鈥淚 recognized both the massive potential AI brought to the tax world, as well as the risks to firms and clients by making mistakes and hallucinations,鈥� he told SA国际传媒 News.

The accounting industry has historically been slow to adopt new technologies. As of today, the majority of small to mid-sized accounting firms 鈥� which make up 90% of the market 鈥� remain stuck in a cycle of manual data entry.

Addressing both the opportunities 鈥� and risks 鈥� that came with advances in AI, Haase started building , a tax prep automation startup, on the side in 2023. Rather than targeting the self-prep market, like does, or the mega-enterprise firms that can afford $15,000-per-return software, Juno was built for the underserved SMB accounting firm.

鈥淲e continuously 鈥榙og fed鈥� the early Juno prototypes into the firm to see what worked best, what slowed things down, and to make it the most efficient tax preparation platform as possible,鈥� Haase said.

It took about a year and a half just to build integrations. 鈥淲e had to do a bunch of hacky things to be able to work with the existing tax software,鈥� he explained, 鈥渂ecause your typical tax software is actually around 15 to 20 years old and they don鈥檛 have public APIs.鈥�

By 2024, Juno had launched a co-pilot. Then, in July 2025, it had a tax product. The startup began onboarding other tax firms, growing to nearly 500 customers over the past year. Last year, Haase sold his accounting firm to focus on growing Juno full-time.

Today, he鈥檚 announcing that San Diego-based Juno has raised $12 million in a seed funding round led by , including participation from and .

AI to help humans 鈥榖e the advisers they were trained to be鈥�

What makes Juno different from others in the market, Haase believes, is that it operates on the premise that, at least for the foreseeable future, human tax preparers should be the ones driving the tax-return preparation process.

鈥淎 business or high-net-worth tax return requires hundreds of calculations, edge cases, deductions and more,鈥� said Haase, who holds an MBA from . 鈥淎I simply can鈥檛 do that with the 100% accuracy required not to get audited or charged with tax fraud.鈥�

Describing much of the manual work that most accountants must perform to complete returns as extremely tedious, Haase acknowledges that it鈥檚 also very easy for accountants to make mistakes that could prove very costly.

鈥淚n school, if you get a 93, an A, you get all the credits,鈥� he said. 鈥淏ut on a tax return, if you have a 99%, you fail, and your client could pay the price in penalties.鈥�

In a nutshell, Juno acts as the bridge between a client鈥檚 raw documents and the accountant鈥檚 filing software. It performs tasks like pulling data from IRS forms and even unstructured documents, such as business financial statements. Overall, it automates 90% of data entry across more than 90 document types while also flagging prior-year changes and inconsistencies for human validation.

The result is that a process that typically takes a human two to three hours is shrunk down to seven to 10 minutes, Haase estimates.

鈥淲e do 95% of a tax return in minutes, leaving the accountant to handle the strategic human decisions 鈥� the parts that actually save the client money,鈥� he said.

While he declined to reveal hard revenue figures, Haase said that in just eight months, Juno grew to mid-seven-figure annual recurring revenue.

The startup sells on a per-return basis, starting around $45, dropping to the low $30s for high-volume firms.

‘s recent move into consumer taxes and OpenAI’s hiring of a tax director show that the bigger players are eyeing the tax market. But Haase doesn鈥檛 feel threatened.

鈥淗igh-wealth individuals want assurance. If you鈥檙e paying $40,000 in taxes, you don’t want to 鈥榗ross your fingers with a chatbot,鈥� he said. 鈥淵ou want a human to talk to, someone who understands the context of your life.鈥�

Juno isn’t trying to replace accountants, he added.

鈥淚t’s trying to rescue them from the data-entry basement so they can actually be the advisers they were trained to be,鈥� Haase said.

The startup plans to roll out business returns soon, a move that Haase expects will significantly scale its customer base.

鈥楢 huge, obvious pain point鈥�

, co-founder and managing director of Bonfire Ventures, said he was drawn to invest in Juno because he believes the company is going after 鈥渁 huge, obvious pain point in a category that hasn鈥檛 been meaningfully modernized in a long time.鈥�

鈥淭he workflow pain is real, the labor dynamics make the timing right, and Dave brought exactly the kind of founder-market fit you hope to see,鈥� Andelman told SA国际传媒 News via email. 鈥淗e lived this problem before he built the company. That always matters.鈥�

The investor believes that tax prep is a category where trust is crucial to product success.

