Ordinary Chaos

Tag: funding

  • Investments in generative AI startups topped $3.9B in Q3 2024

    Investments in generative AI startups topped $3.9B in Q3 2024

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    Not everyone is convinced of generative AI’s return on investment. But many investors are, judging by the latest figures from funding tracker PitchBook.

    In Q3 2024, VCs invested $3.9 billion in generative AI startups across 206 deals, per PitchBook. (That’s not counting OpenAI‘s $6.6 billion round.) And $2.9 billion of that funding went to U.S.-based companies across 127 deals.

    Some of the biggest winners in Q3 were coding assistant Magic ($320 million in August), enterprise search provider Glean ($260 million in September), and business analytics firm Hebbia ($130 million in July). China’s Moonshot AI raised $300 million in August, and Sakana AI, a Japanese startup focused on scientific discovery, closed a $214 million tranche last month.

    Generative AI, a broad cross-section of technologies that includes text and image generators, coding assistants, cybersecurity automation tools, and more, has its detractors. Experts question the tech’s reliability, and — in the case of generative AI models trained on copyrighted data without permission — its legality.

    But VCs are effectively placing bets that generative AI will gain a foothold in large and profitable industries and that its long-tail growth won’t be impacted by the challenges it faces today.

    Perhaps they’re right. A Forrester report predicts 60% of generative AI skeptics will embrace the tech — knowingly or not — for tasks from summarization to creative problem solving. That’s quite a bit rosier than Gartner’s prediction earlier in the year that 30% of generative AI projects will be abandoned after proof-of-concept by 2026.

    “Large customers are rolling out production systems that take advantage of startup tooling and open source models,” Brendan Burke, senior analyst of emerging tech at PitchBook, told TechCrunch in an interview. “The latest wave of models shows that new generations of models are possible and may excel in scientific fields, data retrieval, and code execution.”

    One formidable hurdle to widespread generative AI adoption is the technology’s massive computational requirements. Bain analysts project in a recent study that generative AI will drive companies to build gigawatt-scale data centers — data centers that consume 5 to 20 times the amount of power the average data center consumes today — stressing an already-strained labor and electricity supply chain.

    Already, generative AI-driven demand for data center power is prolonging the life of coal-fired plants. Morgan Stanley estimates that, if this trend holds, global greenhouse emissions between now and 2030 could be three times higher versus if generative AI hadn’t been developed.

    Several of the world’s largest data center operators, including Microsoft, Amazon, Google, and Oracle, have announced investments in nuclear to offset their increasing nonrenewable energy draws. (In September, Microsoft said that it would tap power from the infamous Three Mile Island nuclear plant.) But it could take years before those investments bear fruit.

    Investments in generative AI startups show no sign of decelerating — negative externalities be damned. ElevenLabs, the viral voice cloning tool, is reportedly seeking to raise funds at a $3 billion valuation, while Black Forest Labs, the company behind X’s notorious image generator, is said to be in talks for a $100 million funding round.

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  • Support automation firm Capacity grows with new cash and acquisitions

    Support automation firm Capacity grows with new cash and acquisitions

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    David Karandish has been busy.

    Capacity, his support automation company, was planning a $5 million “bridge round” to help the company reach the break-even point. But TVC Capital, Toloka.vc, and the venture’s other backers had something grander in mind. So they threw in an additional $21 million for what became Capacity’s $26 million Series D.

    While all this was happening, Capacity acquired three companies: enterprise search firm Lucy (which had raised $5.6 million) and two startups focused on customer service automation, Linc and Envision.

    “It’s an exciting time of transformation at Capacity as we grow to help brands do more to automate interactions with customers and team members,” Karandish told TechCrunch. “We’re at an inflection point for AI and many businesses are realizing that they need a complete platform to be successful, rather than cobbling together a bunch of point solutions.”

    Karandish co-founded Capacity with Chris Sims in 2017 as a part of Equity.com’s incubator program. After the $900 million exit of Answers.com (which Karandish also co-founded), Karandish says he wanted to start a business to address what he perceived as major blockers in customer service operations.

    “Rising costs have placed pressure on support teams to do more with less,” Karandish said. “At the same time, consumer expectations are shifting rapidly where consumers both want self-service but are increasingly frustrated by lackluster experiences. Our goal with Capacity is to provide a great customer experience while also recognizing that escalating to a human is the right thing to do in many cases.”

    Capacity connects to a company’s tech stack to answer queries and automate support tasks. The platform mines information from files, apps like Gmail, customer relationship management software, and more to build a knowledge base that Capacity’s chatbot and helpdesk tools can pull from.

    Employees can ask Capacity’s chatbot questions like “What was added to the merger contract yesterday?,” or even instruct it to do things like updating the status of a sales lead. The chatbot and helpdesk can also deliver company-wide announcements, like news and event notifications. And they can be made external-facing (with filters to hide sensitive data, mind you), embedded on a company’s website to answer common customer questions.

    Capacity
    Image Credits:Capacity

    “We view Capacity as having the ease-of-use of a tool like Zendesk with the automation chops of a ServiceNow,” Karandish said. “From an approach standpoint, we are executing a very similar playbook to Parker Conrad’s ‘compound model’ — except in our case, we’re focused on support.”

