for semiconductor manufacturing and was founded by researchers.
• South Korea-based , which develops edge AI processors for on-device inference, raised about $29 million in the first tranche of its Series D funding from existing investors. The 8-year-old company targeting robotics and electronics was valued at about $2.2 billion.
• Shanghai-based , an AI chip startup for inference, raised a Series A led by local state capital investors and . The 4-year-old company was valued at about $1.5 billion with plans to ship its product in Q4 2026.
• Santa Clara, California-based , which develops low-power silicon and software for AI data centers and physical AI, raised a $110 million Series A led by . The 4-year old company was valued at more than $1 billion.

Robotics

• China-based , which is building the general-purpose IRON humanoid robot, raised more than $900 million in its first outside financing at a post-money valuation exceeding $6.3 billion. led the round, with participation from and support from and Alibaba Group. The company, a subsidiary of public smart electric vehicle company , is 10 years old.
• Singapore-based , which develops robots to operate in real-world environments, raised about $669 million in funding. The 2-year-old company was valued at about $3.3 billion and is set to deploy robots in a Dairy Queen in Shanghai to handle the entire 55-step process of taking orders, preparing the food and handing it to a customer.
• Zurich-based , which develops autonomous technology for heavy construction machinery, raised a $200 million Series A led by . The 4-year-old company was valued at $1 billion and works across multiple construction brands.

Financial services

• Bengaluru-based , a financial-services company spanning payment, lending and insurance, raised $100 million in funding led by . The 7-year-old company was valued at $1.3 billion.
• Berlin-based , a finance AI platform for European mid-sized businesses to聽 manage spend, card issuing and expenses, raised a $40 million Series C led by and . The 7-year-old company was valued at around $1.15 billion. The company says it has 5,000 businesses that use the service to give finance teams control.
• Palo Alto, California-based , an AI-native enterprise resource planning platform for accounting, raised a $100 million Series C led by . The 4-year-old company was valued at $1 billion.

Aerospace and defense

• Los Angeles-based , a manufacturer of autonomous military drones and counter-drone systems, raised a $250 million Series C at a $2.5 billion post-money valuation. and the co-led the round. The company is 3 years old. Neros has contracts with the U.S. military as well as half a dozen allied countries.
• Mountain View, California-based , which builds and operates satellite constellations for national security, civil and commercial customers, raised a $250 million Series C led by . The 5-year-old company was valued at $1.5 billion.

Data centers

• Palo Alto, California-based , a vertically integrated AI infrastructure platform, raised a $300 million Series A led by , , and . The less-than-1-year-old company was valued at $2.4 billion. Alongside the equity, Volta secured $5 billion in debt to fund data center buildouts.
• , a full-stack AI infrastructure and neocloud platform, received led by Doha-based broadband provider , which holds a 49% stake. Jakarta-based Zankore is less than 1-year-old and is valued at $1.6 billion. The platform is targeting 1 gigawatt of AI computing capacity.

Security

• San Francisco-based , an AI-native security company that provides autonomous penetration testing, raised a $250 million Series E led by and . The 7-year-old company was valued at $2 billion and is used by 7,000 organizations including defense, Fortune 10, banks and healthcare companies among others.
• Palo Alto, California-based , which provides security for AI agents and third-party applications, raised an $85 million Series D led by . The 9-year-old company was valued at $1.1 billion.

Energy

• China-based , a nuclear fusion company developing small modular reactors, raised about $179 million in seed funding. The 1-year-old company was valued at about $1.5 billion.
• Washington, D.C.-based , which develops software that adjusts AI data-center workloads based on power-grid demands, raised a $150 million Series A at a $1 billion valuation. and co-led the round. The 2-year-old company says the round brings total funding to more than $220 million.

Transportation

• Nigeria-based , a vehicle financing and autonomous fleet management infrastructure, raised a $250 million Series C led by , and . The 7-year-old company was valued at $2.1 billion. It operates a fleet of 42,000 vehicles 鈥� both human-driven and autonomous 鈥� across 29 cities, with annual recurring revenue of $420 million.听

Critical minerals

• Houston-based , which builds mines and refineries using its MarianaOS software platform, raised a $310 million Series B led by . The 2-year-old company was valued at $1.5 billion.

Web3

• Dubai-based , an AI-enabled stablecoin neobanking platform for cross-border payments and tokenized assets, raised a $68 million Series C led by Tokyo-based at a $1 billion valuation. The 7-year-old company says it processes more than $40 billion in annualized transaction volume.

Related 兔子先生传媒 unicorn lists:

• (1,862)
• (658)
• (276)
• (195)
• (119)
• (102)
• (961)
• (547)
• (254)
• (39)
• (489)

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• Which Investors Have Backed The Most 2026 Unicorns?
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Methodology

The 兔子先生传媒 兔子先生传媒 is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 兔子先生传媒 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.听

The unicorn board does not reflect internal company valuations 鈥� such as those set via a 409a process for employee stock options 鈥� as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter.听

Funding to unicorn companies includes all private financings to companies that are tagged as unicorns, as well as those that have since graduated to .听

Exits analyzed here only include the first time a company exits.听

Please note that all funding values are given in U.S. dollars unless otherwise noted. 兔子先生传媒 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to 兔子先生传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

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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 鈥� 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 兔子先生传媒 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.

