All Stories
Most Active And Highest-Spending Startup Investors Diverged In Q1
The investors backing the highest number of startup rounds this past quarter were mostly not the ones writing the biggest checks. And the ones funding the largest deals were not the most prolific dealmakers. That, in broad strokes, was the state of startup funding in Q1 of this year, a period characterized by record-setting rounds and investment tallies. The most famous names in AI captured a lion’s share of funding, drawing in some deep-pocketed backers who are traditionally less active in venture. This includes the quarter’s two lead investors in the priciest rounds — D.E. Shaw and MGX. The two co-led mega-financings for both OpenAI and Anthropic collectively valued at over $150 billion. By deal count, meanwhile, the most active post-seed investor was familiar front-runner Andreessen Horowitz, while the busiest lead investor was Accel. To see who else ranked high for deal counts and totals, below we charted out active investors across multiple metrics, including venture, seed and lead investment. Most active and highest-spending lead investors We’ll start with lead investors, as these are typically the ones putting the most capital to work. For Q1, the most active lead investors in post-seed rounds were Accel, Andreessen Horowitz, and Lightspeed Venture Partners. Overall, 19 investors led six or more rounds this past quarter, as charted below. Of course, the most active lead investors aren’t always the ones writing the biggest checks. We don’t have an exact measure for the latter, but we can get a sense by looking at lead investors in rounds with the highest aggregate value. By this metric, lead investors in the quarter’s two biggest rounds — OpenAI’s record-setting $122 billion financing and Anthropic’s enormous $30 billion Series G — rank highest on our list. This includes tech giants Nvidia and Amazon, which took part as strategic investors in the OpenAI round. Below, we rank the top 26 by total value of Q1 lead investments. Busiest post-seed investors As for sheer deal count at post-seed, familiar names once again topped the list. This included investors participating in rounds as both lead- and nonlead backers. For this category, Y Combinator participated in the highest number of rounds — 47 in total for Q1. While the storied accelerator is best known as a seed backer, it also racks up deal count at later stages by partaking in follow-on rounds for startups it helped incubate. The next-busiest post-seed investors for the quarter were Andreessen Horowitz, Lightspeed, General Catalyst and Sequoia Capital. For a bigger-picture view, below we rank the 18 most active by this metric. Prolific seed dealmakers At seed, Y Combinator once again captured the top slot for most active. Next on the list were the regularly featured Antler, Soma Capital and 500 Global. Below, we ranked the top 21 busiest seed investors. Familiar names, unfamiliar sums Overall, the standout takeaway from the Q1 most active investor rankings isn’t the names on the list. Most are familiar players in the space, balanced out by a few more sporadic investors lured by the promise of AI. No, what stands out for Q1 is the size of the deals getting done and the overwhelming concentration of capital around AI. We’ll stay tuned to see if either of these trends lets up or further intensifies in coming months. Related reading: Illustration: Dom Guzman
5 Interesting Startup Deals You May Have Missed: A Credit Card Backed By Mineral Rights, Flying Ferries, And A Foundation AI Model For Plants
This is a monthly column that runs down five interesting startup funding deals that may have flown under the radar. Check out our previous entry here. In a quarter when nearly two-thirds of global venture capital went to just four companies, it’s easy to lose track of the many other companies getting funding to tackle interesting problems. Nonetheless, we spotted five companies in just the past month working on issues from cleaner ferries and trains to foundational AI for plants. Let’s take a closer look. $55M for a mineral rights-backed credit card Natural resources can be incredibly valuable financial assets, but you can’t exactly buy your weekly groceries with oil or water rights. That’s an issue that a Dallas-based fintech startup aims to solve. Frontlands recently raised $50 million in a debt round from StarMesa Capital to provide a credit card to U.S. households holding mineral rights to natural resources such as oil, natural gas, solar, wind or water. “For the millions of mineral rights owners in the United States, these rights are one of the most valuable assets the family owns. But these families are just like the rest of Americans and often are carrying revolving credit card balances at more than 25% [interest],” Frontlands CEO Brandon Cotter said in a statement. “Historically, owners have had few options to access the value trapped inside their mineral rights without selling.” Its AI system combines machine learning, production data, royalty payment histories, lease terms, commodity price forecasts, geologic data and traditional decline curve analysis to automate the underwriting process, the company says. While it’s historically been difficult for traditional lenders to assess natural resources as collateral, Frontlands says its process typically delivers a same-day credit decision. The company’s recent credit facility is in addition to a $5.5 million equity raise announced in December from venture investors including Cambrian Ventures, Fiat Ventures, Wischoff Ventures and Lime Rock Partners. Frontlands said its average credit line in early markets — Texas, Pennsylvania, New Mexico, North Dakota, Wyoming and Oklahoma — is more than $30,000. It plans to launch its credit card product this summer in partnership with Texas-based sponsor bank TransPecos Banks. Frontlands said it also expects to raise a Series A round later this year. “Our goal isn’t to pile on more debt,” Cotter said in a statement. “But the opportunity to help our customers move away from high-interest credit card debt — and provide a path toward greater financial stability — is compelling.” Investment in fintech startups hit a multiyear high in 2025, Crunchbase data shows, though remains well below the peak. Many of the best-funded companies in recent quarters have brought AI to bear on traditionally more manual or cumbersome processes in the financial services industry. Related Crunchbase query: Funding To Financial Services Companies $32M for ‘flying’ electric commuter ferries As of this writing, oil prices are hovering around $100 a barrel — down from an even greater peak a few weeks earlier, but still among the highest levels seen in years, as the U.S.