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�

Venture firms that set up shop in the Texas capital city included , , and 1, among others. famously moved 鈥檚 headquarters to Austin in 2021, while also purchasing a house and establishing a residence there.

But as more employees returned to in-office work, Austin slowly seemed to fall out of favor with the tech community, some of whom said it had been overhyped as a startup hub.

There were reports of tech workers who had moved to the city during the pandemic and , saying they were going back to places like the Bay Area. Musk back to California in 2023.

Funding tops pandemic peak

Undeterred by the 鈥渢ourists,鈥� the startup and venture community in Austin kept plugging away. And those efforts are reflected in a surge in funding to startups headquartered there last year, with 2025 posting an all-time high for Austin venture investment, 附近上门 data shows.

Investment into Austin-based startups spiked 64.8% to $7.19 billion in 2025 as more investors poured money into companies based in the region, according to 附近上门 . That鈥檚 compared with the $4.37 billion raised by Austin-area startups in 2024 and tops even the $6.1 billion raised in 2021, at the height of the venture funding frenzy.

Notably, deal counts actually decreased from 312 in 2024 to 272 year over year, signaling an increase in later-stage deals. Indeed, the data corroborates that with $4 billion of the total raised in 2025 classified as late-stage rounds.

Last year鈥檚 totals were also more than double 鈥� 130% higher 鈥� than the $3.1 billion raised in 2023. That money was raised across 403 deals, signaling much smaller round sizes at the time and a more mature market.

A tech scene decades in the making

, managing partner of , doesn鈥檛 believe that the Austin funding performance in 2025 was anomalous.

Rather, he calls it 鈥渢he payoff from decades of compounding.鈥�

鈥淭alent density in venture categories such as software, fintech, health tech, defense and听 robotics has reached a critical mass, driven by waves of Bay Area relocations, both full HQ moves and satellite offices, that brought technical, product and operational talent into the market,鈥� Flager said.

That talent eventually left to build new companies, he said, and the cycle repeated.

鈥淥n the capital side, the stack has matured across all stages, from pre-seed through growth, with local firms that have now cycled through multiple funds and understand the market deeply,鈥� Flager said. 鈥淟ayer in a business-friendly regulatory environment, a relatively lower cost of living, as well as a lower effective tax rate, and Austin becomes an attractive place to start and scale a company.鈥�

Former Austin Mayor saw so much potential in the city鈥檚 startup scene that he began a career in venture investing after his tenure ended in early 2023. (He now works for New York-based ).

Part of the city’s success as a startup hub stems from its reputation as a haven for mavericks and risk-takers, Adler has said.

鈥淢ost cities in the world, you try something, you fail; it’s hard to have access to the capital the second time,” he told co-founder in a in 2022. “In Austin, the civic folk heroes are the people that tried something and it didn’t quite work out and they worked on it until it did.鈥�

, founder of , a solo GP venture firm based in nearby San Antonio, said that it feels like Texas and the Austin metro area specifically are becoming more attractive to manufacturing- and engineering-heavy businesses.

鈥淪ome of that may be thanks to Tesla, and some of it may simply reflect the physical advantages of the state,鈥� he told 附近上门 News. 鈥淓ither way, this [surge in financing] feels less like hype returning and more like capital concentrating around a narrower set of serious, technically differentiated companies.鈥�

Deal sizes grow

That diversity among funded startups is reflected in last year鈥檚 investment totals for Austin, which were boosted by several large, late-stage deals across a broad range of industries.

The largest was a $1 billion Series C round for energy provider in October. New York-based led that financing, which valued the 2-year-old company at $4 billion.

Looking back, February in particular was a busy month for venture funding. That month alone saw the second-, third- and fourth-largest rounds in Austin for the year. They included:

• A February Series C round in which autonomous surface vessels maker raised $600 million at a $4 billion valuation. led the round for the defense tech startup.
• Also in February, , which provides endpoint management, security and monitoring, raised $500 million in Series C extensions at a $5 billion valuation 鈥� more than doubling its value from just 12 months prior. The funding came in separate tranches led by and 鈥檚 , with participation from other investors.
• Robotics company in February raised $415 million in Series A financing led by听 and accelerator (A $520 million extension to that Series A was raised in February 2026, taking the total round to over $935 million.)

The findings correspond with Flager鈥檚 observations.

鈥淎 good chunk of the capital raised in Austin was driven by several large deals. Similar to what we saw across the U.S. in 2025, venture funding in Austin was more concentrated than it has been in the past,鈥� he told 附近上门 News. 鈥淩oughly 38% of the capital deployed went to the top five venture financings in Austin. I believe the top 10 deals nationally accounted for more than 40% of the capital raised last year. We’ll see if this trend continues into 2026 and beyond. The start of the year suggests it will.鈥�

, founding partner of , agrees, noting that from a dollars perspective, the surge in financings was driven by a handful of outsized capital-intensive deals in newer categories such as defense and deep tech.

鈥淭hese companies require a combination of technology, land for manufacturing facilities, and talent for manufacturing tasks. Austin has unique skillsets for that,鈥� he said. 鈥淚t has a density of three things: talent in deep tech with , and many others moving to Texas in light of favorable business conditions with expertise in these industries; expansive land around Central Texas that is inexpensive, especially compared to California; and lower cost manufacturing-related labor especially given the surge in manufacturing jobs such as at Tesla in recent times.鈥�

Burgeoning industries

Once upon a time, Austin was better known as home to software and CPG companies. And while those types of companies certainly still exist, a number of other industries are growing increasingly robust, as the local investors have pointed out.

As with many top tech markets, Flager said Austin has long been strong for application and infrastructure software, which is currently being challenged by AI. In his view, that talent has migrated to building 鈥渜uality鈥� vertical agentic software and AI-native businesses.