兔子先生传媒 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鈥檚 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鈥檛 be afraid to take risks. Failure can be a springboard to success.

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Seven companies raised billion-dollar fundings in August, tied with a few months for the year鈥檚 second-highest count after July, when 13 companies did the same.

The largest startup funding deal in August went to 13-year-old which raised $5 billion at a $190 billion valuation.

Other companies across a broad range of industries raised billion-dollar-plus rounds, a testament to the strength of the technology sector impacting聽 a range of more traditional industries, including physical manufacturing, defense, aerospace and energy. They included defense tech startup ; , which performs custom AI fine-tuning for businesses; low-orbit satellite network ; nuclear energy company ; automated coding provider ; and home battery service .

Notable exits

On the IPO front, Hangzhou, China-based humanoid robotics company went public on Aug. 19 and soared 460% on its first day of trading on the .

The largest M&A news in August was 鈥檚 announcement that it aims to acquire open-source AI platform for $12.9 billion. Other notable acquisition news was Milan-based tech aggregator 鈥� plan to acquire 13-year-old database company for around $1.3 billion.

Big rounds are coming faster

Venture capital continues to concentrate rapidly among a small group of fast-growing companies. Two of August鈥檚 billion-dollar recipients illustrate the trend: Databricks added $56 billion to its valuation in just six months, while River AI raised both its seed and Series A rounds this year, amassing a staggering $1.1 billion in early-stage funding.

That accelerated cadence extended across August鈥檚 megadeals: Five of the seven billion-dollar funding recipients had last raised capital less than 12 months earlier, including three that closed their previous rounds earlier this year. The numbers underscore how quickly investors are doubling down on companies they believe can become the next generation of technology giants.

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Methodology

The data contained in this report comes directly from 兔子先生传媒, and is based on reported data. Data is as of Sept. 2, 2026.

Note that data lags are most pronounced at the earliest stages of venture activity, with seed funding amounts increasing significantly after the end of a quarter/year.

Please note that all funding values are given in U.S. dollars unless otherwise noted. 兔子先生传媒 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to 兔子先生传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. 兔子先生传媒 also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. 兔子先生传媒 includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

Late-stage consists of Series C, Series D, Series E and later-lettered venture rounds following the 鈥淪eries [Letter]鈥� naming convention. Also included are venture rounds of unknown series, corporate venture and other rounds above $15 million. Corporate rounds are only included if a company has raised an equity funding at seed through a venture series funding round.

Technology growth is a private-equity round raised by a company that has previously raised a 鈥渧enture鈥� round. (So basically, any round from the previously defined stages.)

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颁谤耻苍肠丑产补蝉别鈥檚 predictive intelligence tools flags a handful of well-funded private companies with at least a 40% probability of going public within the next six months. , arguably the most closely watched IPO prospect, sits just outside that near-term screen: 兔子先生传媒 considers an eventual listing very likely, but the model favors a six- to 12-month timeline.

Together, Anthropic and the other seven companies noted below make up a varied watchlist spanning artificial intelligence, fintech, crypto, consumer health and climate technology, ranging from smart-ring maker to enterprise productivity platform .

A record IPO sets the stage

In the first half of this year, 58 venture-backed companies listed at $1 billion or above, per 兔子先生传媒 data. That compares with 27 that did so in the first half of 2025 and 69 in all of last year.

On a dollar basis, this year has also far surpassed recent IPO years, thanks to SpaceX鈥檚 historic IPO in June that launched it onto the and raised $86 billion in the process. Through the first half of 2026, venture-backed startups globally raised $110.8 billion collectively via IPO listings, 兔子先生传媒 data shows, well above the $12.6 billion raised in the first half of 2025.

With the year鈥檚 end now in sight, a small window remains for other startups to launch 2026 IPOs. With that, here鈥檚 a look at notable venture-backed startups that 颁谤耻苍肠丑产补蝉别鈥檚 predictive intelligence suggests are potential IPO candidates within the next six months.

Venture-backed IPOs to watch

: Anthropic, the most valuable venture-backed startup in the world, has indicated it plans to beat rival to the public markets. The company could debut as soon as September or October and raise up to $100 billion via the offering, according to a in last week. 颁谤耻苍肠丑产补蝉别鈥檚 predictive intelligence tools, meanwhile, pin a slightly longer timeline on an Anthropic IPO, saying it鈥檚 more likely to happen in six to 12 months. Anthropic has already raised $125 billion from private-market investors since its founding in 2021, and whenever it happens its IPO would mark a major liquidity bonanza for those backers. (For its part, OpenAI is also deemed a very likely IPO candidate by 兔子先生传媒, but not within the next six months, a prediction corroborated by the WSJ report, which noted that the company is considering pushing its listing to 2027.)