    Innovations in self-service software — including AI — are making them a more attractive solution to companies than they have been in the past. For example, Cleverly.ai — which Zendesk acquired in August 2022 — finds answers to customers’ questions by creating a knowledge layer on top of applications. Meanwhile, Directly taps algorithms trained by subject-matter experts to strategically answer customer issues in a variety of different messaging channels.

    Customers like self-service options. According to a Zendesk poll, 67% prefer them over interacting with customer support. But it can be difficult to get them right. A Gartner survey found that, on average, only 14% of customer service and support issues are fully resolved in self-service.

    Capacity will upgrade and expand its product portfolio through its recent acquisitions.

    Karandish sees Lucy’s offering, which ingests and analyzes data from enterprise apps and systems, augmenting Capacity’s existing indexing technology. Envision, meanwhile, will help Capacity customers flag unresolved chats and calls and train human agents. And Linc will bring self-service tools for retail and e-commerce to Capacity, said Karandish.

    The plan is for Lucy’s co-founders, Dan Mallin, Scott Litman, and Marc Dispensa, to join Capacity to help lead products and teams integration. Envision CEO Rodney Kuhn will oversee contact center solutions at Capacity, and Linc founder and CEO Fang Cheng will lead Capacity’s e-commerce efforts.

    To date, Capacity has acquired eight companies — the other five being Textel, LumenVox, Denim Social, SmartAction, and Cereproc — and raised more than $89 million.

    Karandish said that the newest tranche will be put toward growing Capacity’s headcount to 200 people by the end of the year as the Saint Louis-based company “heads toward profitability.” Capacity’s customer base now stands at over 2,500 brands, he added, while its annual recurring revenue is nearly $50 million.

    “Our growth strategy reflects what our customers are asking for: an all-in-one AI platform that delivers across all communication channels,” he added. “We’ve identified 24 steps of the customer experience that are ripe for support automation … Each acquisition adds specific tech and talent to help Capacity become a leading provider of AI-powered solutions for customer and employee experience.”

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  • Xscape is building multicolor lasers to connect chips within datacenters

    Xscape is building multicolor lasers to connect chips within datacenters

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    The GPUs and other chips used to train AI communicate with each other inside datacenters through “interconnects.” But those interconnects have limited bandwidth, which limits AI training performance. A 2022 survey found that AI developers typically struggle to use more than 25% of a GPU’s capacity.

    One solution could be new interconnects with much higher bandwidth, according to Vivek Raghunathan, the CEO and co-founder of startup Xscape Photonics. The secret sauce, he says, is silicon photonics: silicon-based material that manipulates light to transmit data.

    “Xscape has created a platform that connects various computing elements in a sustainable way, while offering the highest possible performance,” Raghunathan told TechCrunch in an interview. “The core of this platform’s scaling relies on energy-efficient, cost-effective systems that do not exist in the industry yet.”

    Xscape is based in Santa Clara in the heart of Silicon Valley, but has its roots in a Columbia University lab, where three professors — Alexander Gaeta, Keren Bergman, and Michal Lipson — invented a technique they believed could be used to transmit terabytes of data over light.

    The trio spun off Xscape in 2022 after recruiting Raghunathan and Yoshitomo Okawachi, a laser engineer and a longtime colleague of Gaeta’s. Raghunathan joined by way of Broadcom, where he helped found the silicon photonics team, and Intel, where he was manager for the company’s silicon photonics products.

    Traditional interconnects consist of metal wires that transmit data in the form of electrical signals.

    Metal-based interconnects require a lot of power — and generate lots of heat. They’re bandwidth-constrained by their medium’s conductivity. And, in datacenters with fiber-optic links between components, the interconnects’ electrical data must be converted into optical and back again, introducing latency.

    Silicon photonics like Xscape’s, in contrast, draw minimal power and produce negligible heat.

    “In the past, we primarily used optical communications for long-haul fiber-optic systems,” Raghunathan said. “But recent advancements are enabling the integration of optics-on-chip — in the form of silicon photonics — and bringing the optical interface from the electronic plane to the optical plane all the way into the chip.”

    Xscape’s first product is a programmable laser to power datacenter fiber-optic interconnects, specifically the links among GPUs, AI chips, and memory hardware. The laser can leverage different colors of light (i.e. wavelengths) to transmit multiple data streams along the same link without interference, Raghunathan claims.

    “Electrical systems densely packed together tend to produce crosstalk, interference, and other challenges,” he said. “However, within the optical domain, data can be modulated on different colors, wavelengths, or channels, and all co-propagate within the same wire or fiber — and not interfere with each other.”

    Assuming the tech works as advertised, Xscape faces the same challenge as most hardware startups: manufacturing and selling its products at scale. In a possible leg up over photonics rivals like Ayar Labs and Celestial AI, Xscape’s lasers can be fabricated using the same facilities used to make the microelectronics in phones and laptops.

    The first-generation laser can only emit between 4 and 16 colors. However, Xscape is already planning improved versions that’ll be able to emit up to 128.

    Xscape says that it’s “actively engaged” with ten customers for potential deployments, ranging from vendors to hyperscalers — and that it has secured funding from Cisco and Nvidia, whose venture arms invested in its recent $44 million Series A round. The investments aren’t strategic, meaning that the companies aren’t currently customers. But Raghunathan notes that Cisco is one of the largest sellers of optical networking components in the world.