鈥淲e are seeing these companies grow quickly and build scale, while using less capital 鈥� which is exciting,鈥� he added. 鈥淭he domain experts who built and scaled application software companies here over the last two decades are spinning out to build the next generation of native AI businesses.鈥�

The market overall is also broadening in interesting ways. Defense and autonomy have emerged as breakout categories, with Austin becoming one of the stronger markets in the country for dual-use and autonomous systems companies, noted Flager.

鈥淭he combination of software and hardware skills now in Texas, along with a business-friendly regulatory environment, has allowed Austin to take a leadership position in these important and developing markets,鈥� he said. 鈥淓nergy tech is also a natural fit given Texas’ grid scale and the surging power demands of AI infrastructure.鈥�

Finally, robotics and advanced manufacturing are also gaining momentum, driven by deep engineering talent and the ability to scale manufacturing near Austin cost-effectively, allowing engineers, executives and other factory employees to coexist and collaborate in close proximity.

Srinivasan noted that his firm is seeing strong activity in vertical AI companies, or companies that serve vertical markets with AI that is tuned on specialized proprietary vertical data, often targeting the services and labor expenditures by their customers.

鈥淭hese companies deliver 鈥楽ervices as Software鈥� with close to software gross margins and pricing models that are based more on usage and outcomes as opposed to the traditional seat-based models,鈥� he said.

Srinivasan also expects the city to continue to see large funding deals in defense and deep tech, given the combination of local strengths and robust global demand for such products.

Continued momentum

Investors and companies continue to be drawn to Austin. In late December, San Francisco-based venture firm in the city. One of the firm鈥檚 founders, , also announced that he had personally moved to Austin. The firm鈥檚 other founder, , had lived and worked in the city since 2022.

In late March of this year, Musk to build two semiconductor factories totaling 100 million square feet in Austin to supply advanced chips for and Tesla. The venture, known as Terafab, aims to manufacture 1 trillion watts of computing power per year, he said. Media outlets valued the initiative at nearly

Also this week, Barcelona-based AI health tech startup announced it will open an office and hire in Austin.

CEO told 附近上门 News that with the company鈥檚 New York office already established, the next step was not just expansion, 鈥渂ut choosing the right place to build.鈥�

鈥淎nd we chose Austin for one reason above all: talent,鈥� he said. 鈥淎s an AI health tech company, our success depends on attracting exceptional people across engineering, data and life sciences. Austin has rapidly become one of the most competitive talent markets. The city is one of the fastest-growing in the United States. This brings together deep tech expertise, entrepreneurial energy and a growing concentration of healthcare innovation. Ideal for our goal of building an R&D hub. 鈥�

Coelho also points out that Biorce has witnessed a 鈥渢rend鈥� of people moving from the Bay Area to Austin, noting that 鈥渢he quality of life has gained notoriety.鈥�

鈥淏ut for us, this isn鈥檛 about following a trend,鈥� he added. 鈥淚t鈥檚 about building where the best people are 鈥� and where they want to be.鈥�

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The investor is vocal about his belief that AI is a massive threat to entry-level jobs, or what he views as a shifting social contract in the modern workforce.

He would know about AI鈥檚 impact. Choi has led investments in several AI-first companies.

Known for a founder-first conviction, he鈥檚 also backed enterprise software and fintech infrastructure companies.

Prior to joining Khosla in 2024, Choi was a partner at , where he led and managed high-profile growth investments in companies such as , , (which was acquired by ), and . Before Accel, he worked at , backing companies such as (acquired by ), , and (acquired by ).

I recently spoke with Choi to hear more about why he thinks entry-level jobs could be disappearing, why he鈥檚 flipped his investing philosophy, and how he鈥檚 gone from growth-stage investing to being stage-agnostic.

This interview was edited for brevity and clarity.

附近上门 News: You鈥檝e had a prolific run the past couple of years, leading deals in , , , , and others. How are you managing that volume?

Choi: It has been an intense stretch. About seven deals happened just last year, which was an insane year by any standard. This year has been a bit calmer as I focus on settling in with the companies I鈥檝e invested in.

You鈥檙e currently researching the disappearance of entry-level jobs. As a parent, that sounds a bit scary to me. What are you seeing?

AI is a massive conundrum. I鈥檓 seeing it in my own workflow. I use the models to get up to speed on technical capabilities 鈥� asking about Clickhouse鈥檚 indexing methodology versus 鈥檚 in voice mode while I鈥檓 driving. It鈥檚 pulling from research papers and documentation faster than any human could. I describe it as feeling like I have an “Ironman suit” on.

The problem is that if I can do the work of a junior associate myself, almost instantly, those roles vanish. We鈥檙e facing a world where the base-level work we used to rely on young folks for is now table stakes.

If the “on-the-job” training era is over, where does that leave students and universities?

The burden of the first three years of 鈥渓earning how to be a professional鈥� has to shift to the universities. I look at the traditional U.S. model of general education requirements and think, 鈥淲hy are we doing this?鈥� We did that in high school. Universities should be places where you use AI to actually build things and apply knowledge to the real world.

If you’re a computer science major today, you need to graduate looking and delivering like a third- or fourth-year engineer. The bar has been raised for everyone. While schools like and are leaning into an 鈥淎I-first鈥� curriculum, many elite institutions are still silent, trying to figure out how to adapt.

Khosla is known for being contrarian. How does that translate to the growth stage in such a competitive market?

I鈥檝e actually evolved to be stage-agnostic. While people still put me in the 鈥済rowth鈥� bucket, I鈥檓 doing much more seed and Series A. In this era, the metrics a company has today don’t guarantee where they’ll be in two years because the rate of change is so high.