-Iran war disrupts global energy markets. So Swedish electric vessel maker Candela’s recent funding of €30 million (about $32 million) seems timely. The Stockholm-based company makes electric “flying” boats that are used as commuter ferries. They differ from traditional vessels by using computer-controlled hydrofoils to lift the hull above the water, an approach the company says dramatically reduces drag and cuts energy use by up to 80% — enabling faster, smoother, zero-emission travel compared to conventional diesel ferries that push through the water. “From a physics perspective, ships have been essentially the same for hundreds of years,” Candela founder and CEO Gustav Hasselskog said in a statement. “We’re redefining waterborne transport by effectively creating a new category of vessel. This allows cities and municipalities to finally take full advantage of waterways — while escaping the fossil-fuel cost trap that has long prevented them from being used efficiently.” Its P-12 vessels have already been deployed as commuter ferries in Stockholm, Gothenburg, Oslo and Trondheim. The new funding was led by The World Bank’s International Finance Corp. arm and included previous investors EQT Ventures, SEB Private Equity, KanDela and Ocean Zero LLC. The capital will primarily be used to fund a second factory in Poland. Candela says it has more than 65 vessels on order and planned deployments across markets including India — where a fleet of 10 of its P-12s will reportedly cut travel times from Navi Mumbai Airport to the city center from around two hours to 35 minutes — the Middle East and Southeast Asia. The startup’s funding defies an overall downturn in clean-tech funding. Funding for clean-tech related startups totaled $26.9 billion in 2025, down 23% year over year and the lowest annual amount since 2020, Crunchbase data shows. Related Crunchbase query: Global Cleantech Startup Funding In 2025 $30M to electrify trains with batteries and microgrids Let’s now turn from waterways to train tracks, with another company that recently raised significant funding aimed at giving centuries-old transportation systems a green overhaul. Voltify, a Philadelphia-based startup, said last month that it raised $30 million in seed funding led by Australian mining company Fortescue Future Industries and Israeli venture firm Aleph to develop a new way of powering freight rail that avoids the high costs of traditional electrification. The startup positions its technology as a way to decarbonize one of the world’s most efficient but still fossil-fuel-dependent transport systems. It’s targeting a major pain point for the rail industry: its heavy reliance on diesel. In North America alone, the six largest freight rail operators spend roughly $11 billion annually on diesel fuel, while full electrification of rail networks could cost more than $1 trillion, according to Voltify. Instead of relying on overhead wires, Voltify says it’s building a system that combines battery-equipped railcars with technology that allows trains to recharge while moving. The goal is to help rail operators cut emissions and fuel costs without requiring massive infrastructure overhauls. Its approach — using mobile batteries and distributed charging via microgrids — aims to sidestep those costs by retrofitting existing trains and building localized energy systems rather than rebuilding entire rail networks. CEO and co-founder Daphna Langer told The Wall Street Journal that the company has signed a paid pilot agreement with a Class 1 railroad, though she declined to name the customer, citing a confidentiality agreement. She noted in a LinkedIn post that raising funding for a transportation company in the current market was difficult. “Securing capital in the hardware space and traditional industries is challenging,” she wrote. “It is not the ‘in’ space; there is no FOMO at play, so we need to focus on metrics and execute quickly. With some of the top 5 largest rail companies globally and a large order pipeline, we are determined to keep moving at lightning speed.” Related Crunchbase query: Global Transportation Venture Funding In 2026 $7M for foundation AI for biology Funding to foundational model AI startups surged last quarter, reaching $178 billion, per Crunchbase data. But the vast majority of that funding went to AI giants like OpenAI and Anthropic that are building general-purpose GenAI models. Such models are fundamentally lacking for hard sciences, argues Living Models, a startup based in Paris and Berkeley, California, that last month raised $7 million in seed funding to develop foundation AI for biology trained on DNA, RNA and data from other “omics” fields, rather than human text. The company’s first family of transformer models is called Botanic and is trained on data from 43 plant species. Living Models noted that it’s starting with the commercial crop industry, a massive global market that has abundant data, well-established research infrastructure, and fewer regulatory concerns and faster commercialization timelines than the pharmaceutical industry. “Plant biology combines three properties that make it an ideal first domain for biological foundation models: genomic data is abundant and largely unrestricted, the commercial need is acute and quantifiable, and the feedback loop between computational prediction and real-world validation is well established through