鈥淚f you鈥檙e going to bring AI into that workflow, it has to be transparent, auditable, and built with a human in the loop,鈥� Andelman added. 鈥淭hat鈥檚 what Juno understood early, and I think that鈥檚 a big part of why the product is resonating.鈥�

Fintech startups, particularly those that apply AI to traditionally manual or burdensome processes, have benefited from increased investment in recent quarters. Total global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per SA国际传媒 . That鈥檚 a more than 29% increase from 2024鈥檚 total of $41.6 billion raised.

Related SA国际传媒 query:

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Some are longstanding blue chip tech and pharmaceutical companies. Others are fast-growing venture-backed unicorns. And still others are more recent public market entrants looking to stay competitive in the age of AI.

To get a sense of who鈥檚 buying in bulk, we used SA国际传媒 data to put together a that acquired three or more seed- or venture-backed startups in the past three years. From there, we picked the most acquisitive names.

The most prolific startup acquirers of the past 3 years

Per SA国际传媒 data, the most prolific acquirers of seed- and venture-backed startups in recent years are 1, and . Overall, our query showed six companies with six or more known purchases, charted below.

For top-ranked Salesforce, high-volume M&A is nothing new. The San Francisco software giant has purchased at least 91 companies in the past 20 years, per SA国际传媒 data. Its most recent startup purchases include , a revenue orchestration platform, and , which focuses on agentic AI for e-commerce.

OpenAI, by contrast, has a shorter track record of M&A shopping sprees. The pioneering generative AI company has bought 16 companies in the past three years. Among the most recent was an deal involving open-source AI agent and its creator, . This month, it also snapped up , a creator of open source tools for software developers, and , an open-source tool for testing AI applications.

Snowflake, meanwhile, has 19 acquisitions to date. Most recently, it acquired , a developer of AI observability tools that previously raised more than $460 million in venture funding.

Notably, recent the active acquirers list for recent years looks quite a bit different that the ranking of all-time top M&A dealmakers in the SA国际传媒 dataset, shown below:

Highest-spending acquirers

The most prolific startup buyers also aren鈥檛 always the biggest check-writers. By the latter metric, the far-and-away leader is , and its $32 billion acquisition of .

For a broader picture view, we used SA国际传媒 data to put together a list of six companies that made the biggest-ticket funded startup acquisitions of the past three years.

2026 off to a promising start

So far this year, it looks like the pace of startup M&A dealmaking remains fairly robust.

This includes two deals in the multiple billions: 鈥檚 $5.15 billion purchase of and s $2.4 billion acquisition of . The AI sector鈥檚 appetite for acqui-hires and smaller purchases of earlier-stage startups also continues to boost momentum.

We鈥檒l see if it keeps up.

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• Small And Mid-Sized Startup Purchases Are Still Well Below The 2021 Peak
• SA国际传媒 Predicts: Why The Race For Talent And Tech Could Accelerate Startup M&A In 2026
• M&A The Highest On Record For Unicorn Exits In 2025

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

Busy week, big checks, lots of AI and robotics. That, in ultra-brief synopsis form, characterized the general startup fundraising environment this week. Notably, the two largest global rounds were U.K.-based and Paris-based , which raised $2 billion and $1.03 billion, respectively.

In the U.S., meanwhile, e-commerce platform , AI networking developer and industrial automation startup each picked up $500 million.

1. (tied) , $500M, e-commerce: Quince, an online fashion and home goods retailer with an affordable luxury theme, said it secured $500 million in Series E financing led by . The round sets a $10.1 billion post-money valuation for the 8-year-old, San Francisco-based company.

1. (tied) , $500M, AI infrastructure: AI networking startup Nexthop AI raised $500 million in Series B funding led by , with joining as a major investor alongside other backers. The Santa Clara, California-based company develops switching technology built on open-source operating systems for AI and cloud networking.

1. (tied) , $500M, robotics: spin-out Mind Robotics closed on a $500 million Series A round, co-led by and Andreessen Horowitz. The Palo Alto, California-based company is developing an AI-enabled industrial robotics platform, with a focus on automating industrial and manufacturing tasks at scale.