I鈥檝e flipped my philosophy: it used to be 80% metrics and 20% founders. Now, it鈥檚 90% founders. The only constant is how special the founding team is and how quickly they can adapt. If code is being created 10x faster, a company might face 50 years of change in a single decade. You have to back the people who can handle that stress.

You鈥檝e predicted “mass carnage” for some software companies. Who survives the transition to an AI-native world?

We are moving from trading on revenue multiples to trading on free cash flow and PE multiples. That鈥檚 a painful transition. The market now needs to believe that a company is AI-native 鈥� that its revenue is moving toward inference- and usage-based models rather than just old-school seat licenses.

I expect carnage for lightweight, horizontal applications and mid-market companies that can’t attract applied AI talent. I have a ton of respect for founders like those at or who are 鈥渂urning the boats鈥� to reinvent their entire businesses. It鈥檚 incredibly difficult, but in this market you either reinvent or you get replaced by someone building natively from day one.

With your background in fintech infrastructure, where do you see the next 鈥渦nconventional鈥� opportunity in financial services that most growth investors are currently overlooking?

It’s now become somewhat consensus, but I still believe it’s fairly unconventional that systems of record can be ripped out, whether it be in financial services or in other categories.

For example, we recently invested in , which is seeking to replace and the core accounting system, which is the last system of record I would have thought might be under threat. We’re seeing that with AI, startups can build migration paths that didn’t exist before, and also the depth and breadth of incumbent platforms in a fraction of the time.

often talks about 鈥渃hallenging the conventional wisdom鈥� of founders. Can you share an example of a time you had to steer a growth-stage founder away from a 鈥渟afe鈥� path toward a much larger, albeit riskier, vision?

In general, there are many times when a founder is thinking through a very risky but potentially game-changing product addition or acquisition. While I view part of our job as investors and board members as helping identify and manage potential risks, the most important thing we can do is give them the courage to take risks that are transformational to the business and the category they are in.

You鈥檝e noted that talent density is the most important variable for success. In a market where AI is automating routine work, how has your criteria for what defines an 鈥渆lite鈥� executive hire changed?

Perhaps somewhat ironically, one of the main differences in criteria is whether this exec has “IC’d” (individual contributor鈥檇) themselves and can do most of the work required out of the gate with their own two hands plus AI.

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For years, industry observers have predicted an uptick in startup M&A activity, in part due to the limited number of companies going public. As the IPO dam finally broke in 2025, we didn鈥檛 see a huge surge in M&A dealmaking, but we did see a large spike in the known value of M&A deals.

Globally, in 2025 so far, there have been around 2,300 M&A deals involving venture-backed companies with a collective known deal value of more than $214 billion, per 附近上门 . (It must be noted that most of the reported M&A deals do not have amounts, so the dollar amount is based only on the deals in which a value was provided.)

Interestingly, deal count was only up slightly, signaling much larger deal sizes. The dollar amount is up from a known value of $112 billion in 2024, for an impressive 91% increase.

The trend was similar in the United States, which dominated M&A activity, comprising about 73% of all transaction values and 56% of transactions alone, globally.

There was a known value of $157 billion across nearly 1,300 deals, compared with a known $79 billion across about 1,100 transactions in the U.S. in 2024. Around 37 of those deals were valued at $1 billion or more, per 附近上门 .

, technology, media and telecoms deal advisory and strategy leader for , is not surprised by the uptick in M&A deal volume and dollars.

鈥淎 healthy IPO market tends to increase M&A activity rather than reduce it,鈥� he told 附近上门 News. 鈥淢any companies pursue dual-track strategies, simultaneously preparing for an IPO while exploring M&A, which gives them greater flexibility and leverage in negotiations. The threat of a public offering can be used as a bargaining chip to drive up a startup’s sale price.鈥�

On top of that, he points out, a strong IPO market creates a new wave of cash-rich public companies that 鈥渋mmediately look to acquisitions to accelerate their growth,鈥� ultimately stimulating M&A demand.

Larger deals tick up

$32 billion purchase of cloud security unicorn marked the largest acquisition of a private, venture-backed U.S. company, not just this year so far, but ever. The next-closest deal historically, per 附近上门 data, was 鈥檚 2014 acquisition of for $19 billion. Still, that deal alone wasn鈥檛 responsible for the large increase in value of M&A transactions this year.

The next-closest deal in 2025 was 鈥檚 $10.3 billion buy of South Korea fintech . After that came 鈥檚 $8.87 billion acquisition of .

In fact, M&A exit numbers this year are the highest ever for unicorn companies, with 36 deals in 2025 totaling $67 billion in value.

Other large transactions included:

• In late May, quietly announced its $6.5 billion acquisition of , a little-known but highly technical company focused on model deployment and orchestration.
• In March, it would acquire chip design company , in a $6.2 billion cash transaction.
• In December, , the company behind social media platform , announced plans to combine with fusion company . The two signed a merger agreement to combine in what TMTG called a stock transaction valued at more than $6 billion
• Healthcare software platform in March sold a majority stake to at a reported value of $5.3 billion.

Strategic plays and a flurry of acqui-hires

, technology sector leader, believes that strategic plays drove 2025鈥檚 M&A surge far more than distressed sales.

鈥淐orporations听are writing big checks for AI, cybersecurity, data acquisitions, and massive tech and talent deals,鈥� he said. 鈥淭hese tech and talent deals used to be worth tens of millions, and now we are in the billions.鈥�

Indeed, fear of missing out appeared to be a driving factor in a lot of M&A activity, especially when it came to AI. The sector also drove a flurry of acqui-hires.