    “This reflects Cisco and Nvidia’s trust in the value we bring to this ecosystem,” Raghunathan said.

    The latest funding round was led by IAG Capital Partners, and brought the company’s total raised to $57 million. Raghunathan says that the proceeds will be put toward growing Xscape’s 24-person team, and scaling up fabrication of its lasers and related photonics tech.

    “The funding will allow Xscape to push the boundaries of our platform and integrate it with simulation, high-performance compute, and AI software to help customers in all industries take their innovations to new heights,” Raghunathan said.

    Xscape certainly has its work cut out for it. Aside from Ayar and Celestial, the firm competes with Intel in the multi-billion-dollar silicon photonics market. Intel claims to have shipped over 8 billion photonics chips and 3.2 million on-chip lasers since 2016.

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  • India’s Physics Wallah raises $210M at $2.8B valuation even as edtech funding remains scarce

    India’s Physics Wallah raises $210M at $2.8B valuation even as edtech funding remains scarce

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    Physics Wallah, an Indian edtech startup, has secured $210 million in fresh financing amid a tough funding environment for edtech companies in the country following the collapse of Byju’s, once the biggest company in the space.

    Physics Wallah said on Friday the Series B round was led by Hornbill Capital, with Lightspeed Ventures Partners “significantly” participating, alongside existing backers WestBridge and GSV. The round values Physics Wallah at $2.8 billion, a substantial increase from the previous $1.1 billion valuation it scored in June 2022. The startup has raised $310 million to date.

    The startup began its journey as a YouTube channel in 2016, where co-founder and teacher Alakh Pandey posted his lectures for free to help students who — like he had — lacked the financial means to enroll in premium coaching classes. By 2020, Physics Wallah had grown to become the largest Indian education community on YouTube, prompting Pandey to formalize his efforts into a company that now serves 46 million students in five vernacular languages.

    “He always felt that he couldn’t crack the IIT entrance exam because he didn’t have access to quality education,” said Prateek Maheshwari, co-founder of Physics Wallah, explaining the motivation behind the startup’s mission.

    India, the world’s most populous nation, boasts one of the largest education markets globally, with approximately 250 million students attending school and about 4 million giving entrance exams for engineering colleges and medical schools every year.

    Physics Wallah caters to a broad spectrum of this market, serving students from third grade through those preparing for competitive engineering and medical entrance exams and government positions. It even offers live classes that typically draw tens of thousands of simultaneous attendees.

    The startup employs teaching assistants and AI to address student queries, and has developed an app called AI Guru that helps students solve problems in their learning material. Maheshwari noted that Physics Wallah has trained the AI on its own data.

    One of Physics Wallah’s key strengths is the affordability of its courses, with prices starting as low as $50 for an entire year. More than 5.5 million students are paying subscribers, the startup said.

    “We are covering nearly all exams in India, and for all the special ones – JEE, NEET, GATE, UPSC, and CAT — we are No. 1 in terms of revenue and the size of the student base served,” Maheshwari said.

    That traction is serving Physics Wallah well: It reported revenue of $96.2 million in the year ended March 2023, and the startup told TechCrunch revenue increased 2.5x between March last year and March 2024. It expects its fiscal year ending March 2025 to be its most profitable yet in EBITDA terms.

    Dev Khare, a partner at Lightspeed and one of the earliest investors in Indian edtech startups, told TechCrunch that many trends have converged to help Physics Wallah grow. “When you bring the price point down, it just makes things way more accessible,” he said, pointing to budget-hotel chain Oyo, quick-commerce startup Zepto, and storytelling platform PocketFM as other examples of Lightspeed’s portfolio startups that run similar playbooks.

    Maheshwari said Physics Wallah will explore inorganic growth opportunities with the fresh funds, but added that the company largely raised the capital because the funding was available and the investors saw value in doing so. The company is thinking about an IPO, but he cautioned that it would not make any immediate moves soon.

    The new funding arrives as India’s edtech sector faces significant headwinds. Online learning startups, which saw rapid growth during the COVID-19 pandemic when schools were closed, have seen a sharp decline in usage since.

    Unacademy, a major edtech company based in Bengaluru, has cut approximately 2,000 jobs since 2022. The company cut another 250 positions in July this year, citing the need to restructure for profitability.

    Byju’s, formerly India’s most valuable startup at $22 billion, has suffered a dramatic downturn over the past two years. The company now faces the prospect of bankruptcy proceedings.

    Maheshwari said recent industry events haven’t affected the market opportunity. “From a student’s lens, things haven’t changed much post-COVID. The market is entirely hybrid and students are enjoying the best of both worlds to strengthen their preparation,” he said.

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  • Fal.ai, which hosts media-generating AI models, raises $23M from a16z and others

    Fal.ai, which hosts media-generating AI models, raises $23M from a16z and others

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    Fal.ai, a dev-focused platform for AI-generated audio, video, and images, today revealed that it’s raised $23 million in funding from investors including Andreessen Horowitz (a16z), Black Forest Labs co-founder Robin Rombach, and Perplexity CEO Aravind Srinivas.

    It’s a two-round deal: $14 million of Fal’s total came from a Series A tranche led by Kindred Ventures; the remaining $9 million is from a previously unannounced, a16z-led seed round.