4. , $450M, robotics: Palo Alto, California-based robotics startup Rhoda AI emerged from stealth with $450 million in Series A funding reportedly led by . The startup trains robots using hundreds of millions of videos to develop intelligent models for operating in complex and changing environments.

5. , $400M, AI software creation: Replit, an agentic AI software creation platform, picked up $400 million in Series D funding at a $9 billion valuation, up from $3 billion just six months ago. led the financing for the Foster City, California-based company, joined by a long list of venture and celebrity investors.

6. (tied) , $200M, AI networking: AI startup Eridu emerged from stealth with over $200 million in a newly announced Series A round led by , , , and . Saratoga, California-based Eridu develops a high-performance network switch for AI data centers.

6. (tied) , $200M, artificial intelligence: Palo Alto, California-based Axiom Math AI, a developer of AI systems that can perform automated verification of computer code, $200 million in Series A funding at a $1.6 billion valuation. led the round, joined by , , and .

8. , $165M, robotics: Sunday, a startup planning a beta launch for a household robot called Memo later this year, raised $165 million in Series B funding. led the financing, which set a $1.15 billion valuation for the Mountain View, California-based company.

9. , $125M, cybersecurity: San Jose, California-based Kai, developer of an agentic AI cybersecurity platform, announced that it secured $125 million in funding led by .

10. , $100M, procurement: Oro Labs, developer of a procurement platform for enterprise customers, raised $100 million in Series C funding. and led the financing, which the company said follows a year of 300% revenue growth.

Global financings

The week鈥檚 largest rounds went to European startups.

, $2B, AI infrastructure: Nscale, an AI infrastructure hyperscaler, secured聽 $2 billion in Series C funding. and led the financing, which set a $14.6 billion valuation for the London-based company.

, $1.03B, artificial intelligence: Advanced Machine Intelligence, a startup co-founded by computer science pioneer and former AI chief , said it has raised $1.03 billion to develop 鈥渨orld models,鈥� or AI designed to learn from and interact with the physical world. The funding for the Paris-based company represents the largest seed round ever for a European startup.

Methodology

We tracked the largest announced rounds in the SA国际传媒 database that were raised by U.S.-based companies for the period of March 7-13. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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If a venture-backed company has gone more than four years between funding rounds, the forecast generally looks dim. It becomes increasingly unlikely that it will secure another good-sized financing or a sizable exit.

Four-year funding gaps are especially top of mind these days, as it鈥檚 been that long since U.S. venture investment hit its all-time peak. During the boom that lasted from 2020 to early 2022, software companies in particular routinely raised megarounds at rich valuations.

That, as we know, resulted in some strong exits, a lot of mediocre outcomes, and quite a lot that haven鈥檛 flourished.

Stranded software unicorns

For many, flush times came to an abrupt end. Per SA国际传媒 data, more than 150 boom-era U.S. software and software-related companies with $100 million or more in equity funding have not raised capital in over four years, remain private and have not been acquired.1

Collectively, they were a well-funded bunch. Companies in the cohort that raised their last round during the peak聽2 pulled in over $51 billion in aggregate funding, per SA国际传媒 data.

The list also contains a number of companies that were fairly high-profile startups several years ago. Examples include:

: The equity and fund management software platform raised close to $1.2 billion in total funding but hasn鈥檛 reported a new round since 2021.

: The NFT marketplace operator raised over $427 million in equity funding but closed its last round just over four years ago.

: The developer of the popular scheduling app secured $350 million in 2021 and hasn鈥檛 raised a round since. Since Calendly was mostly self-funded for its first seven years of existence, however, we鈥檇 guess it鈥檚 not a company that鈥檚 likely to be in financial distress.

Using SA国际传媒 data, we put together a longer sample featuring 10 companies.

Where are they now?

The ranks of companies that haven鈥檛 raised for years include a mix of those that are still active, have shuttered or are quietly winding down. For software startups in particular, many can continue eking along with a skeleton staff and a sparsely supported offering without formally shutting down. Or, they might be doing fine, given the capital they raised at the peak.

Given these are private companies, we can鈥檛 peek under the hood regarding details of their financial condition. All we can say is they haven鈥檛 disclosed a new round for some time.