鈥淥n the one hand, big corporates are snapping up seed/Series A startups for talent and tech 鈥� we can call that the AI acqui-hire trend. Many teams with fewer than 100 employees have landed $100 million-plus exits,鈥� Hoebarth said. 鈥淥n the other hand, a cohort of听3-听to听6-year-old unicorns that stalled on IPO plans is finally selling.鈥�

Looking ahead to 2026, he predicts that acquirers will likely increasingly focus on earlier plays 鈥� scooping up emerging tech before it scales, especially听in high-growth sectors like AI and cybersecurity.

, co-founder of and a corporate attorney for startups and small businesses, agrees that more acquisitions are happening at seed and Series A, but believes that more value is being transacted at later stages.

鈥淎cquirers are buying at an earlier stage to speed up to capability rather than build internally, as hiring the same team individually is slower and riskier,鈥� she noted. 鈥淪eed and Series A founders are more willing to sell in light of the current financing environment and the fact that there is less stigma around a really early exit at present.鈥�

Unless the financing environment picks up evenly for early-stage seed and Series A companies, she expects this trend to continue.

AI vs. everything else

Not only did the ultra-competitive environment, especially in the AI and cybersecurity industries, drive more acqui-hires, but talent also played a larger role than ever in determining transaction value.

, owner of Israel-based , believes that in 2025, pricing has effectively been split into two markets: AI and everything else.

鈥淚n AI, talent and IP value often dominate, including outsized acqui-hires that would be irrational in other sectors,鈥� he said.

However, in non-AI tech, pricing remains anchored in revenue multiples and public comparables, heavily influenced by unit economics and operational KPIs.

鈥淟ooking into 2026, I expect greater financial discipline across all sectors, including AI, with stronger emphasis on sustainable P&Ls and defensible unit economics,鈥� he predicted.

KPMG鈥檚 Bahal said that while traditional valuation metrics such as revenue multiples still play a role, acquisition prices are increasingly being dictated by the strategic value of a company鈥檚 talent and its intellectual property.

鈥淭his fundamental shift toward valuing people and technology over pure revenue is the new reality in dealmaking, especially as the 鈥榓cqui-hire鈥� trend accelerates to secure top engineering talent in high-demand fields like AI,鈥� he said.

Unlike Sagie, he thinks this trend is not temporary.

鈥淚t is expected to intensify through 2026 as the war for talent and unique technological capabilities continues to be a primary driver of value,鈥� he predicted.

M&A driven by down rounds

Talent and technology weren鈥檛 the only things driving M&A activity.

In Hoebarth鈥檚 view, the most common trigger听event听in 2025 was a funding crunch. Because there is so much money flowing into AI companies, it can be easy to forget that a lot of other sectors are struggling.

鈥淢any founders opted to be acquired when facing a down round or failed raise,鈥� Hoebarth said. 鈥淲e听saw startup down rounds hit a decade high 鈥� about听16% of deals 鈥斕齮his year, so rather than accept significant dilution, founders听did a听pivot to M&A. These down rounds get lost in the broader AI narrative, which continues to be very positive, for now.鈥�

Mignano agrees. In 2025, the most common practical trigger that pushed early-stage founders to sell wasn鈥檛 a single dramatic event but a confluence of many, she said.

Those events include the inability to raise the next round at all or on good terms. If an AI company, the AI technology was not defensible “enough” to get it to the next round, and founder fatigue after a number of years where they have been financially strapped.

Another factor?

鈥淓xpansion and increased revenue metrics require a capital-intensive GTM build that the current investors won鈥檛 fund and that a possible acquirer may fund post-acquisition,鈥� Mignano noted.

Looking ahead

So what鈥檚 ahead for 2026?

Bahal believes that the trajectory of the M&A market in 2026 will be determined by the overall health and stability of the economy.

鈥淎 bull case would be fueled by the need to continue the digital transformation of every business, a favorable regulatory environment, falling interest rates and continued economic growth, which would give dealmakers the confidence to pursue strategic acquisitions, particularly in technology and AI,鈥� he said.

Conversely, Bahal believes that a bear case would emerge from an economic downturn, marked by higher inflation or increased regulatory scrutiny and increased geopolitical uncertainty, creating headwinds that would cause both buyers and sellers to pause dealmaking.

Hoebarth notes that EY-Parthenon Americas is forecasting a modest increase in M&A activity in听2026, and definitely lower than what occurred this year. The U.S. M&A deal volume is expected to grow听about听3%, following a 9% increase in 2025, according to their data.

In his view, bull case听factors include easing monetary policy and continued lower interest rates, strong corporate balance sheets, significant private equity dry powder, and continued innovation in high-growth sectors like AI and cybersecurity.

Hoebarth believes that bear case factors include an听economic downturn,听trade and tariff uncertainty,听tight funding markets limiting liquidity, and increased regulatory scrutiny, especially in China, the EU and the U.K., or geopolitical barriers slowing deal approvals.

鈥淭he elephant in the room听is still the question of听what happens with AI,鈥� he said. 鈥淲e do see early signs of a pullback in the AI space, which would have ripple effects far beyond the tech ecosystem.鈥�

Sagie believes that if the macro environment 鈥渟tops getting in the way, M&A activity will take care of itself.鈥�

鈥淟ower and more predictable interest rates, fewer regulatory surprises, and easing trade tensions would give boards and buyers the confidence to plan again,鈥� he said. 鈥淲hen that happens, consolidation comes back naturally, not because companies are desperate, but because buying becomes a faster and less risky way to grow than building from scratch.鈥�

The bear case is not about technology suddenly breaking, Sagie points out.