existing breeding infrastructure,” the company said in a statement. The global seed industry is also dominated by a handful of incumbents, it noted: Bayer CropScience, Corteva Agriscience, Syngenta, BASF and Limagrain — companies that already spend billions of dollars a year on breeding research. “Biology is an information problem at every scale, from a single cell to an entire ecosystem. The genomic data exists across many domains; what’s been missing is a model architecture capable of learning from it at scale,” Leonard Strouk, Living Models’ CTO and co-founder, said in a statement. “We start with plants because the data is rich and the breeding cycle is a clear bottleneck, but the same approach applies wherever sequence data meets slow, empirical discovery.” The company’s recent funding was led by Artesian VC, Asterion Ventures, GrainCorp and The Galion Project. Other investors included Station F and Berkeley SkyDeck Fund. Related Crunchbase query: Foundational AI Funding In 2026 $2.1M for a brain-stimulating consumer wearable Billions of dollars a year are spent on therapy and other mental-health treatments, yet measuring progress can be elusive. That’s one of the issues that San Francisco-based Mave Health aims to take on with a neuromodulation wearable headset that it says can reduce stress, improve attention span and mood, and more quantitatively measure mental health scores. Mave’s device uses transcranial direct current stimulation, or tDCS, a noninvasive technique that delivers a low electrical current to the brain through electrodes placed on the scalp, with the aim of modulating neural activity. The technology is generally considered safe when used by adults as directed in controlled settings. Mave’s neuromodulation wearable headset. (Courtesy photo) The company last month raised $2.1 million in seed funding led by Blume Ventures, with participation from individual investors including Tesla Autopilot AI lead Dhaval Shroff. Crucially, Mave says it does not plan to pursue FDA medical-device approval for its product, which sells for $495. Instead, it is positioning the gadget as a wellness tool that consumers can use on a daily basis to improve their mental well-being and better measure the outcomes of talk therapy or other treatments. “If you ask a psychologist how do you know if a person is making progress, their response to it is very standard, which is that it’s not about progress. It’s about process […] But for somebody with depression who is spending a lot of time in therapy, progress is important. So how do you know whether they’re making progress or not? And even these basic questions were not being answered,” co-founder Dhawal Jain told TechCrunch. Mave’s funding comes amid an overall downturn in investment for wellness and fitness-related companies, although select wearables makers including Whoop and Oura have raised significant funding in recent years. Related Crunchbase query: Fitness- And Wellness-Related Startup Funding Related reading: Illustration: Dom Guzman
North America Q1 Funding Surges Across Stages To Record Level
The first quarter was one for the North American venture capital record books. U.S. and Canadian companies secured a staggering $252.6 billion in seed- through growth-stage funding rounds per Crunchbase data. That’s more than 3x the total raised in the prior quarter, and the largest quarterly total of all time. Predictably, artificial intelligence was the driver. More than 87% of Q1 investment went to companies in Crunchbase AI-related categories. To say these are record funding tallies is somewhat of an understatement. It’s more like Q1 smashed the prior quarterly record — $95.7 billion — set in Q3 2021. Just a single financing for OpenAI was bigger than the prior quarterly record for all startup funding rounds put together. And the four next-largest financings totaled almost as much as the prior quarter, which at the time we considered a very strong period for startup funding. So, in summary, it was a lot of money. For a more detailed picture, we drill down more deeply into how that largesse was distributed across stages and sectors. We also take a look at exits for the quarter, including both IPOs and acquisitions. Table of contents AI We’ll start with AI, since that’s where the overwhelming majority of the money went. A staggering $221 billion went to North American companies in Crunchbase AI-related categories in the first quarter. That’s about 6x the AI investment total from the prior quarter, which was itself no slacker on this front. For perspective, we charted out AI-related funding over the past 13 quarters to compare. A few megarounds for high-profile companies accounted for most of the quarter’s AI funding, led by OpenAI, Anthropic, xAI and Waymo. Later stage and technology growth These same names factor heavily in tallies for late-stage and technology-growth funding, which comprised the vast majority of total startup investment. Per Crunchbase data, $222.4 billion — or 88% of all North America startup investment — went to rounds at these stages. That’s more than 5x the prior quarter’s tally, and more than triple year-ago levels. The gains were driven by bigger deals, not more of them. Later- and growth-stage round counts were actually down a smidge sequentially in Q1. For perspective, below we chart round counts and investment totals at this stage for the past five quarters. Enormous rounds for AI companies accounted for a majority of the late- and growth-stage totals. The biggest of these was OpenAI’s record-setting $110 billion February financing led by Amazon, Nvidia and SoftBank. The generative AI giant topped it off with a further $12 billion raise in March. Anthropic secured the quarter’s next-biggest late-stage financing — a $30 billion February Series G — followed by xAI, which announced a $20 billion Series E in January. Waymo landed another of the quarter’s very big deals, with a $16 billion February Series D. Early stage Early-stage investment was also running high in Q1, albeit not setting records. Overall, investors