Related SA国际传媒 query:

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• Global Venture Funding And Unicorn Creation In 2021 Shattered All Records聽

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A partner at (Google Ventures), Sakach has helped lead the firm’s investments in high-profile startups such as , , , and .

Unsurprisingly, considering her involvement in so many significant fintech deals, Sakach followed a fairly traditional path into finance. She started in the technology, media and telecom investment banking group at before moving into investing roles.

Sakach began her investing career at , focusing mainly on software and fintech businesses across buyouts and minority investments. Over time, she transitioned more toward growth and venture investing, joining in 2021.

In May 2024, Sakach landed at GV, where she now focuses on growth-stage companies, and in her view, her fintech background gives her an introspective lens to examine different verticals.

鈥淎cross my investments, the common thread is solving large structural problems with technology and data advantages,鈥� she said.

SA国际传媒 News recently spoke with Sakach to find out more about her investment thesis, her thoughts on what defines winning fintech and AI companies, how AI is affecting traditional software businesses, and how she determines what truly is a large opportunity.

This interview was edited for brevity and clarity.

SA国际传媒 News: Do you consider yourself a fintech investor or more of a generalist?

Sakach: I consider myself an investor first. Some venture investors define themselves by sector, but I鈥檝e always wanted to be the best investor possible, regardless of category.

I鈥檝e worked across stages and strategies 鈥� from banking to buyouts to growth equity to venture.

Those experiences are interconnected. For example, banking exposes you to companies at every lifecycle stage, buyouts focus on mature businesses, and venture focuses on emerging leaders.

At GV, we invest in hyper-scaling businesses early in their lifecycle that we believe could become public companies.

What does it take to build a successful fintech company today?

I think a lot about compounding businesses 鈥� companies that naturally grow in value as customers use them over time.

The best fintech companies share several characteristics: trust-based customer relationships because once customers trust a financial platform switching becomes difficult; expansion economics because over time, companies can upsell and cross-sell additional products; and a core infrastructure role, which allows them to become embedded in essential financial workflows.

For example, compounds through customer engagement and product expansion. continues to grow as a core infrastructure provider for global payments.

Even today, modern payment service providers still handle a minority of global payment volume, which highlights how much growth opportunity remains.

How do you evaluate fintech opportunities now compared to a few years ago?

Today, companies tend to fall into two categories: very early, highly novel ideas, often AI-driven, or late-stage compounding businesses with strong retention and expansion dynamics.

Execution quality is critical. Many fintech successes come from doing the fundamentals exceptionally well.

There鈥檚 also a large opportunity in automation within financial institutions 鈥� AI-driven efficiency improvements inside banks and financial operations.

How is AI affecting traditional software businesses?

AI has reduced technology as a durable moat. Many software products can now be rebuilt quickly. As a result, defensibility is shifting toward proprietary data, distribution channels, customer relationships and talent and research capabilities.

Companies that succeed will preserve or expand their distribution advantage, rebuild their product stack for an AI-native world, and learn from proprietary usage data faster than competitors.

The dividing line is roughly pre- and post-ChatGPT. Companies built before must replatform. Companies built after must start with the right architecture.

What excites you most about AI鈥檚 long-term impact?

I think about two categories of impact: cost reduction and expansion of possibilities. The most exciting outcomes come from expanding what鈥檚 possible, not just reducing costs. AI can increase access, scale services, and grow total output. For example, healthcare automation doesn鈥檛 just reduce expenses 鈥� it enables providers to serve more patients.

I focus on opportunities that expand outcomes dramatically rather than simply making existing processes cheaper.

Are current AI valuations sustainable?

The key difference between today and 2021 is the presence of a true platform shift. In 2021, capital surged and there was no comparable technological shift. Today, AI represents a foundational technology transition. So, capital is flowing toward transformative opportunities.

Another major change is structural. Venture capital has grown dramatically as an asset class.

Large funds must deploy capital, which increases competition and deal sizes. The critical question is not valuation alone. It鈥檚 whether investors are backing category-defining opportunities.

How do you determine what qualifies as a truly large opportunity?

You cannot make a small idea large simply by investing more capital. Investors evaluate things like market scale, structural tailwinds, timing (asking 鈥渨hy now?鈥�), team capability and potential for industrywide change.

We鈥檙e looking for ideas that can reshape entire systems if they succeed. Those opportunities are relatively rare, which is why selectivity matters so much.