鈥淚t is about hesitation,鈥� he said. 鈥淚f rates stay high, geopolitical noise continues, or capital markets remain jumpy, buyers slow down. Decisions take longer, deals get smaller, and only the transactions with a very clear strategic rationale actually close. What separates the two is confidence. When executives believe they can underwrite the next three to five years with some degree of certainty, M&A moves quickly. When that confidence is missing, even good assets struggle to transact.鈥�

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By and

We鈥檙e not doomsday thinkers. The truth is, we can鈥檛 afford to be, because founders rarely have that luxury. Instead, we make decisions in real time with clients, teams and cash flow.

But the signals around us are loud, and getting stronger.

Startups like , and each operate with . Humanoid robots are being built explicitly to replace labor. and have cited automation or AI as contributing factors in recent reductions in force. Whether every case is perfectly causal isn鈥檛 the point 鈥� the direction is unmistakable.

So what about the companies in the middle? Not fully AI-native. Not legacy. Actively transforming in real time.

A reply to 鈥檚 captured the moment with dark humor: 鈥�.鈥�

It鈥檚 funny but clarifying. If a PE firm were leading our transformation, they鈥檇 restructure aggressively around speed, automation and product velocity. Many roles 鈥� potentially including ours, even as founders 鈥� would be redesigned or replaced.

Welcome to the modern dilemma faced by nearly every existing founder, CEO and management team on the planet.

Everyone is experimenting with AI partly out of curiosity but mostly out of fear 鈥� fear of being left behind, losing business, missing the next shift. No one, however, agrees on what 鈥淎I is coming鈥� actually means. CEO predicts abundance; CEO predicts chaos. The truth is probably somewhere in between.

Meanwhile, leverage is becoming nonlinear, just as Ravikant warned. Highly leveraged individuals can create exponentially more output than peers. Society, however, isn鈥檛 built for exponential asymmetry, and most companies aren鈥檛 either.

Which is precisely why culture is so important. We鈥檙e definitively reorganizing work and what it means to be professional, yes, but we must also reorganize culture in order to succeed.

Nearly all AI commentary focuses on operations 鈥� efficiency, automation, productivity, tools, workflows. But what of culture 鈥� the real operating system of a company 鈥� within organizations?

We have now over-indexed on the operational, rational, intellectual, left-brain paradigm. Ironically, we鈥檙e doing so precisely as intelligence gets commoditized. We must now concern ourselves with its reciprocal.

• How do teams build trust when AI handles core work?
• What does 鈥渃ontribution鈥� mean when output is hybrid?
• How do you maintain belonging when leverage increases?
• What does creative authorship look like between humans and machines?
• How do you preserve dignity, identity and motivation?

These are cultural questions. And we don鈥檛 have established norms, language or frameworks for them yet. The cultural gap is the founder鈥檚 dilemma hiding in plain sight.

is the co-founder of the world鈥檚 newest creative AI marketing tool, RYA. He鈥檚 also the co-founder of , an advertising agency that leverages data to make hits for , , , and many other marquee brands. Over the past two decades he has led cross-functional teams and developed multidiscipline communications and creative strategies for both for-profit and nonprofit organizations. Himmelsbach is a MBA graduate from 鈥檚

is head of business development at WestComms. He strongly believes that high-quality communication will only continue to appreciate in value and supports clients working in AI, crypto and frontier technologies. Pinson still keeps a regular hand-written journal, loves wine and earned a degree in economics and philosophy at in California.

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By and

This story starts with a loss.

A client didn鈥檛 renew, so we reduced headcount. Operationally, it made sense, but the decision surfaced something bigger than a single role or contract: a growing tension inside modern leadership that鈥檚 becoming harder to ignore.

Our company spans a creative services business and an AI-powered software platform. That combination has made one trend obvious: The modern economy rewards software, automation and what investor and entrepreneur calls 鈥� the 鈥渇orce multiplier for your work.鈥�

Years ago, Ravikant bemoaned that labor 鈥� once the original form of leverage 鈥� had become 鈥渙vervalued,鈥� and that capital, code and now AI would define the next era. 鈥淵ou want the minimum amount of labor that allows you to use the other forms of leverage,鈥� he wrote.

, perhaps the 鈥渇ace鈥� of AI writ large, is famous for espousing the as the ultimate form of leverage, claiming that it will create 鈥�,鈥� and that 鈥淸a]lmost everyone will want more AI working on their behalf.鈥�

Investor enthusiasm around , and 鈥� companies with extraordinary output and extremely small teams 鈥� suggests he may be right. Humanoid robots, though still early, extend this trajectory even further.

Behind their enthusiasm, however, lies something the most fervent AI supporters seem reluctant to name. In this brave new world of AI, optimal business models continue to reward leverage, software and automation, of course, but they now also appear to reward something new: having materially fewer people.

As a consequence, we keep returning to a central question: What happens when the efficient thing and the decent thing diverge, even temporarily?

The economic pressure is clear, but the human pressure is just as real. We all seem convinced that we鈥檒l remake our workflows with AI, but what of our culture 鈥� the intangible connective tissue beneath it all? It鈥檚 no coincidence that before AI, the best companies often had the best cultures. In fact, not only do we believe this dynamic will continue as we adapt to AI, we think it will become even more important.

The future of work 鈥� perhaps, even, the future period 鈥� will invariably depend on how humans and machines collaborate, but it will also depend upon the culture we create that holds that collaboration together.

