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The Rise of Pit AI Swedish startup Pit, led by Voi co-founders Fredrik Hjelm and Adam Jafer, has gained attention for its innovative approach to enterprise AI. With a $16 million seed round led by a16z, Pit is poised to make a significant impact in the industry. Founders' Background and Vision Founded by Voi co-founders Fredrik Hjelm and Adam Jafer Jafer left Voi last summer after a seven-year tenure Hjelm is still Voi's CEO, but will play a less hands-on role in Pit Pit's vision is to create custom software to automate business processes, positioning itself as an 'AI product team as a service.' The company has developed two key products: Pit Studio, which lets enterprise employees guide it through processes that could be handled by AI-generated software, and Pit Cloud, which provides that software in a way that meets enterprise requirements on governance, certifications, and auditability. The Market Opportunity Pit is entering a crowded market, but hopes to differentiate itself through its unique approach and European DNA. The startup is targeting industrials and plans to benefit from the current tailwinds for sovereign tech, especially in critical sectors. Financial Backing and Growth Plans $16 million seed round led by a16z Backed by Pit's founders, Lakestar, executives from American tech companies, and wealthy families from the Nordics Pit is preparing to scale up commercially and is hiring solution engineers to drive enterprise adoption With its innovative approach and strong financial backing, Pit AI is one to watch in the European tech scene.

The Power of Anthropic's Mythos Model When Anthropic unveiled its new Mythos model in April, it also delivered a stern warning to anyone developing software. The model was so powerful at sniffing out software vulnerabilities, the lab claimed, that it had discovered thousands of high-severity bugs that would need to be fixed before it could be made public. Improving Software Security with AI Now, security researchers for Mozilla's Firefox browser are providing a closer look at what that process has looked like in practice, and what Mythos' powers mean for software security at large. In a post published on Thursday, Mozilla said Mythos has unearthed a wealth of high-severity bugs, including some that had lain dormant in the code for more than a decade. The Data Behind the Discovery In April 2026, Firefox shipped 423 bug fixes, compared to just 31 exactly a year earlier. The researchers have also published details on 12 of the bugs, which range from a pair of unusual sandbox vulnerabilities, to a 15-year-old error in how the browser parses an HTML element. The Impact on Cybersecurity The fact that the system helped reveal vulnerabilities in Firefox's 'sandbox' system is particularly impressive, given how intricate an attack that exploits it needs to be. To find sandbox vulnerabilities, the model must write a compromised patch for the browser, then attack the most secure part of the software with the new code implemented. Finding and demonstrating the bug is a delicate, multi-step process, requiring both creativity and close attention. The Future of AI in Cybersecurity It's still not clear how AI's emerging capabilities will change the broader balance of power in cybersecurity. One month since Mythos was previewed, most of the bugs discovered likely haven't been patched, which makes it hard to capture the full scope of their impact. Anthropic has been scrupulous about following responsible disclosure norms, but it's likely bad actors are using similar techniques behind the scenes, even if the models they're using aren't quite as good. The Prediction Speaking at a recent event, Anthropic CEO Dario Amodei was optimistic that the new tools would ultimately favor defenders. 'If we handle this right, we could be in a better position than we started, because we fixed all these bugs. There are only so many bugs to find,' Amodei said. 'So I think there's a better world on the other side of this.'