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Nonetheless, the first couple months of the year have brought a steady stream of market entries from companies in sectors such as construction tech, space tech and biotech. Noticeably absent, however, are new offerings from SaaS companies, long an IPO market staple.

Per SA国际传媒 data, 11 venture- or seed-backed U.S. companies went public on major exchanges so far this year, raising just over $3 billion. Comparatively, that鈥檚 a fairly robust showing for the first couple months of the year, which tends to be a reasonably active period for IPOs.

Looking at recent years charted below, the first couple months of 2026 are well above the bottom ranks, but still far below the 2021 market peak for volume of offerings and total raised.

Leading offerings weren鈥檛 your typical VC-backed deals

The lineup of companies going public so far this year, however, includes many that don鈥檛 look like your typical VC-backed offering.

This includes the year鈥檚 largest VC-funded IPO: , a service that provides construction equipment rentals and support for building projects. The 11-year-old, Columbia, Missouri-based company raised more than $700 million in its January offering and had a recent market cap of over $7 billion.

The second-largest debut was also somewhat of an outlier: space tech company , which is majority-owned by private equity firm . It鈥檚 down from its initial trading price but recently valued around $3.4 billion.

Per SA国际传媒 data, there have been six IPOs of venture-backed companies this year that raised $200 million or more, which we list below.

SaaS squashed

It鈥檚 also noteworthy who isn鈥檛 on the list. For years, enterprise software companies have been among the more reliable IPO market entrants. This year, however, they鈥檝e been notably absent as the sector contends with an extended selloff fueled partly by concerns of AI-abetted disruption.

We鈥檙e also not seeing SaaS companies in the immediate IPO pipeline. A perusal of so far this year showed no venture-backed SaaS unicorns that submitted a new IPO filing in 2026.

It鈥檚 a sharp contrast to just a few months ago. One of last year鈥檚 splashiest IPOs 鈥� design software platform 鈥� is now down more than two-thirds from its peak. Another of the more recent big SaaS offerings 鈥� business travel and expense platform 鈥� has shed more than half its value.

Meanwhile, -backed , which provides tools for marketers and app developers, withdrew its planned IPO this month, amid the software route. It鈥檚 likely a delay, as that Liftoff filed a new confidential plan shortly afterward.

IPO market in an odd place

Overall, the IPO market is in an odd place at the moment. It鈥檚 an unfriendly scene for companies with business models viewed as vulnerable to AI-driven displacement. At the same time, there鈥檚 still continued buzz around the potential for record-setting offerings from , and .

Of those, the one rumored to be closest on the horizon is SpaceX, newly combined with at a reported $1.25 trillion valuation. The company is said to be eyeing a market debut as early as this summer.

If that happens, and the current SaaS squeeze continues, it wouldn鈥檛 be surprising to see a pattern of record-setting IPO returns coinciding with a very small number of actual debuts.

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• Yes, I鈥檓 Biased. But Still, Leading Unicorns Like Anthropic Should Be Prepping For IPOs

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The news was big in the fintech world with Brex claiming the pairing would represent 鈥渢he largest bank-fintech deal in history.鈥� ( had planned to buy in 2020 for $5.3 billion until that deal fell apart a year later due to regulatory concerns.)

In a joint statement, Capital One founder, chairman and CEO said it’s always been a goal of the bank 鈥渢o build a payments company at the frontier of the technology revolution.鈥�

鈥淎cquiring Brex accelerates this journey, especially in the business payments marketplace,鈥� he said. 鈥淏rex invented the integrated combination of corporate credit cards, spend management software and banking together in a single platform. They have taken the rarest of journeys for a fintech, building a vertically integrated platform from the bottom of the tech stack to the top.鈥�

While $5 billion is no small sum, it is less than half the that San Francisco-based Brex was valued at in October 2021. In total, the company has raised $1.7 billion in equity and debt since its 2017 inception 鈥� with about $1.2 billion of that being venture funding.

Early investors such as , which led Brex鈥檚 in 2017, are likely quite pleased with the outcome. Investors who wrote checks at its later stages are likely less so.

Other early backers include , and 1听.

The company has 1,100 employees, according to a Brex spokesperson who also told SA国际传媒 News that its business is growing 40% year over year and is profitable. Customers include , , , , and , among others.