put $25.1 billion into deals around Series A and Series B stage in the first quarter. That’s up 17% from the prior quarter and 56% from year-ago levels. It’s also the highest quarterly total in over three years, though still below peaks scaled in 2021. Early-stage round counts, meanwhile, were down a bit, indicating investors’ increasingly concentrating their bets among perceived star performers. As usual, a few jumbo-sized deals significantly boosted the early-stage totals. For Q1, this included four rounds of $500 million or more. Of these, Austin-based humanoid robotics startup Apptronik was the biggest fundraiser, pulling in $520 million in a February Series A. Three other companies secured $500 million financings: AI infrastructure developer Nexthop AI, semiconductor startup MatX, and industrial robotics-focused Mind Robotics. Seed Seed-stage investment, meanwhile, did not show an upswing but remained at historically robust levels. Per Crunchbase data, an estimated $5.1 billion went to seed and pre-seed investments in Q1. That’s roughly flat with the prior quarter and up a bit from year-ago levels. Seed round counts declined in Q1, both sequentially and year over year. However, we expect these tallies to rise some over time, along with investment totals, as seed deals commonly get added to the data set weeks after they close. Exits Exit activity was fairly staid in comparison to the high-rolling startup fundraising environment. That said, the IPO market did boast a few sizable startup debuts. Of these, the largest was the January IPO of construction equipment rental marketplace EquipmentShare, followed by space tech company York Space Systems, and crypto platform BitGo. Below, we aggregated a list of 12 private, venture-backed companies that carried out IPOs on U.S. exchanges. Acquirers also announced several large deals to purchase venture-backed private companies. The priciest planned M&A deal was Capital One’s agreement to purchase business credit card provider Brex for $5.15 billion. Biotech also delivered some large outcomes, including Eli Lilly’s planned acquisition of RNA therapeutics startup Orna Therapeutics, and Novartis’ purchase of allergy treatment startup Excellergy. Below, we put together a list of five of the quarter’s biggest M&A deals.1 Big picture: A paradigm shift Having written many of these funding reports over the years, it’s common for one quarter to quietly blur into another. Not so for Q1 of 2026. The just-ended quarter cemented a notion that startup insiders have been circling for some time: Private markets now have the capital stores and appetite for ultra-high valuations to rival public markets. For evidence, look no further than OpenAI’s $122 billion raise at a valuation higher than all but a handful of the largest large-cap technology companies. IPO enthusiasts may pine for a future period when these most sought-after foundational AI names finally do make it to public markets. But for now, they’ve demonstrated there are plenty of investors willing to shell out billions in private offerings as well. Related Crunchbase queries: Methodology The data contained in this report comes directly from Crunchbase, and is based on reported data. Data is as of March 31, 2026. Note that data lags are most pronounced at the earliest stages of venture activity, with seed funding amounts increasing significantly after the end of a quarter/year. Please note that all funding values are given in U.S. dollars unless otherwise noted. Crunchbase converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to Crunchbase long after the event was announced, foreign currency transactions are converted at the historic spot price. Glossary of funding terms Seed and angel consists of seed, pre-seed and angel rounds. Crunchbase also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less. Early-stage consists of Series A and Series B rounds, as well as other round types. Crunchbase includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million. Late-stage consists of Series C, Series D, Series E and later-lettered venture rounds following the “Series [Letter]” naming convention. Also included are venture rounds of unknown series, corporate venture and other rounds above $15 million. Corporate rounds are only included if a company has raised an equity funding at seed through a venture series funding round. Technology growth is a private-equity round raised by a company that has previously raised a “venture” round. (So basically, any round from the previously defined stages.) Illustration: Dom Guzman
The Week’s 10 Biggest Funding Rounds: Largest Financings Went To Defense, Wearables, Energy And Security
Want to keep track of the largest startup funding deals in 2025 with our curated list of $100 million-plus venture deals to U.S.-based companies? Check out The Crunchbase Megadeals Board. This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here. Startup investors kept up the busy dealmaking pace this week with a number of big rounds. Top among them was a $1.75 billion Series D for Saronic, developer of autonomous vessels. Other big funding recipients hailed from sectors including fitness wearables, energy tech, cybersecurity and AI infrastructure, among others. 1. Saronic, $1.75B, autonomous ships: Austin-based Saronic, a defense tech startup focused on autonomous sea vessels, raised $1.75 billion in Series D funding, bringing total funding to around $2.6 billion. Kleiner Perkins led the round, which set a $9.25 billion valuation for the company, more than double its Series C level in 2025. 2. Whoop, $575M, fitness wearables: Whoop, a provider of wearable fitness technology and a subscription platform that tracks physiological data, secured $575 million in Series G funding. Collaborative Fund led the financing,which set a $10.1 billion valuation for the Boston-based company. 