    Burkay Gur and Gorkem Yurtseven co-launched Fal (short for “Features and labels”) in 2021. Yurtseven previously worked at Amazon as a software dev, while Gur, an ex-Oracle engineer, led machine learning development at Coinbase for several years.

    While hacking together side projects during the pandemic, Gur and Yurtseven, longtime friends, realized the growing demand for AI cloud infrastructure — particularly infrastructure to run generative AI models.

    “The big bet was that the nascent space of generative media was about to change all media consumed,” Gur told TechCrunch. “The timing worked out perfectly, because there were some breakthrough models that were released right after Fal started.”

    Fal offers two products: privately managed compute and workflows for running models, and APIs for open source models that generate images, audio, and video. Fal was one of the first platforms to host Black Forest Labs’ Flux, the model powering image generation in Grok, X’s controversial chatbot.

    Many cloud rivals like CoreWeave provide resources along these same lines. But what makes Fal different is its scalability, Gur argues.

    “Our platform can handle hundreds of millions of requests [and our] own inference engine is the most performant,” he said. “Using Fal, you can integrate models into your applications — the product is for enterprises that have media at the core of what they do.”

    Whether those claims hold up to scrutiny or not, Fal has managed to grow an impressive customer roster. In addition to Perplexity (which explains Srinivas’ investment) and enterprise customers in the retail and e-commerce sector, popular generative AI apps Photoroom, Freepik, and PlayHT are all paying for Fal’s services, Gur says.

    Fal.ai
    Models in Fal.ai’s model gallery.
    Image Credits: Fal

    It’s a profitable bunch. A source tells TechCrunch that Fal’s annual run rate has climbed to nearly $10 million (~$800,000 per month), up around 10x from January. The Series A valued the startup at $80 million.

    “Fal has reached 500,000 developers on the platform,” Gur said, “generating 50 million images, videos, or audio streams a day.”

    Given the many deepfake and misinformation risks around generative technologies, I asked Gur if Fal has moderation policies or filters in place for sensitive content. He said that Fal prefers to take a hands-off approach, leaving the decision whether to implement safety features up to the companies developing models on Fal’s platform.

    “For moderation, a lot of what is done happens during training, so we leave that to the companies building the models,” Gur said. “As you might guess, having a very robust program requires more research and resources.”

    It’s a bit of an empty answer, given that Fal sponsors some open source training efforts under its research grants program. One would assume that Fal has a say in the development of models it funds.

    Gur did suggest, however, that Fal is looking to undertake some de-toxifying efforts itself… at some point. “We do have plans to do more of this in-house, and rely on some vendors specialized in this type of work,” he said.

    I asked about IP liability, as well. Should the models on Fal’s platform regurgitate any copyrighted data, will the company protect customers if they’re sued? Gur wouldn’t answer. But the language in Fal’s terms of service imply that customers are on their own.

    That’s in contrast to generative AI products from Adobe, Canva, Google, Microsoft, and Shutterstock, all of which have indemnity clauses (albeit with some carve-outs). Vendors like Getty Images, as well as startups such as Fairly Trained, have gone so far as to train models only on “commercially safe” content to avoid the threat of copyright lawsuits altogether.

    That’s all to say, those who use Fal assume some risk.

    Fal intends to spend the bulk of the capital it’s raised so far on upgrading its inference optimization product to make it self-serve. The company is also establishing a research team that’ll focus on model optimizations and will join Fal’s 17-person staff.

    Fal’s other backers include Vercel founder Guillermo Rauch, entrepreneur and investor Balaji Srinivasan, and Hugging Face CTO Julien Chaumond.

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  • Greenlite, founded by an ex-Gopuff exec, automates construction permitting

    Greenlite, founded by an ex-Gopuff exec, automates construction permitting

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    Construction permitting often involves drafting lengthy applications, leading to unpredictable timelines for developers and businesses. There are tens of thousands of jurisdictions — each with their own different forms and application processes for building permits.

    Ben Allen knows a thing or two about permitting. While leading business expansion and strategy at Gopuff, Allen was charged with spinning up Gopuff Kitchens, Gopuff’s attempt at ghost kitchens, in hundreds of locations throughout the U.S.

    The biggest obstacle his team faced was obtaining the necessary building permits, Allen said.

    “The permitting process for developers, builders and governments is largely antiquated and manual,” he told TechCrunch. “For example, some governing bodies only accept or review permit plans on a specific day of the week during specific hours. Without adopting a solution to streamline this process, many cities would be stuck in a time-consuming and costly cycle for current permit processes.”

    After leaving Gopuff, Allen was inspired to try his hand at a solution to the conundrum with James Gallagher, a former colleague at Gopuff. Two years ago, the two launched Greenlite, a platform that attempts to standardize the permitting process for customers across multiple jurisdictions.

    Using the platform, Greenlite’s customers — which today range from retailers and quick service restaurants to developers and production home builders — can conduct construction plan reviews almost entirely via software. Rival firms like PermitFlow, Accela and Tyler Technologies also offer this capability, but Gallagher argues that they’re more “application submission-oriented” and simplistic.

    Greenlite
    Greenlite’s customer dashboard.
    Image Credits: Greenlite

    “Greenlite provides a digital plan review solution that actually delivers permits faster and more transparently,” Gallagher, Greenlite’s CEO, asserted — adding that Greenlite is also authorized to review construction plans and perform building inspections in around 2,000 jurisdictions.