Close friends Franceschi and , who co-founded Brex, started working together when they founded another company, Brazilian payment processing startup , in 2012 at the wee age of 16. That company ended up getting acquired by Stone Pagamentos for 鈥渢ens of millions of dollars鈥� 鈥� before the two had even gone to college.

A change of plans

Brex began its life as a buzzy startup that served mostly other startups. But in June 2022 鈥� three months after announcing it would make a into software and enterprise 鈥� Brex confirmed that it was apparently it started to serve: small to medium-sized businesses.

The abrupt news didn鈥檛 sit well with many of the SMBs it served.

Over time, Brex began to seemingly fall behind its largest rival, , when it came to fundraising and revenue generation. Ramp as of last November was valued at $32 billion, having raised a total of $2.3 billion in equity.

By joining Capital One, Brex says it will accelerate Capital One鈥檚 presence in corporate cards and spend management, complementing its existing leadership in SMB banking.

Capital One鈥檚 purchase of Brex is slated to close midyear.

Fintech M&A expected to pick up

On the heels of a strong year for venture funding to fintech startups, sources who spoke with SA国际传媒 News said they expect exits 鈥� both M&A deals and IPOs 鈥� in the sector to gain steam in 2026.

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• Visa And Plaid Pull Plug On $5.3B Merger Amid Increased Antitrust Scrutiny
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• Fintech Funding Jumped 27% In 2025 With Fewer Deals But Bigger Checks
• Fintech Forecast: Momentum Builds With Big Deals, IPO-Ready Companies And More AI

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

With the winter holiday season nearly upon us, this was likely the last busy week of 2025 for big funding announcements. And as weeks go, it was certainly an active one.

Perennial megaround raiser was the top funding recipient by far, securing a fresh $4 billion in Series L funding (yes, that is a thing) at a $134 billion valuation. Next on the list were data security platform and nuclear microreactor company , followed by startups in healthcare, biotech, fintech and AI.

1. , $4B, data and AI: Databricks that it is raising over $4 billion in a Series L financing at a $134 billion valuation, led by , and . The 12-year-old, San Francisco-headquartered company also said it crossed the $4.8 billion revenue run-rate in its third quarter,聽 growing聽 over 55% year over year.

2. , $400M, cybersecurity: New York-based Cyera, provider of an AI-enabled data security platform, reportedly $400 million in a funding round led by at a $9 billion valuation. The financing brings total funding to date for the 4-year-old company to $1.7 billion.

3. , $300M, nuclear power: Radiant, a maker of portable nuclear microreactors, it closed on over $300 million in Series D funding led by and . The El Segundo, California-based company said it plans to break ground early next year on a factory in Oak Ridge, Tennessee.

4. , $250M, healthcare software: Tebra, a provider of patient record software for healthcare private practices, says it raised $250 million in equity and debt financing to invest in AI and automation. led the equity financing, which constituted most of the round, while provided the debt funding for the Corona del Mar, California-based company.

5. (tied) , $150M, fintech: New York-based Imprint, a provider of credit cards affiliated with consumer brands, raised $150 million in Series D funding at a $1.2 billion valuation. led the round, with participation from , , , and .

5. (tied) , $150M, satellite intelligence: HawkEye 360, a provider of technology to detect, geolocate and characterize radio-frequency emissions, says it landed $150 million in Series E equity and debt financing. and co-led the equity funding, while provided the debt. The Herndon, Virginia company says it also completed its acquisition of .

7. , $130M, biotech and AI: Chai Discovery, a startup that uses AI to predict and reprogram interactions between biochemical molecules, landed $130 million in a Series B round. and led the financing, which set a $1.3 billion valuation for the San Francisco-based company.

8. (tied) , $125M, biotech: Irvine, California-based Ambros Therapeutics launched publicly with a $125 million Series A financing co-led by and ‘s strategic health care investment arm . The company licensed the rights to neridronate, which is used to treat Complex Regional Pain Syndrome.

8. (tied) , $125M, microprocessors: Mythic, an Austin-based startup developing semiconductor architecture to make AI computing more energy efficient, raised $125 million in a funding round led by and joined by a long list of venture investors.

10. , $120M, biotech: Cambridge, Massachusetts-based Atavistik Bio, a developer of聽 allosteric small molecule therapeutics, raised $120 million in Series B funding led by and . Founded in 2021, Atavistik has raised $220 million in known funding to date, per .