3. Valar Atomics, $450M, nuclear energy: El Segundo, California-based nuclear energy startup Valar Atomics, raised fresh capital at a valuation of $2 billion, according to a Bloomberg article citing unnamed sources. The financing reportedly included $340 million in equity funding and $110 million in debt. 4. EnerVenue, $300M, battery technology: EnerVenue, a developer of grid-scale energy storage technology, says it closed on a $300 million extension of its Series B preferred round led by Full Vision Capital. The Fremont, California-based company also appointed a new chief executive officer, Henning Rath. 5. Tenex.AI, $250M, cybersecurity: Sarasota, Florida-based AI-enabled cybersecurity startup Tenex picked up $250 million in Series B funding led by Crosspoint Capital Partners. The company said it plans to use the funds to hire more than 250 people and supplying them with AI technology that makes them “ten times more efficient.” 6. Also, $200M, micromobility: Also, an electric mobility company spun out of Rivian, raised $200 million in a Series C round backed by Greenoaks, DoorDash, and Prysm Capital. The Palo Alto, California-based startup’s product lineup includes bikes, small autonomous EVs for deliveries, and associated gear. 7. Starcloud, $170M, space tech: Starcloud, a space infrastructure startup focused on building orbital data centers, secured $170 million in Series A funding led by Benchmark and EQT. The financing sets a $1.1 billion valuation for the Redmond, Washington-based company, making it the fastest Y Combinator alum to achieve unicorn status after demo day, which was 17 months ago. 8. ScaleOps, $130M, cloud infrastructure: New York-based cloud and AI infrastructure startup ScaleOps landed $130 million in Series C funding. Insight Partners led the financing, which set a valuation of over $800 million for the 4-year-old company. 9. Ambrosia Biosciences, $100M, biotech: Boulder, Colorado-based Ambrosia Biosciences, a developer of next-generation oral therapeutics for obesity and related cardiometabolic diseases, picked up $100 million in Series B funding led by Blue Owl, Redmile Group and Deep Track Capital. 10. OpenFX, $94M, money transfer: OpenFX, provider of a platform to move money across borders, secured $94 million in Series A funding from backers including Accel, Atomico, M13, Northzone and Pantera Capital. Methodology We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of March 28-April 3. 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: Dom Guzman
This Is A Momentous Year For Early-Stage Unicorns
As global venture funding kicks off this year at record-setting levels, startup investors are also minting new early-stage unicorns at an unprecedented clip. A total of 47 seed- and early-stage companies joined the unicorn ranks in the first quarter of this year, per Crunchbase data. Barring a major slowdown, that puts 2026 on track to deliver the largest cohort of young unicorns to date. This year’s newcomers follow a good-sized 2025 cohort of early-stage companies that secured valuations of $1 billion or more as well. Per Crunchbase data, 59 hit this valuation milestone last year, up about 50% from 2024. Over the past 10-plus years, meanwhile, the number of new early-stage unicorns has fluctuated widely, from a couple dozen to more than 100, as charted below. Recent early unicorns are all about AI Virtually all of the early-stage unicorns minted in the past couple quarters are AI-focused. This includes several of the most heavily funded newcomers. Examples include Project Prometheus, the physical AI startup launched by Jeff Bezos, Thinking Machines Labs, the foundational AI company co-founded by former OpenAI CTO Mira Murati, and Nscale, a London-based AI infrastructure unicorn that has raised over $5 billion. All this represents the opposite of a surprising development, given that 80% of global venture funding this past quarter went to AI. Additionally, later-stage AI companies are famously securing unheard-of private market valuations, with OpenAI and Anthropic recently valued at $852 billion and $380 billion, respectively. While we’re not seeing those kinds of numbers for more recently minted early-stage unicorns, several are hitting post-money valuations previously unheard of for such young companies. Thinking Machines Lab, valued at $12 billion for its first funding, is reportedly looking to secure a $50 billion valuation for its next round. And 2-year-old Reflection AI, which secured an $8 billion valuation late last year, is reportedly seeking fresh funding at a $25 billion value. Fastest climbers In addition to their high valuations, many newcomers to the early-stage unicorn club are also noteworthy for the speed of their ascents. Quite a few unicorns minted in the last 15 months were founded in 2025. And one — Advanced Machine Intelligence — was apparently founded just this year. For a broader view, we used Crunchbase data to aggregate some prominent examples of recently founded early-stage unicorns. By now, some of our early-stage unicorns have also already moved on to later stage. Nscale, for instance, closed a Series C this month. And residential backup power provider Base Power closed on $1 billion in Series C funding in October, just eight months after its Series B. Others are already close to securing new funding at Series C and beyond. Was this the peak? Given the new funding records set last quarter, and the blistering pace of early-stage unicorn creation, it’s worth considering whether this could be the peak for the ultra-high AI newcomer funding rounds and valuations. After all, public markets haven’t done well in recent weeks, and private markets have a history of following suit. For those of us who’ve followed startup funding ebbs and peaks for some time, it’s clear the current environment shares characteristics of a market top. By the same token, top performing tech startups have long demonstrated that doubters are often wrong. Related reading: Illustration: Dom Guzman
Exclusive: Miravoice, Builder Of An AI ‘Interviewer’ To Conduct Phone Surveys, Raises $6.3M