The frameworks, norms and practices that will eventually govern human-AI partnerships are critical, but they remain undefined. And we鈥檙e all going to have to build that culture largely from scratch.

is the co-founder of the world鈥檚 newest creative AI marketing tool, . He鈥檚 also the co-founder of , an advertising agency that leverages data to make hits for , , , and many other marquee brands. Over the past two decades he has led cross-functional teams and developed multidiscipline communications and creative strategies for both for-profit and nonprofit organizations. Himmelsbach is a MBA graduate from 鈥檚

is head of business development at WestComms. He strongly believes that high-quality communication will only continue to appreciate in value and supports clients working in AI, crypto and frontier technologies. Pinson still keeps a regular hand-written journal, loves wine and earned a degree in economics and philosophy at in California.

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Founded in 2024, San Francisco-based Coverbase aims to reinvent how enterprises vet and manage vendors in a 鈥渟ecurity-first鈥� manner. Specifically, it uses artificial intelligence to automate and secure how large, regulated companies onboard new vendors and suppliers, such as software providers, consultants, contractors and service firms.

Coverbase counts , , and the among its customer base.

Co-founders CEO and CTO have impressive backgrounds. Chio also co-founded , a startup that helps businesses monitor fraudulent activities with its no-code software that has raised from the likes of . Chong is a former engineering manager at fintech giant .

The pair started Coverbase to automate the procurement process 鈥渂y weaving risk, security, and compliance decision-making directly into every stage of intake, due diligence, contracting, and ongoing monitoring.鈥�

鈥淲hat makes us different is that our AI agents don鈥檛 just manage workflows, they actually perform the work,鈥� Chio, who currently teaches AI and cybersecurity at , told 附近上门 News.

Most competitors, he claims, build tools that help humans move through manual approval steps. (Competitors include the likes of , , and .) By being 鈥淎I-agents-first鈥� instead of 鈥渨orkflow-first,鈥� Coverbase allows customers to onboard vendors faster, with less friction and stronger security outcomes, according to Chio.

According to 1 Data Breach Investigations , breaches involving third parties reached 30% this year, up 2x compared to 2024, 鈥渄riven in part by vulnerability exploitation and business interruptions.鈥�

Investors appear to be pouring more money into AI-powered procurement startups lately. Examples include:

• In late June, , a provider of AI-enabled procurement tools, it raised over $55 million in a Series B round led by . The company鈥檚 platform uses AI agents to autonomously handle procurement tasks for businesses.
• In July, , a startup using artificial intelligence to improve efficiency in the construction industry supply chain, raised $20 million in a Series A funding round.
• In October 2024, procurement startup saw its valuation jump 47% after raising a $190 million Series D led by .

Fast growth

Existing and new investors including , , , and also participated in Coverbase鈥檚 Series A round. To date, the company has raised about . While Chio declined to reveal its valuation, he said the Series A represents 鈥渁 roughly 4x increase鈥� compared to its previously undisclosed $3.5 million seed round led by Fika.

Chio also declined to reveal hard revenue figures, noting that Coverbase鈥檚 customer base has grown 10x since the start of 2025. Overall, the startup has about 35 customers and operates on a usage-based SaaS pricing model that scales with the number of suppliers and risk assessments performed on its platform.

Its customers range in size, with some having as few as 50 suppliers, and others being larger companies with over 50,000 suppliers. Besides those mentioned above, customers include , , , , , , , and .

Coverbase is currently active in industries such as financial services, insurance, healthcare, pharmaceuticals and technology because they 鈥渄emand high levels of compliance and security,鈥� Chio noted.

But the company is also expanding into telecommunications and critical infrastructure, and sees future opportunities in other highly regulated sectors such as energy and utilities, defense contracting, government, aerospace and aviation, medical devices and biotech, and payments and logistics.

The company plans to use its new capital to expand into contract management and continuous security monitoring. It鈥檚 also planning to quadruple its sales force to meet 鈥渁ccelerating enterprise demand.鈥� Presently, Coverbase has 12 employees.

鈥楢 real and persistent pain point鈥�

, president and general partner at Canapi, said his firm was drawn to Coverbase because it believes the company is 鈥渟olving a real and persistent pain point in enterprise procurement鈥攑articularly in highly regulated, security-conscious sectors.鈥�

鈥淰endor onboarding is typically slow, fragmented, and risk-prone,鈥� he wrote via email. 鈥淐overbase is flipping that dynamic by using AI to make procurement faster, more secure, and strategically valuable.鈥�

Forehand also believes that what sets Coverbase apart is its AI-native approach.

鈥淭his gives enterprises a faster, smarter, and more secure way to adopt innovation without adding operational burden,鈥� he said. 鈥淚t鈥檚 not just about efficiency 鈥� it鈥檚 about turning procurement into a competitive advantage, which is a fundamentally different mindset from traditional solutions.鈥�

Related reading:

• Exclusive: AI-Powered Construction Procurement Startup Lands $20M Series A
• AI-Enhanced Procurement Startup Zip Locks Up $190M At $2.2B Valuation

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Case in point: When tech stocks and startup funding hit their last cyclical peak four years ago, few knew it was the optimal time to cease new deals and cash in liquidatable holdings.

This time around, quite a few market watchers are wondering if the tech stock and AI boom has reached bubble territory. And, as we explored in Friday鈥檚 column, there are plenty of similarities between current conditions and the 2021 peak.

Even so, by other measures we鈥檙e also in starkly different territory. The current boom is far more concentrated in AI and a handful of hot companies. The exit environment is also much quieter. And of course, the macro conditions don鈥檛 resemble 2021, which had the combined economic effects of the COVID pandemic and historically low interest rates.

Below, we look at four of the top reasons why this time is different.

No. 1: Funding is largely going into AI, while other areas aren鈥檛 seeing a boom

Four years ago, funding to most venture-backed sectors was sharply on the rise. That鈥檚 not the case this time around. While AI megarounds accumulate, funding to startups in myriad other sectors continues to languish.