Methodology

We tracked the largest announced rounds in the SA国际传媒 database that were raised by U.S.-based companies for the period of Dec. 13-19. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

Illustration:

Rat, who had served as a product manager at companies including , and , dug into the problem and discovered that 鈥渕ost of the software used in the industry鈥� was more than 20 years old and still required physical services onsite.

鈥淢ost lacked integration with other platforms, were slow and buggy, and impossible to train new employees on,鈥� he recalls.

So Rat teamed up with , a former director of engineering at Uber, to start , an AI-powered platform that aims 鈥渢o put dental practices on autopilot.鈥� The pair previously led the rebuilding of Uber’s payment platform that’s still in use today.

鈥淚 realized there was a massive need and opportunity for a modern, cloud-based software platform and set out to build that,鈥� Rat told SA国际传媒 News. 鈥淚 also realized bigger tech players have been building software for the larger healthcare market but overlooked the $500 billion dental industry.鈥�

And now, Archy has just raised $20 million in Series B funding to help it grow even more, it told SA国际传媒 News exclusively. led the financing, which also included participation from , , and 25 practicing dentists who wrote checks as angel investors. The raise brings Archy鈥檚 total funding to date to $47 million, Rat said.

The company raised led by Entr茅e Capital almost exactly one year ago. Rat confirmed the Series B was an up round, but declined to disclose Archy鈥檚 valuation.

All-in-one tool

Archy claims to replace more than five existing tools to handle scheduling, charting, billing, imaging, insurance, payments, staffing, messaging and reporting 鈥渇rom one login.鈥�

It is now building AI agents 鈥渢o handle the busywork鈥� such as checking eligibility, filing and following up on claims, writing notes, managing patient communications and scheduling, and 鈥渢urning raw practice data into clear answers,鈥� according to Rat.

The startup processes more than $100 million in payments annually across 45 states and has seen roughly 300% year-over-year growth, he said. It currently serves 2.5 million patients and has processed over 35 million X-rays through its platform.

The company claims that mid-sized dental practices report saving around 80 hours a month by using its technology, and are able to avoid 鈥渂ig hardware costs.鈥� For example, Rat said that one practice saved about $50,000 in its first year of using Archy.

Dual-revenue model

San Jose, California-based Archy operates on a dual-revenue model that combines subscription-based fees with payment processing services, and offers tiered monthly subscription packages. In addition to its subscription fees, Archy serves as a merchant processor for its clients, generating revenue from a percentage of payment transactions processed through the platform.

鈥淭his hybrid approach allows us to remain aligned with our clients’ success while providing flexible options that scale with their business needs,鈥� Rat told SA国际传媒 News.

The company plans to use its new capital to 鈥渉ire aggressively鈥� across its engineering, AI and go-to-market teams. Presently, it has 57 employees. It plans to expand internationally starting in 2026.

, partner at TCV, told SA国际传媒 News via email that his firm had been looking for a way to invest in the dental space 鈥渇or a long time鈥� but didn鈥檛 find a company that was 鈥渁ppropriately tackling the root of the problem 鈥� the core PMS (practice management systems)鈥� until it came across Archy.

He added: 鈥淲e consistently heard that Archy was supremely easy to use, requiring almost no training in contrast to others, providing a seamless 鈥榠Phone-like鈥� experience, and reducing what took 10 clicks in other software to one or none in Archy.鈥�

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Just over a year ago, my co-founders and I realized that our company had an existential problem.

The product we had been building and selling 鈥� a SaaS platform for sales engineers 鈥� was rapidly going to be made obsolete by AI.

When we tried to envision how our software would fit into an AI-enabled future, we realized there simply wasn鈥檛 going to be a future where people interacted with our software the way they do today. The world of SaaS tools will eventually be killed by AI-native interfaces.

We needed to start over and rebuild a product for the future from scratch. And if we were going to survive, we needed to do it without losing the bulk of our customers.

Here鈥檚 how we managed it.

Same outcomes, brand-new world

It鈥檚 important to recognize that this wasn鈥檛 a case of selling customers on an existing platform upgraded with AI features. Instead, we needed them to embrace a brand-new, AI-native product that would completely replace their existing workflows.