    Some localities and municipalities, like Miami, allow contractors to hire their own private providers (e.g. Greenlite) in lieu of having jurisdiction plan review and inspections. “Greenlite’s platform is unique because it integrates construction drawings, zoning and use data, local building code and expert compliance markup all in one database,” Gallagher added.

    Gallagher wouldn’t share revenue. But he claimed that Greenlite has “dozens” of clients and is in a “position of strength to continue to grow.”

    “Our customers have a perpetual need for building permits, and Greenlite is in a position to continue to serve our customers even if they adjust priorities through potential headwinds,” Gallagher said. “Specifically, our customers need building permits to support new unit expansion and also need building permits to renovate, remodel and refresh existing assets.”

    It helps that VCs are injecting fresh capital into the operation.

    Greenlite this week closed a $28.5 million Series A round led by Craft Ventures with participation from 53 Stations, Trust Ventures and LiveOak Ventures. Bringing the company’s total raised to $36.5 million, Gallagher said that the new money will drive Greenlite’s market expansion and customer acquisition in segments like lodging, industrial and green infrastructure.

    Based in New York, Greenlite has 30 employees. Gallagher expects to hire ten more by the end of the year.

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  • DryMerge promises to connect apps that normally don’t talk to each other — and when it works, it’s great

    DryMerge promises to connect apps that normally don’t talk to each other — and when it works, it’s great

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    Platforms to connect apps that wouldn’t normally talk to each other have been around for a minute (see: Zapier). But they have not gotten dramatically simpler to use if you’re nontechnical. Generative AI has lowered the barrier to entry somewhat. However, getting the most out of these platforms — and fixing things when they break — still requires a bit of programming know-how.

    Software developers Sam Brashears and Edward Frazer perceived this to be the case as well. During internships at tech giants like Meta and Stripe, they struggled to get automations working using some of the more popular app-linking tools.

    “I’d been dealing with the pain of designing integrations and automations from scratch,” Frazer told TechCrunch in an interview. “And Sam believed that generative AI models would solve the biggest problem in integrations — transforming data between APIs.”

    So Brashears and Frazer, longtime friends who’d been building software together since elementary school, decided to try their hands at a streamlined, easy-to-use app-to-app integration platform.

    DryMerge is the fruit of their work. A chatbot for building workflows, DryMerge lets you describe an automation you want between apps — for instance, “Whenever I get an email from a new prospect, ping the team on Slack and add them to HubSpot” — and handles the necessary technical scaffolding.

    “Currently, IT departments use complicated no-code tools to automate workflows on behalf of non-IT teams,” Frazer said. “A natural language interface opens up automation to nontechnical people.”

    It sounded like a neat idea, a chatbot that can string apps together for you — particularly if you, like me, have spent countless hours wrestling with IFTTT. So, I decided to give DryMerge a go, hoping to replace my old and rickety automations once and for all.

    DryMerge’s UI is quite clean and minimalist. It reminds me a bit of ChatGPT; there’s not much to look at besides a text bot. Each new request (e.g., “Text me a summary of my calendar meetings every morning”) starts a new chat session, and these sessions can be revisited at any time from a list on the left-side panel.

    DryMerge
    DryMerge’s automations management screen.
    Image Credits: DryMerge

    DryMerge hooks into an expanding library of apps, including Gmail, Microsoft Outlook, Salesforce, storage services like Dropbox and OneDrive, social media platforms (e.g., X), and messaging clients (e.g., Discord). Once the platform creates an automation with these, it plops that automation into a dedicated window showing when the automation last run and whether DryMerge encountered any errors.

    I tried setting up a few automations I thought might be useful for a reporter with an overfull schedule, like one to throw Gmail contacts into a spreadsheet and add dates from recent email invitations to a Google Calendar. Things started out promising — DryMerge had me log into the relevant apps and asked whether I’d like to test the automations to ensure everything was working properly.

    But then, problems started to crop up.

    Several times, DryMerge’s chatbot stopped responding altogether. Other times, it missed key details in a request. I tried repeatedly to get DryMerge to understand that I wanted to copy Gmail contacts to my Google Calendar, but every attempt, it thought I wanted to manually enter contacts into a spreadsheet.

    The setbacks didn’t completely ruin my DryMerge experience. Giving credit where it’s due, the platform’s nifty when it works. For example, I successfully got DryMerge to set up an automation that copies posts from my X account to the personal Discord server I use to aggregate various notifications. A niche use case? Perhaps. But it’s going to save this reporter a lot of task switching.

    DryMerge
    Chatting with DryMerge’s bot.
    Image Credits: DryMerge

    The bugs, Frazer assures me, will be addressed in time. He and Brashears are DryMerge’s only employees, so there’s lots on the to-do list.

    “We think we’re well-positioned to iterate quickly and nimbly,” Frazer said.

    Assuming Frazer and Brashears can get DryMerge’s platform in good working condition, the bigger challenge the duo will have to face is staying relevant in the fiercely competitive integration-platform-as-a-service (iPaaS) space. According to recent poll released by IDG and TeamDynamix, iPaaS is one of the fastest-growing software markets, projected to reach $2.7 billion this year.