Biotech is on track to capture the smallest percentage of U.S. venture investment on record this year. Cleantech investment looks poised to hit a multiyear low. And consumer products startups also remain out of vogue, alongside quite a few other sectors that once attracted big venture checks.

The emergence of AI haves and non-AI have-nots means that if we do see a correction, it could be limited in scope. Sectors that haven鈥檛 seen a boom by definition won鈥檛 see a post-boom crash. (Though further declines are possible.)

No. 2: The IPO market is not on fire

The new offering market was on fire in 2020 and 2021, with traditional IPOs, direct listings and SPAC mergers all flooding exchanges with new ticker symbols to track.

In recent quarters, by contrast, the IPO market has been alive, but not especially lively. We鈥檝e seen a few large offerings, with , and among the standouts.

But overall, numbers are way down.

In 2021, there were hundreds of U.S. seed or venture-backed companies that on or , per 附近上门 data. This year, there have been less than 50.

Meanwhile, the most prominent unicorns of the AI era, like and , remain private companies with no buzz about an imminent IPO. As such, they don鈥檛 see the day-to-day fluctuations typical of public companies. Any drop in valuation, if it happens, could play out slowly and quietly.

No. 3: Funding is concentrated among fewer companies

That brings us to our next point: In addition to spreading their largesse across fewer sectors, startup investors are also backing fewer companies.

This year, the percentage of startup funding going to megarounds of $100 million or more reached an all-time high in the U.S. and came close to a record global level. A single deal, OpenAI鈥檚 $40 billion March financing, accounted for roughly a quarter of听 U.S. megaround funding.

At the same time, fewer startup financings are getting done. This past quarter, for instance, reported deal count hit the lowest level in years, even as investment rose.

No. 4: ZIRP era is long gone

The last peak occurred amid an unusual financial backdrop, with economies beginning to emerge from the depths of the COVID pandemic and ultra-low interest rates contributing to investors shouldering more risk in pursuit of returns.

This time around, the macro environment is in a far different place, with 鈥渁 鈥溾�� U.S. job market, AI disrupting or poised to disrupt a wide array of industries and occupations, a weaker dollar and a long list of other unusual drivers.

What both periods share in common, however, is the inexorable climb of big tech valuations, which brings us to our final thought.

Actually, maybe the similarities do exceed differences

While the argument that this time it鈥檚 different is a familiar one, the usual plot lines do tend to repeat themselves. Valuations overshoot, and they come down. And then the cycle repeats.

We may not have reached the top of the current cycle. But it鈥檚 certainly looking a lot closer to peak than trough.

Related 附近上门 query:

Related reading:

• The Great 鈥楢I Bubble鈥� Debate
• The Last Market Boom Ended 4 Years Ago. Here鈥檚 How Current Conditions Look Similar
• Biotech Share Of US Funding Hits Lowest Point In 附近上门 History
• Cleantech On Track For Weak Funding Year
• A Record Share Of Startup Funding Is Going To $100M+ Rounds
• SoftBank And OpenAI Make History With Largest Startup Financing Ever

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One such startup, , has secured $51 million in equity and debt funding, the company tells 附近上门 News exclusively.

The raise includes a $36 million Series C led by (Silver Lake Waterman) with participation from , 听补苍诲 , as well as $15 million in growth financing from . The financing brings Findem鈥檚 total funding since its 2019 inception to $105 million, with $90 million of that being equity, per the company.

Redwood City, California-based Findem鈥檚 mission is simple, even if its methods are not. It aims to transform how businesses 鈥渋dentify, attract and engage top talent.鈥�

The startup uses what it calls (out of a dataset developed out of 1.6 trillion data points) that it combines with AI to automate 鈥渒ey parts of the talent lifecycle.鈥� And those parts include building 鈥渢op-of-funnel鈥� pipelines of interested candidates, executive search and analyzing workforce and labor markets.

In an interview with 附近上门 News, co-founder and CEO said that Findem鈥檚 user base surged by 鈥渁bout 100x鈥� in the last 12 months and that the company is experiencing 3x year-over-year growth. Its enterprise customer base increased by 3x over the last year.

It has a user base of more than 12,000 customers, including from , , , 听补苍诲 , Kolam said.

Currently, Findem operates under a SaaS business model, charging per seat. As it expands its agentic abilities, the company plans to add an outcome-based model as well, according to Kolam. It is not yet profitable.

Findem is just one of more than a dozen startups at the intersection of AI and recruitment globally that have raised venture capital in 2025. As of early September, global startup investment for startups in the HR, recruitment and employment categories totaled around $2.3 billion, per 附近上门 data. That puts funding on track for a year-over-year gain, even as investment remains at a fraction of the levels hit during the market peak, as charted below.

How it works

Watching Findem鈥檚 platform in action provides better insight into just how it helps companies zero in on the specific talent for which they鈥檙e searching.

Say a startup wants to hire a software engineer who has worked at a company from its early days until it raised a Series C funding round. But it also wants that engineer to have a profile that it can view. Or, say a company wants to hire competitive coders who have seen a successful exit, or a CFOs who drove a company from a negative operating margin to a positive one.

Findem鈥檚 software will allow you to filter for all those desired attributes.

The startup says it鈥檚 able to help companies recruit so specifically because its 3D data combines people and company data over time into a format suitable for AI analysis. It claims that the 鈥渃ontinuously enhanced鈥� 3D dataset is 鈥渆xponentially larger and more factual鈥� than traditional sources of candidate data, making it a powerful tool for deep insights and automated workflows.