Miravoice, a startup using AI voice agents to conduct long-form phone surveys, has raised $6.3 million in a seed funding round, the company tells Crunchbase News exclusively. Unusual Ventures led the financing, which included participation from Neo, 25madison and angel investors from companies such as Ramp, PubMatic, Atlassian and Google. Miravoice has developed an AI interviewer that it says can conduct phone surveys and voice interviews for “precision data collection” without human interviewers. The surveys are long-form and quantitative, with some including more than 120 questions and lasting over 40 minutes. They span open-ended responses, numerical inputs, multiple choice questions, Likert scales and matrix questions. Danny D. Leybzon, Nishant Jain and Shreyas Tirumala, co-founders of Miravoice. (Courtesy photo) “Imagine talking to 100,000 people and instantly capturing what they know,” said CEO and co-founder Nishant Jain. “We make that as simple as creating a Google Form.” Voice interviews have long been the gold standard for rigorous data collection, but the costs and operational frictions of talking to people have made it more challenging, Jain contends. “Having to hire call centers made running quantitative research surveys infeasible for most organizations,” he said. Miravoice claims its agent is designed to be simple for anyone to deploy and not require technical backgrounds to operate. A user can build a questionnaire, spin up a phone number, and launch its trained voice agent “to get results back in hours rather than weeks,” Jain said. Multiple languages and ‘messy realities’ Miravoice is hyper-focused on precision, according to Jain. “Unlike other voice agent companies, we focus on structured conversations in which most questions are known in advance,” he explained. “Our customers know what information they want to get ahead of time, which is why we focus on extracting as much information as possible from respondents while minimizing bias.” He said Miravoice’s agent will ask every question in a survey without hallucinating responses. “And when the messy realities of human conversations arise, like interruptions or pauses, our AI can handle them seamlessly,” Jain said. The Miravoice interviewer is also multilingual by design, a capability that Jain believes is difficult for individual call centers to match. Using Miravoice’s agent is also cheaper than hiring and training call centers to conduct the same surveys, Jain contends. The platform can handle both outbound and inbound calls if a respondent calls back at any time of day. Idea and business model Miravoice was founded by Jain, Danny D. Leybzon and Shreyas Tirumala, three close friends from California who have known each other for more than a decade. The idea for Miravoice came from firsthand experience with the pains of scaling quantitative survey research in their roles as product managers and consultants. They realized that voice agent technology would be the way these calls would be handled in the future, “if agents were appropriately crafted for the unique needs of this market use case.” Miravoice has between 10 and 20 customers at varying stages — from paid pilot to production use cases — according to the company. Those customers include a variety of public-opinion survey organizations, market research firms, university departments and private companies across retail, entertainment and logistics. Its revenue model is usage-based billing: Customers pay for the time its AI agents are actually on the phone with respondents. Miravoice surpassed 100,000 calls made in 2025, per the company, and expects that number to be significantly higher this year. “What’s exciting about the space we’re operating in is that the scale of the number of calls our platform has to handle dwarfs most other voice agent use cases,” Jain said. “Our pilot projects alone are on the order of tens of thousands of calls: more than some voice agent companies’ monthly production workloads. In production, some of our customers expect to perform millions to tens of millions of calls each year, after full deployment and implementation.” Voice AI on the rise Lars Albright, general partner at Unusual Ventures, said his firm was impressed by the founding team’s technical acumen and product vision. In Albright’s view, Miravoice’s focus on precision data collection sets it apart from most other entrants in the voice agent market research space. “They’ve correctly identified that voice AI can streamline operations and time-to-insight for large-scale quantitative research studies,” he wrote via email. Another area where Miravoice distinguishes itself is its ease of use, he said. “Many voice agent platforms are geared towards technical audiences and software developers,” Albright said. “Miravoice was built from the ground up with simplicity in mind so that truly any team can use it. This is a step-function change in making AI voice agents for surveys as ubiquitous as web forms are today.” Indeed, voice AI startups have emerged as standouts in the vast AI space, attracting the attention of investors globally, according to Crunchbase data. Over the past two years, several voice AI companies have seen their valuations triple — a signal of accelerating market demand and perceived long-term worth. One example of a voice AI company that has seen a massive valuation jump is ElevenLabs, which allows creators, enterprises and others to use AI software to replicate voices in dozens of languages. The Brooklyn, New York-based startup went from achieving unicorn status with an $80 million Series B raise in January 2024 to being valued at about $3.3 billion one year later with a $180 million Series C co-led by Iconiq Capital and Andreessen Horowitz. Then, in February of this year, it raised a $500 million Series D round led by Sequoia Capital at an $11 billion valuation. Related reading: Illustration: Dom Guzman
Exclusive: Anvil Robotics Raises $5.5M to Build ‘Legos for Robots’ Platform For Physical AI Teams