    AWS has its own iPaaS called AppFabric. IBM recently acquired iPaaS tech from Software AG. A growing number of startups aside from DryMerge are attempting to break into the segment, while incumbents like Zapier and IFTTT are aggressively deploying generative AI capabilities.

    Frazer makes the case that DryMerge’s differentiator is — and will remain — “being 10x easier to use” than drag-and-drop integration builders.

    “Our users include online fashion retailers, school administrators, and asset managers — the vast majority of which have never touched a line of code,” he said. “They use us to save hours a day on tasks ranging from customer support automation to customer relationship management data entry.”

    Frazer’s not wrong about the opportunity. Per the IDG and TeamDynamix poll, 66% percent of companies said that they’ll invest in iPaaS to address internal automation and data integration challenges.

    “We think a gigantic enterprise opportunity is in increasing the simplicity of automation and delivering easy-to-use tooling that empowers nontechnical folks,” Frazer said.

    It’s very early days for DryMerge, which only has around 2,000 users at present. But the company was accepted into Y Combinator’s Winter 2024 batch, and DryMerge this past summer closed a $2.2 million seed round led by Garage Capital with participation from Goodwater Capital, Ritual Capital, and angels whose names Frazer wouldn’t reveal.

    Frazer says that the funds are being put toward adding new app integrations and doubling the size of DryMerge’s team in the next few months.

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  • LineLeap lets users pay to skip the line at bars

    LineLeap lets users pay to skip the line at bars

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    No one likes standing in line. I was reminded of just how awful the experience can be last Saturday, while being herded like cattle through a two-hour queue for a nightclub in unseasonably cold weather.

    I’d not soon repeat the experience. Fortunately, there’s a startup for that.

    LineLeap, backed by Y Combinator, lets people pay to skip lines at bars. Using the startup’s mobile apps, users can shell out for front-of-the-line passes to venues that LineLeap’s partnered with.

    “As college students, we noticed a common problem that many people before us have endured,” Max Schauff, LineLeap’s co-founder and CEO, told TechCrunch. “Our favorite college bars had really long lines. The issue was that bars didn’t have an open and transparent way of allowing customers to skip the line on their most special nights. And they were leaving a lot of revenue on the table because of it.”

    Love the concept or hate it, VCs seem to like where LineLeap’s taking it. Y Combinator last month led a $10 million round in the company with participation from The Chainsmokers’ Alex Pall and others. The round, which brought LineLeap’s total raised to $25 million, valued the startup at an eye-popping $100 million.

    Driving from college town to college town

    Schauff met LineLeap’s second co-founder, Patrick Skelly, while working at EnvoyNow, an on-demand food delivery startup aimed at the college crowd. Through mutual friends, Schauff and Skelly met Nick Becker, who became LineLeap’s third co-founder.

    While still undergrads — Schauff at the University of Wisconsin-Madison and Becker and Skelly at the University of Michigan — the trio began hashing out LineLeap’s business plan and building the website together.

    “We launched on a negative-five-degree February night in Madison, Wisconsin,” Schauff said. “After night one resulting in success, we used that excitement and spent the next few years, mostly during our summer breaks, loading into the car and driving college town to college town, trying to expand.”

    LineLeap wasn’t the only line-skipping app out there at the time — and the trio knew it. So, to set their platform apart, the three co-founders decided to go after college bars as their first big customer segment.

    LineLeap
    Image Credits: LineLeap

    The co-founders slept in beat-up motels — and their cars — traveling the country to sell to venues, sneaking into YMCAs for quick showers when they could. After a few years of grinding, the trio felt they’d proven out the business model and applied to Y Combinator.

    They got accepted into the summer 2019 cohort.

    Flash forward to 2024. LineLeap survived the COVID slump, and now has an office in NYC and a team of 40 people (not counting its part-time ambassadors). The app has 1 million users and over 400 college bar partners, and is on track to process over $30 million in payments this year.

    “One of our biggest challenges — getting in front of venue owners and getting them signed on — has also proven to be one of our largest differentiators,” Schauff said. “It’s hard to sign these venues, and we’ve cracked the code through relationships in the industry and a proven track record over the last seven years.”

    Inequity and privacy concerns

    Today, LineLeap offers quite a bit more than line-skipping passes. Using Venmo, PayPal, Apple Pay or an attached credit card, users can buy concert tickets, pay cover, pre-order drinks and reserve VIP table/bottle service. They also get notified — via push notifications and email — of special events and promos, while venue owners get access to dashboards showing transaction reports and analytics.

    Events run the gamut from DJ nights to football watch parties to stand-up comedy.

    LineLeap
    Image Credits: LineLeap

    LineLeap makes money by charging Ticketmaster-style convenience fees for certain passes. The company also imposes fees for “newfound revenue” on venues — i.e. revenue that the venues weren’t generating beforehand, such as sales of skip-the-line passes.

    “Venues generate a significant new revenue stream, while also gaining the ability to communicate and market directly to their top customers via the LineLeap platform,” Schauff said. “For venues, LineLeap has no costs and is entirely risk free, so they can partner and launch with us on a moment’s notice with no downside.”

    I’m not sure I’d agree that there’s no downside.