Using the combination of the data and AI, Findem creates 3D profiles, also dubbed 鈥渆nriched鈥� profiles, for every candidate it helps surface. The goal of the profiles is to provide 鈥渁 detailed and factual view鈥� of an individual鈥檚 鈥減rofessional journey and impact,鈥�

So just where does all this data come from? Findem says it continuously leverages a language model to generate that 3D data from more than 100,000 sources that are chronologically gathered (from earliest to latest).听

Those sources include , GitHub, , , personal websites, the , company funding announcements and IPO details, business models, more than 300 million patents and publications, over 5 million open datasets and ML projects, and over 200 million open source code repositories.听

It also pulls applicant profile information from applicant tracking systems such as , , , , and , among others.

This comprehensive data pull is what helps set Findem apart, in Kolam鈥檚 view. Some other hiring tools rely on one-dimensional data from resumes or LinkedIn profiles, which, he argues, 鈥済ive only a snapshot of someone鈥檚 career 鈥� without the context that reveals true potential.鈥� Kolam contends that it takes 鈥渆xtensive manual effort鈥� to verify and interpret the data.

鈥淛ust looking at a resume on paper really doesn’t come close to telling the whole story of how really qualified a candidate could be, or if they can really fit the criteria that a particular employer is looking for,鈥� Kolam maintains.

Findem is primarily focused on North American customers who have users across the globe. It鈥檚 also expanding into Europe. The company has a second headquarters in Bangalore, India.

Kolam declined to reveal Findem鈥檚 valuation, saying only that it was 鈥渁 significant up round and more than 2x鈥� compared to its valuation when it raised a $17 million-plus Series B extension in December 2023.

, managing partner at SLW, told 附近上门 News via email that his firm first got to know Kolam before Findem raised its Series B and then 鈥渢racked the company鈥檚 trajectory for some time.鈥�

鈥樷�橶hat drew us to Findem wasn鈥檛 just the technology, it was the traction,鈥� he said. “The team has achieved strong commercial momentum while tackling one of the most persistent challenges in HR 鈥� connecting data, insight and human potential in a way that actually drives business outcomes.鈥�

But the technology didn鈥檛 hurt.

In O鈥橬eill鈥檚 view, Findem鈥檚 main differentiator is its 鈥渄ata advantage 鈥� in a market where most companies are simply wrapping LLMs.鈥�

鈥淭he depth and breadth of their 3D profiles and web-scale dataset are unlike anything else in the market,鈥� he said. 鈥淭he UX is excellent, but the magic is really in how the platform leverages that data 鈥� it makes finding and understanding people effortless. We use it ourselves and see the power firsthand.鈥�

Related 附近上门 lists and queries:

Related reading:

• Funding To HR Software Startups Rises As M&A Activity Heats Up听
• 鈥嬧�婮ob-Related Startup Funding Points To More AI Screening And More 鈥楪igification鈥� Of Work
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That was one core finding from our latest analysis around funding for companies developing tools for employers and jobseekers.

A deeper dive into the numbers shows startups targeting frontline workers in industries such as healthcare, construction and retail comprised one of the larger investment themes. This translates into both deal flow and big checks. To illustrate, we used 附近上门 to put together a list of 14 recently funded听1 companies in this area.

Healthcare in the lead

Investment recipients include a mix of industry-specific and more general purpose offerings. But among sector-focused startups, healthcare stood as a favored area.

This makes sense given the sector鈥檚 longstanding status as a growth industry. Even amid the rather bleak U.S. August , healthcare was one of the few areas that saw measurable gains. It seems the is not going away.

Two of the largest funding recipients on our list 鈥� and 鈥� are tackling this predominantly in-person profession with different aims. McLean, Virginia-based ShiftMed has raised over $315 million to date for a platform helping employers bring local per diem nurses on board and tackle understaffing with AI-enabled scheduling tools.

New York-based Nomad Health, on the other hand, offers a platform for travel nurses to find jobs. The decade-old company has raised over $240 million in funding to date.

Construction, industrial and customer-facing businesses

Developers of employer tools for other industries are also generating enthusiasm with investors.

In the construction space, for instance, San Francisco-based is looking to build up its user base with $23 million in Series A funding this spring led by and . The 4-year-old company offers a single platform for contractors to manage payroll, HR, expenses and field operations.

In some ways, the startup fits in the category that Bessemer partner , who led the firm鈥檚 investment in Miter, calls 鈥渂usiness in a box鈥� companies. These are essentially platforms that business owners can use to handle administrative tasks and free up time to concentrate on their core offerings.

鈥淪o much of that is language-based work,鈥� Bennett said, regarding the peripheral demands of running a business, and so can see remarkable efficiency gains with the rise of AI-enabled language models.

Several others have raised rounds for tools targeting the manufacturing space, including San Francisco-based and Paris-based . In the hospitality industry, meanwhile, Paris-based raised a fresh fund this spring for a platform targeting hospitality industry employers.

Where the jobs are

For frontline work-related startups, it helps that this category encompasses most jobs. While remote work may seem widespread, nearly three-fourths of employed Americans still on a typical workday. Typically, frontline jobs are either difficult, impractical or flat-out impossible to carry out remotely.

Moreover, these are commonly sectors like healthcare, building and home services, that have shown to be more resilient of late, even amid a weakening job market. For employers, there鈥檚 apparently considerable appeal in tools that automate some of the drudgework and administrative work, to focus on their primary mission.

And for investors there鈥檚 also potential for some good returns. The most recent big exit offering validation for this thesis is , the software platform for home services providers that went public in December. Shares got a boost last week following a strong earnings report, pushing its market cap to around $11 billion. Seems you can do alright on public markets, too, as a software company focused on the frontline workforce.

Related 附近上门 list:

Related reading:

• Job-Related Startup Funding Points To More AI Screening And More 鈥楪igification鈥� Of Work

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