Anvil Robotics, an eight-month-old startup that aims to be the “Legos for robots,” has raised $5.5 million in a seed funding round, it tells Crunchbase News exclusively. Matter Venture Partners led the raise, which included participation from Humba Ventures, DNX Ventures, Superhuman founder Vivek Sodera, Spacecadet Ventures and Position Ventures. Anvil had previously raised $1 million in pre-seed capital from Matter in 2025. The San Francisco-based startup builds custom robots for businesses and describes itself as a hardware, software and manufacturing platform. Mike Xia and Vijay Pradeep, co-founders of Anvil Robotics. (Courtesy photo) Before starting Anvil Robotics last July, Mike Xia, CEO, and CTO Vijay Pradeep, spent six months talking to a variety of businesses. They concluded that physical AI teams in companies, big and small, were spending over six months piecing together various robot arms, cameras and open-source libraries “just to get a glued-together prototype.” “This isn’t a problem if you’re Tesla, or have nine-figure R&D budgets, and you custom design and build everything, including hardware and software,” Xia told Crunchbase News in an interview. “But for many companies, even well-funded teams, standing up a robotic system with all the sensors and tools and controls you need is a huge challenge that costs you both time and money.” So the pair started Anvil to fill that gap. “We support physical AI teams who don’t have $100 million, to make this industry much more accessible,” Xia said. Customers can go on Anvil’s site and “essentially build out what they want,” he added, using either prebuilt kits or customization. “They are very much like Legos,” Xia said. Anvil then ships the robots within 1 to 2 days via 2-day air freight. The company is able to do so because it has a significant presence in Taiwan, and is its own manufacturer, he said. (But more on that later.) Its robots are about the size of a middle-school-aged child, but big enough to do basic dextrous tasks. Anvil’s robots typically cost $5,000 to $10,000, but its least expensive model is just $1,900. “I think the pricing is going down to a point where researchers and individuals are able to afford this,” Xia said. “I think it’s going to make a really big difference with the community and we’ll see a lot more activity in people building physical AI applications.” Anvil started shipping robots in September and has so far delivered over 100 of them to customers globally. Open-platform approach Anvil competes with the likes of Universal Robots and Unitree Robotics but claims that it’s different from other startups in the space in a couple of ways. “Most are basically building toys for rich people,” Xia said. Anvil’s model stands out, he believes, because it’s an open platform, meaning that all of its robot designs are open-sourced. Most other startups, according to Xia, sell a proprietary design that gets customers “locked in hardware and software.” “If you work with Anvil, you’re not locked into a single vendor, plus you have large communities behind you,” he said. Also, as mentioned above, Anvil is an actual manufacturer, and it “controls the whole stack.” “We don’t outsource — we do this hard part ourselves,” he told Crunchbase News. “We buy each part and operate our own factory, which our customers can leverage.” Further, Anvil customers can choose where their components come from and how many to build. Historically, if a U.S. company has wanted to deploy a robot, it’s largely been dependent on hardware built in China. “If a business wants 10 robots made with Taiwanese or Japanese parts, we can do it,” Xia said. “I believe many companies will become more aware of supply chain risk and need this. Many robots today are made in China, and we’re not exactly on great terms [with the country]. Business growth Anvil won’t disclose hard revenue figures, but Xia noted that it has reached seven figures and that it has over 50 customers. That revenue mostly comes from hardware today, but the company plans to release more software, data tools and services, which should diversify its revenue base. Its customers are a varied bunch, with some “exciting” ones such as giant tech companies under NDA. Those they can talk about are a small chocolate factory based in Portland, Oregon; Nvidia’s GEAR lab, which is doing the humanoid research behind GR00T; and Path Robotics, which has raised more than $300 million to automate welding and industrial tasks. So far, all of its customers have been inbound, according to Xia. “It’s all been word-of-mouth, and a lot of it is community-driven,” said Xia, who added that he previously co-founded another startup called Lumina Industries and was formerly chief product officer at Voltage Park. A ‘robotics foundry’ Haomiao Huang, founding partner at Matter, told Crunchbase News via email that his firm has been investing “at the forefront” of physical AI “for some time.” “It quickly became clear that innovation on the hardware — the motors, actuators, sensors, systems, etc. — hasn’t kept pace with the rapid improvement in AI. They are still stuck in the same paradigms that powered the industrial robotics of decades past.” In his view, AI robots today are like “incredible brains trapped in weak, incapable bodies.” That’s where Anvil comes in. His firm incubated the startup to create a robotics foundry that could “move many companies forward.” “Behind great generations of products are foundational platform enablers,” Huang said, “and we founded Anvil to be to physical AI what AWS (Amazon Web Services) has been to SaaS and what TSMC (Taiwan Semiconductor Manufacturing Co.) has been to chips.” The hard part of hardware is less about creating a great robot once, and more about making many great robots “over and over again,” Huang added. Anvil’s founders, he said, will be able to produce and iterate on hardware at “software-like speeds” and then deliver it at scale in production. Added Huang: “This is something unmatched.” Overall, robotics startup funding hit a record high last year, per Crunchbase data. Startups in the sector raised nearly $14 billion in funding in 2025, up from $8.2 billion in 2024, even topping the $13.1 billion raised in the peak venture funding year of 2021. Related Crunchbase queries: Related reading: Illustration: Dom Guzman