    LineLeap is yet another example of tech that’s letting the wealthy avoid waiting. CNN’s Nathaniel Meyersohn called it a “booming industry of advantages” — advantages that come at the cost of a worse experience for less fortunate patrons, and that raise concerns about service quality and fairness for those who aren’t willing to spend top dollar.

    That could backfire for some venues. As one reviewer writes of LineLeap’s app on the Google Play Store: “Yeah, if a bar ever makes you pay to make a reservation… find a new bar.”

    Schauff tried to assure me that there’s nothing to worry about.

    “In this industry, there’s been a new wave of operators and an overall change in mindset to adopt technology and data solutions, which LineLeap has been at the forefront of,” he said. “Venue operators are now craving more data-backed solutions for marketing purposes and better technology that can help them increase their bottom line.”

    That seems like a potential privacy issue, too.

    I asked Schauff about LineLeap’s data retention policy, including how long the company stores user data and whether users can delete their data at any time. He declined to answer in detail, instead referring me to the terms of use on the LineLeap website.

    The terms, concerningly, don’t give a firm data retention time frame, and say that LineLeap may be “unable to fully delete or de-identify” user data due to “technical” or “other operational reasons.”

    For now, Schauff says that the cash is being put toward expanding LineLeap to more venues in the nightlife and entertainment industry, introducing new in-app features and building a full-blown customer relationship management platform for bars.

    LineLeap
    Image Credits: LineLeap

    “Plenty of others have tried to start line-skipping companies for bars and clubs, but none have successfully expanded into multiple markets and lasted more than a couple of years,” Schauff said. “We pride ourselves in being the company that will be our venues’ partner for years to come.”

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  • Generative AI coding startup Magic lands $320M investment from Eric Schmidt, Atlassian and others

    Generative AI coding startup Magic lands $320M investment from Eric Schmidt, Atlassian and others

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    Magic, an AI startup creating models to generate code and automate a range of software development tasks, has raised a large tranche of cash from investors, including ex-Google CEO Eric Schmidt.

    In a blog post on Thursday, Magic said that it closed a $320 million fundraising round with contributions from Schmidt, as well as Alphabet’s CapitalG, Atlassian, Elad Gil, Jane Street, Nat Friedman and Daniel Gross, Sequoia and others. The funding brings the company’s total raised to nearly half a billion dollars ($465 million), catapulting it into a cohort of better-funded AI coding startups whose members include Codeium, Cognition, Poolside, Anysphere and Augment. (Interestingly, Schmidt is backing Augment, too.)

    In July, Reuters reported that Magic was seeking to raise over $200 million at a $1.5 billion valuation. Evidently, the round came in above expectations, although the startup’s current valuation couldn’t be ascertained; Magic was valued at $500 million in February.

    Magic also on Thursday announced a partnership with Google Cloud to build two “supercomputers” on Google Cloud Platform. The Magic-G4 will be made up of Nvidia H100 GPUs, and the Magic G5 will use Nvidia’s next-gen Blackwell chips scheduled to come online next year. (GPUs, thanks to their ability to run many computations in parallel, are commonly used to train and serve generative AI models.)

    Magic says it aims to scale the latter cluster to “tens of thousands” of GPUs over time, and that together, the clusters will be able to achieve 160 exaflops, where one exaflop is equal to one quintillion computer operations per second.

    “We are excited to partner with Google and Nvidia to build our next-gen AI supercomputer on Google Cloud,” Magic co-founder and CEO Eric Steinberger said in a statement. “Nvidia’s [Blackwell] system will greatly improve inference and training efficiency for our models, and Google Cloud offers us the fastest timeline to scale, and a rich ecosystem of cloud services.”

    Steinberger and Sebastian De Ro co-founded Magic in 2022. In a previous interview, Steinberger told TechCrunch that he was inspired by the potential of AI at a young age; in high school, he and his friends wired up the school’s computers for machine-learning algorithm training.

    That experience planted the seeds for Steinberger’s computer science Bachelor’s program at Cambridge (he dropped out after a year) and, later, his job at Meta as an AI researcher. De Ro hailed from German business process management firm FireStart, where he worked his way up to the role of CTO. Steinberger and De Ro met at the environmental volunteer organization Steinberger co-created, ClimateScience.org.

    Magic develops AI-driven tools (not yet for sale) designed to help software engineers write, review, debug and plan code changes. The tools operate like an automated pair programmer, attempting to understand and continuously learn more about the context of various coding projects.

    Lots of platforms do the same, including the elephant in the room GitHub Copilot. But one of Magic’s innovations lies in its models’ ultra-long context windows. It calls the models’ architecture “Long-term Memory Network,” or “LTM” for short.

    A model’s context, or context window, refers to input data (e.g. code) that the model considers before generating output (e.g. additional code). A simple question — “Who won the 2020 U.S. presidential election?” — can serve as context, as can a movie script, show or audio clip.

    As context windows grow, so does the size of the documents — or codebases, as the case may be — being fit into them. Long context can prevent models from “forgetting” the content of recent docs and data, and from veering off topic and extrapolating wrongly.

    Magic claims its latest model, LTM-2-mini, has a 100 million-token context window. (Tokens are subdivided bits of raw data, like the syllables “fan,” “tas” and “tic” in the word “fantastic.”) One hundred million tokens is equivalent to around 10 million lines of code, or 750 novels. And it’s by far the largest context window of any commercial model; the next-largest are Google’s Gemini flagship models at 2 million tokens.