DeepSeek’s Funding Surge: From $20B to $45B in Weeks DeepSeek, the Chinese AI lab known for a cost‑efficient large language model, is in talks to raise its first venture‑capital round that could push its valuation to $45 billion, up from $20 billion just weeks earlier. First Venture Capital Round Targets Chinese AI Champion The round will be led by the state investment vehicle China Integrated Circuit Industry Investment Fund. Potential co‑investors include cloud giants Tencent and Alibaba. Founder Liang Wenfeng, who owns nearly 90% of the company, is seeking capital to retain talent amid competitor poaching. Valuation Leap and Investor Line‑up: Numbers at a Glance Previous valuation: $20 billion Target valuation: $45 billion Founder ownership: ~90% Key investors: China Integrated Circuit Industry Investment Fund, Tencent, Alibaba Model advantage: runs on Huawei chips, lower compute cost Strategic Implications for China’s AI Independence The funding aligns with Beijing’s goal to develop home‑grown AI hardware and software, reducing reliance on U.S. chips. By optimizing models for Huawei silicon, DeepSeek offers a domestic alternative to OpenAI and Anthropic, potentially accelerating China’s AI ecosystem. What the Next Funding Milestone Could Mean for Global AI Competition If the round closes at the projected valuation, DeepSeek could attract further private and state capital, scale its model offerings, and challenge Western AI leaders on both performance and cost. Analysts expect increased pressure on U.S. firms to secure supply chains and consider strategic partnerships in Asia.

SAP's Strategic Bet on AI Enterprise software giant SAP is making a significant bet on artificial intelligence (AI) with the acquisition of German startup Prior Labs for an undisclosed amount. As part of the deal, SAP plans to invest approximately $1.16 billion over the next four years to grow Prior Labs into an AI lab focused on structured data. The Event Details Prior Labs, founded just 18 months ago, specializes in tabular foundation models (TFMs) that can make predictions from data stored in tables and databases. This technology is seen as a better fit for enterprises than language models, particularly for SAP, whose software products rely heavily on databases. The Data Analysis The acquisition is a significant exit for Prior Labs' founders, Frank Hutter, Noah Hollmann, and Sauraj Gambhir, with sources indicating a healthy payout of over half a billion dollars in cash upfront. Prior Labs' TabPFN model series has gained traction among developers, with over three million downloads of its open-source models. The Impact Analysis The deal is part of SAP's broader strategy to bolster its AI capabilities and compete with emerging technologies. SAP has been investing in generative AI companies, including Anthropic, Aleph Alpha, and Cohere, and has developed its own relational pretrained transformer model, SAP-RPT-1. The Prediction With this acquisition, SAP aims to create a new "globally-leading frontier AI lab for structured data" in Europe. The company hopes that Prior Labs will develop TFMs that can combine data with language, reasoning, and domain knowledge, leading to innovative AI solutions for enterprises.

Replit’s Billion‑Dollar Run‑Rate Surge At a sold‑out StrictlyVC event, Amjad Masad outlined how Replit grew from $2.8 million in 2024 revenue to a trajectory that could exceed a $1 billion annual run‑rate within months, positioning the firm as a heavyweight in AI‑assisted software creation. Why Replit’s Economics Defy a Cursor‑SpaceX Sale Masad contrasted Replit’s financial health with Cursor’s reported negative 23% gross margins and the speculative $60 billion SpaceX acquisition talk. He argued that Replit’s positive gross margins, product‑led growth, and focus on non‑technical creators give it a sustainable path without needing a buy‑out. Replit has been gross‑margin positive for over a year. Target market: non‑technical users who previously could not build software. End‑to‑end platform includes prompts, deployment, security, and managed databases. Revenue, Retention, and Margin Numbers Paint a Strong Picture Key metrics highlighted during the interview: Net revenue retention reaching as high as 300% in certain enterprise accounts. Enterprise customers such as Zillow and Meta upgraded organically after product adoption. Customers report ROI multiples of 10‑30×; a $100,000 monthly spend can generate $2‑10 million in value. Transaction volume through the newly integrated Stripe system is growing in triple‑digit month‑over‑month percentages. Apple’s App Store Blockade and Its Ripple Across the AI‑Coding Landscape Replit has been stuck in App Store “purgatory” for months, a situation Masad attributes to Apple feeling threatened by Replit’s ability to push code to iOS devices. Apple claims the blockage is due to post‑approval code downloads, a charge Masad calls a lie and says he is prepared to litigate. Four‑year presence on the App Store, used by students in under‑privileged communities. Apple’s restriction does not threaten core revenue but harms brand perception and user acquisition. Potential precedent for other AI‑coding platforms seeking mobile distribution. What’s Next for Replit: Independence, Customer‑Equity Deals, and Market Position Looking forward, Masad emphasized three strategic pillars: Maintain independence despite occasional acquisition interest from partners. Explore equity‑for‑services arrangements, investing in startups that originated on Replit. Double down on security and full‑stack capabilities to differentiate from “vibe‑coding” competitors. If Replit continues to leverage its high retention, strong margins, and growing ecosystem, it could set a new benchmark for AI‑driven development platforms while forcing Apple to reconsider its App Store policies.