Sector Snapshot: Venture Funding To Foundational AI Startups In Q1 Was Double All Of 2025
Funding to foundational AI startups, also known as generative AI companies or frontier labs, has doubled in the first quarter of 2026 so far compared to all of 2025, Crunchbase data shows. That funding is increasingly concentrated in a handful of foundational giants, including OpenAI, Anthropic and xAI. In 2025 and early 2026, the market saw a shift to a small number of companies capturing a disproportionate share of global capital. The broad trend: After three years of declining or flat venture investment, global startup overall funding grew year over year in 2025, Crunchbase data shows. Notably, year-over-year funding growth concentrated in the largest rounds and in the AI sector. Roughly 50% of all global venture funding in 2025 went to companies in AI-related fields, making artificial intelligence the leading sector for funding, as it was for the past three years. Venture funding to AI overall reached $211 billion — up 85% year over year from $114 billion in 2024 — Crunchbase data shows. Funding to the AI sector in 2025 surpassed every year in the past decade, including the peak global funding year of 2021. The numbers: As of March 31, foundational AI startups had raised $178 billion across 24 deals, compared with $88.9 billion across 66 deals in all of 2025 in a 100% increase. That’s also significantly higher — 466.9% higher to be exact — than the $31.4 billion raised across 52 deals in 2024. By contrast, funding to foundational AI companies totaled just $23.2 billion in 2023 (a fraction of the size of OpenAI’s latest round) and a mere $1.4 billion in 2022. Noteworthy rounds Unsurprisingly, the two largest rounds in 2026 so far were raised by rivals OpenAI (maker of ChatGPT) and Anthropic (maker of Claude). Last month, OpenAI revealed that it’s raising an additional $10 billion in funding for its record-setting $110 billion megaround announced in February, bringing the total fundraise for the San Francisco-based company to over $120 billion. On March 31, it was reported that the round actually reached $122 billion. Backers in the latest financing include Andreessen Horowitz, D.E. Shaw, MGX, TPG and T. Rowe Price. The first tranche of that round had already marked the largest venture funding deal of 2026 so far and the largest of all time, per Crunchbase data. Also in February, generative AI company Anthropic announced it had raised $30 billion in a massive Series G funding round led by GIC and Coatue, valuing it at $380 billion post-money. With that round, San Francisco-based Anthropic has now raised nearly $64 billion since its 2021 inception, per Crunchbase. The year kicked off with Elon Musk’s xAI, the generative AI startup known for its Grok chatbot and the parent company of X (formerly Twitter), securing $20 billion in Series E funding from a long list of venture and strategic investors. Founded in 2023, xAI has raised $42.7 billion in reported debt and equity funding to date, per Crunchbase data. Beyond the three largest generative AI giants, a smaller cohort of foundational AI startups are also raising significant sums of money. Advanced Machine Intelligence, a startup co-founded by computer science pioneer and former Meta AI chief Yann LeCun, in March raised $1.03 billion to develop “world models,” or AI designed to learn from and interact with the physical world. The funding for Paris-based AMI represented the largest seed round ever for a European startup and one of the region’s largest fundings for an AI startup overall, per Crunchbase data. Bezos Expeditions, Cathay Innovation, Greycroft, Hiro Capital and HV Capital led the funding, which reportedly values AMI at $3.5 billion. After that, the next-largest raise so far is a $1 billion injection into World Labs, a San Francisco-based startup founded by AI pioneer Fei-Fei Li that develops foundational models to generate and interact with the 3D world. Investors in that round included AMD, Autodesk, Emerson Collective, Fidelity, Nvidia and Sea. Exits and IPOs The foundational AI sector is too young to have seen any significant exits yet. However, OpenAI in particular has done quite a bit of acquiring. OpenAI has already made six acquisitions in 2026, nearly as many as it made in all of 2025, according to Crunchbase data. Its latest purchase took place on March 19, when it announced plans to acquire Astral, a creator of open-source tools for software developers. This month, it also snapped up Promptfoo, an open-source tool for testing AI applications. Overall, the San Francisco-based company has acquired 17 companies in the past three years, Crunchbase data shows. Eight of those purchases were made in 2025, although it didn’t even start making acquisitions until April last year. Meanwhile, data shows that Anthropic has been far less acquisitive. So far this year, it has made only one known purchase, buying Vercept, a 2-year-old software development startup. In 2025, Anthropic made two known acquisitions: Humanloop, an LLM evaluation platform for enterprises, and Bun, a JavaScript runtime for developing and managing web applications. No foundational AI model company is currently public, though several are actively preparing to change that in late 2026 or sometime in 2027. The most likely candidates are the companies that have also raised the most capital: OpenAI and Anthropic. Toronto-based Cohere, founded by ex-Google researchers, is also another possibility. That startup last August raised $500 million at a $6.8 billion valuation. Inovia Capital and Radical Ventures co-led the round, which included participation from AMD Ventures, Nvidia, PSP Investments, Salesforce Ventures 1 and others. The case of xAI is an interesting one. In early 2026, the company effectively merged its interests with SpaceX. As a result, the highly anticipated SpaceX IPO, expected in mid- to late-2026, will now be the primary vehicle for public investors to gain exposure to xAI’s foundational models. Related Crunchbase query: Related reading: Illustration: Dom Guzman