: Smart-ring maker Oura is a likely IPO candidate in the next six months, per 兔子先生传媒. The Finland-based company, which has raised $1.5 billion from investors, is mulling an offering as soon as September or October that could fetch a valuation above the $11 billion it achieved in its most recent funding, the Journal last week. A successful offering would also provide a notable test of public-market appetite for consumer health hardware, a category that has produced relatively few large venture-backed listings in recent years.

: San Francisco-based Notion is a strong candidate for a near-term IPO, according to both 颁谤耻苍肠丑产补蝉别鈥檚 predictive tools and independent reporting. The productivity-software maker has raised more than $343 million from investors over time and has posted strong revenue growth from its enterprise AI offerings. Startup reporter Alex Konrad recently that the company has appointed a new board of directors with significant public-company experience in 鈥渁 big step towards an IPO.鈥�

: Cryptocurrency exchange Kraken is another probable public-market entrant, per 兔子先生传媒, and if it does make the IPO leap, it鈥檚 highly likely to do so within the next six months. The Cheyenne, Wyoming-based company filed a confidential IPO registration statement with the almost a year ago, but subsequently paused its going-public plans amid market volatility. In May, CEO said the company was 鈥渵80% ready鈥� for a 2026 listing, although it has reportedly weighed delaying again until 2027.

: Following 鈥� $6.4 billion Nasdaq IPO in May, attention has turned to SambaNova, a fellow developer of specialized AI chips and infrastructure. 兔子先生传媒 predicts that the San Jose, California-based company is a probable IPO candidate, with a slightly less than even chance of going public within the next six months. That prediction jibes with comments from co-founder and CEO, who in July that the company was strongly considering a U.S. IPO next year. His comments followed SambaNova鈥檚 $1 billion Series F raise this summer at an $11 billion post-money valuation.

: Sweden-based green-steel maker Stegra has raised approximately $12.6 billion across equity and debt financing, according to 兔子先生传媒, including a 鈧�1.4 billion financing round that closed in June. in June 2025 that the company was considering an IPO to fund further expansion. Founded in 2020, Stegra has attracted orders from automakers and industrial customers including , , , and parent for steel produced using renewable electricity and green hydrogen. It broke ground in August 2022 on an integrated steel plant in Boden, northern Sweden, whose first phase is designed to produce 2.5 million tonnes of green steel annually. Some customer agreements call for deliveries to begin in 2027, although Stegra has said the project鈥檚 overall timeline remains under review. 兔子先生传媒 considers Stegra a probable IPO candidate and gives it a roughly even chance of listing within the next six months.

: Stripe is a perennial presence on our IPO predictions lists, and for good reason. Before the AI giants displaced it at the top of The 兔子先生传媒 兔子先生传媒, the payments company held the crown as the most valuable U.S.-based startup, and one with a solid business to boot. Stripe has raised a total of $10.4 billion, including venture rounds and secondaries, since its 2010 founding, but has delayed entering the public markets with repeated tender offers that provide liquidity to employees. Will it finally make a run at the public markets in 2027? While 兔子先生传媒 predicts the South San Francisco, California-based company is a very likely IPO candidate in the long-term, in the short run it鈥檚 a bit iffier. The model says six to 12 months is a more believable time frame, and CEO has said the company is in .

: OpenEvidence, an AI platform for doctors, is a probable IPO candidate, per 兔子先生传媒. If it does pursue a listing, it鈥檚 likely to go public within the next six months, per our predictive intelligence. CEO has been somewhat more circumspect: In an with CNBC in January, he said the Cambridge, Massachusetts-based company would consider an IPO after OpenAI and Anthropic had listed: 鈥淭here鈥檚 an order to nature,鈥� he said. 鈥淔oundation model companies go public first. Then the application layer follows. That鈥檚 how the internet played out, and that鈥檚 how this cycle will play out, too.鈥�

Methodology

For this analysis, we used 颁谤耻苍肠丑产补蝉别鈥檚 predictive intelligence tools and our own reporting and analysis to refine a list of potential near-term IPO candidates.

颁谤耻苍肠丑产补蝉别鈥檚 use company data 鈥� including funding and valuation history, financial growth, key leadership hires, market-share expansion and headcount trends 鈥� to assess the likelihood that a private company will go public.

The model produces an overall IPO probability score and corresponding rating, such as 鈥渧ery likely,鈥� 鈥減robable鈥� or 鈥渦ncertain.鈥� For companies that meet a minimum confidence threshold, 兔子先生传媒 separately estimates when an IPO might occur across four windows: within six months, six to 12 months, 12 to 24 months, or more than 24 months.

For this analysis, we define a 鈥渘ear-term鈥� candidate as a private company rated at least 鈥減robable鈥� overall, with a 40% or greater probability of going public within six months of the prediction date. The overall and timing scores should be read separately: A company may be considered highly likely to IPO eventually without being a strong near-term candidate. Predictions are directional rather than guarantees and may change as new company and market data becomes available.

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