For a moment we asked ourselves whether we should even expect our customers to move over for us.

But the reality was that we were still aiming to solve the same problems 鈥� plus so much more with the new vision. Our existing customer was still our ideal customer profile. They bought us to solve a specific problem: improve sales productivity for sales teams selling complex products.

Our goal was to deliver the same outcomes, but far more effectively. Instead of providing a SaaS system to keep track of work done by humans, we would provide an AI system that could do the work itself.

As the CEO, I realized that it was on me to communicate such a dramatic change to our customers. I reached out to many of them across every channel I could find 鈥� I sent personal emails and personal messages, and in many cases I scheduled calls to talk through the details and answer their questions.

The message boiled down to this:

鈥淎I is a once-in-a-generation technology shift. We鈥檙e not doing you any good as a customer if we keep building things for a world that doesn鈥檛 have a future. We want to give you the same outcomes, and so much more, in a brand new world.鈥�

Three types of customer transition

For a startup founder, explaining a vision is easy. Things get harder when you start getting contracts involved.

As we looked at how to transition our customers from their existing agreements to the new product, we found that we had to have three types of conversation.

Our customers paid for user licenses, and our approach depended on their level of utilization with our existing product. The first group of customers were those who were basically completely utilized and relying on our existing SaaS product.

For those customers, our approach was essentially a net new cross-sell sales cycle, helping them to secure new budget for the new product we were selling. Over time, we expected them to free up budget as users transitioned from the old platform to the new platform, but these heavily utilized customers needed us to help them communicate the new direction and secure additional budget.

While those were tough conversations, the majority of SaaS customers are not typically 100% utilized. For customers that had some capacity, we were able to offer a middle path. We took the amount that those customers were underutilized and offered it as a credit to use the new service.

That way they could prepare for the transition by having some users on the new service as a forward-deployed team; once it became time for renewal, those users could help with change management and support the rest of the organization.

The last group of customers were those who were underutilized but didn鈥檛 have significant change management needs. These companies 鈥� typically smaller, more nimble organizations 鈥� could simply take their existing spend and move it from point A to point B. For those customers, we just turned off the SaaS service, booted up the new AI platform and provided the same level of training that we would provide to a net new customer.

The result? Across all three groups, more than 80% of our customers have already transitioned or are in the process of transitioning to the new platform. While it wasn鈥檛 easy, the result is a stable company that鈥檚 now built to thrive in the AI era.

What we learned

When we were deciding what to do a year ago with our suddenly disappearing product roadmap, we settled on a specific motto: Instead of waiting for the axe to fall, prepare for a world where you have no head.

Right now there are hundreds of SaaS companies that are anxiously waiting for the moment when AI renders their product or service obsolete. Instead of trying to wring the last drops of revenue we could out of an inferior product, we chose to make a bet and build into the fog.

We learned a few key lessons in the process:

• Rip off the Band-Aid: While the decision sounds easy in hindsight, the actual change itself had to be handled extremely delicately. We had to reassess team members to determine who could support the new product while maintaining the existing product at the same time, and we had to let go of employees who no longer fit with the new vision of the company. We also had to make the case to our investors that we were still on the right path. The longer we waited to change our platform, the harder the transition would have been 鈥� this is a moment for decisive action.
• Don鈥檛 sugarcoat the situation: In all of our conversations with employees, investors and customers alike, we gave them a straight, unvarnished story. By being brutally honest about how we saw the market, we maintained a lot of credibility at a moment when it would have been fair to question our judgment.
• Look for easy compromises: We could have taken a take-it-or-leave-it approach with our customers. We believed in our new product and didn鈥檛 see a long-term future for our old one. But a rigid approach probably would have led to a lot more lost customers, even though we were still solving the problems they bought us for in the first place. Finding the middle ground and supporting companies that needed to linger on the older SaaS platform a little longer allowed us to keep more customers in the fold and maintain a stable business during a period of disruption.

In the end, we found one more silver lining to our year of disruption. In talking to our customers, there were a few who were approaching renewal who weren鈥檛 planning to continue with the previous SaaS platform. But the new AI platform? They didn鈥檛 just renew 鈥� they expanded.

is the CEO and co-founder of , the AI sales teammate. Prior to Vivun, he built the global presales team and ran multiple product lines during ‘s IPO run.

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