    Magic says that thanks to its long context, LTM-2-mini was able to implement a password strength meter for an open source project and create a calculator using a custom UI framework pretty much autonomously.

    The company’s now in the process of training a larger version of that model.

    Magic has a small team — around two dozen people — and no revenue to speak of. But it’s going after a market that could be worth $27.17 billion by 2032, according to an estimate by Polaris Research, and investors perceive that to be a worthwhile (and possibly quite lucrative) endeavor.

    Despite the security, copyright and reliability concerns around AI-powered assistive coding tools, developers have shown enthusiasm for them, with the vast majority of respondents in GitHub’s latest poll saying that they’ve adopted AI tools in some form. Microsoft reported in April that Copilot had over 1.3 million paying users and more than 50,000 business customers.

    And Magic’s ambitions are grander than automating routine software development tasks. On the company’s website, it speaks of a path to AGI — AI that can solve problems more reliably than humans can alone.

    Toward such AI, San Francisco-based Magic recently hired Ben Chess, a former lead on OpenAI’s supercomputing team, and plans to expand its cybersecurity, engineering, research and system engineering teams.

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  • Twenty eight sites receive funding from the National Park Service for restoration work

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    The National Park Service (NPS) announced $25.7 million in funding for the cultural and historic preservation of 59 nationally significant sites and collections. Among the buildings and sites receiving money for renovation and restoration projects are a Spanish colonial residence in Santa Barbara, a church by Frank Lloyd Wright, and a project to repair the steps at a Christopher Wren–designed building at the College of William and Mary.

    For 25 years, the Save America’s Treasures program has provided over $405 million from the Historic Preservation Fund (HPF) to the preservation and conservation of notable sites, collections, artifacts, and structures. National Park Service Director Chuck Sams noted in a statement, “It’s fitting to celebrate this milestone anniversary through a wide range of projects that help to pass the full history of America and its people down to future generations.”

    swimming pool grotto at the Vizcaya Museum and Gardens, one of the projects receiving funding from the National Park Service
    The swimming pool grotto at the Vizcaya Museum and Gardens (Elisa.rolle/Wikimedia Commons/CC BY-SA 4.0)

    The funding will be distributed to 28 historical sites in need of preservation or repair work. Money will also be allocated for over two dozen cultural institutions seeking to safeguard or digitize their collections and archives. Among the list of buildings and landscapes with prominent historical legacies, are the Longue Vue House and Gardens in New Orleans. The residence will receive funds to further recognize the work of Ellen Biddle Shipman, a landscape designer. Through the restoration and conservation of Shipman’s design, these funds carve the path for education and public awareness of Shipman’s influence and her emergence within the male-dominated field.

    Other notable sites on the list include the Vizcaya Museum and Gardens’ swimming pool grotto. The Mediterranean-style villa was once a center of entertainment. The house oft-referred to as the “Hearst Castle” of the East houses a collection of decorative furnishings and objects from Europe. Also notable is the Louisiana State University (LSU) Campus Mounds Preservation Project. The mounds, now part of the LSU Campus, were once sacred structures, constructed at least 6,000 years ago by Indigenous people. The grant will aid in preserving the stability of the mounds’ surface and stop ongoing damage to the site.

    The full list of historic sites receiving funding for preservation projects is reproduced below. A brief description of the scope for each project can be found here.

    California Missions Foundation | California
    Telluride Council for the Arts and Humanities | Colorado
    Vizcaya Museum and Gardens Trust | Florida
    Foundation for Homan Square | Illinois

    grassy mounds at Louisiana State University
    Funds will prevent erosion from continuing and add denser drought-resistant grass to stabilize the mounds’ surface. (Spatms/Wikimedia Commons/CC BY-SA 3.0)

    Louisiana State University | Louisiana
    Longue Vue House and Gardens Corporation | Louisiana
    Mount Vernon Place Conservancy | Maryland
    Captain Robert Bennet Forbes House Museum | Massachusetts
    Oakland University | Michigan
    The Durham Museum | Nebraska
    Dover Friends Meeting | New Hampshire
    Inlet Public/Private Association | New Jersey

    St. Bartholomew’s Conservancy | New York
    Historic Hudson Valley | New York
    Basilica Preservation Fund | North Carolina
    Rivers of Steel Heritage Corporation | Pennsylvania
    Pennsylvania Academy of the Fine Arts | Pennsylvania
    Arch Street Meeting House Preservation Trust | Pennsylvania
    Quintessence Theater Group | Pennsylvania
    Cathedral of St. Luke and St. Paul | South Carolina
    City of Dallas | Texas
    The Landmark Trust USA | Vermont

    main entrance to Christopher Wren building at the College of William and Mary
    Funding will rebuild the steps of the Christopher Wren building at the College of William and Mary. Skilled stonemasons, historic brick masons, and other specialized craftspeople will execute the work using Portland limestone. (MiguelYerena/Wikimedia Commons/CC BY-SA 4.0)

    College of William & Mary | Virginia
    Coalfield Development Corporation | West Virginia
    State Historical Society of Wisconsin | Wisconsin
    Center for Veterans Issues | Wisconsin
    Annunciation Greek Orthodox Church Foundation |Wisconsin



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