The Pentagon's AI Partnerships The Pentagon said on Friday it had reached agreements with seven leading artificial intelligence (AI) companies: SpaceX, OpenAI, Google, Nvidia, Reflection, Microsoft and Amazon Web Services. The Scope of the Agreements “These agreements accelerate the transformation toward establishing the United States military as an AI-first fighting force and will strengthen our warfighters’ ability to maintain decision superiority across all domains of warfare,” the Pentagon said in a statement. The Companies Involved SpaceX OpenAI Google Nvidia Reflection Microsoft Amazon Web Services The Impact on AI Development The US Department of Defense is budgeting tens of billions of dollars for numerous technology firms’ cutting edge programs related to intelligence, drone warfare, classified and unclassified information networks and much more. It has requested $54bn for the development of autonomous weapons alone. The Controversy Surrounding Anthropic Anthropic, which makes the popular Claude chatbot, had rejected including the lawful use standard in its contract with the Defense Department in a high-profile feud with the bureau last month. The Pentagon labeled Anthropic a supply-chain risk last month, the first time an American company has been designated as such. The Future of AI in the Military Defense department officials believe signing with Anthropic’s rivals could bring the holdout startup back to the negotiating table. Anthropic’s latest AI model, the cybersecurity-focused Mythos, has rattled government officials and bankers over its ability to find vulnerabilities in well-tested software.

The Upgrade from Assistant to GeminiGoogle is fundamentally upgrading the in-car experience by replacing the legacy Google Assistant with its advanced Gemini AI model across millions of vehicles equipped with Google built-in. This transition marks a significant leap from simple voice commands to a more fluid, conversational interface designed for safety and utility.Millions of Vehicles on the RoadThe rollout begins in the U.S. with English-language support, expanding over the coming months. Crucially, this update is not limited to new models; it applies to compatible existing cars via software updates. This mirrors the strategy seen with General Motors, which recently revealed Gemini is coming to approximately 4 million vehicles from model year 2022 and newer, spanning brands like Cadillac, Chevrolet, Buick, and GMC.Redefining the In-Car ExperienceThe shift enables drivers to interact with their vehicles using natural language. Users can now ask complex queries, such as finding a highly rated restaurant with outdoor seating along their route. Gemini can then handle follow-up tasks like checking parking availability or menu options based on dietary preferences.Gemini Live: A beta feature allowing for open-ended, real-time conversations.Task Automation: Controlling vehicle settings like heat, music, and navigation.Message Handling: Summarizing and responding to incoming messages hands-free.The Road Ahead for AI IntegrationGoogle plans to expand Gemini support to additional languages and regions, deepening its integration with the broader Google ecosystem, including Gmail, Google Calendar, and Google Home. This rollout signals a broader industry trend where automotive interfaces are evolving from static displays to intelligent, conversational co-pilots.

The Journey from Prototype to ClearanceBuilding a medical device is fundamentally different from standard software development. This week on Build Mode, host Isabelle Johannessen sat down with Robhy Bustami, co-founder and CEO of BioticsAI, to discuss the arduous path from a $100,000 prototype to FDA clearance. Bustami, a Startup Battlefield winner, detailed how his team is building an AI copilot for ultrasound designed to detect fetal abnormalities. The conversation revealed that the traditional startup mantra of 'move fast and break things' is obsolete in the medical sector, replaced by a necessity for extreme precision and coordination.Market Validation and Resource AllocationThe episode provides a strategic look at the 'data' driving medtech success. BioticsAI's recognition as a Startup Battlefield winner serves as a key validation of their technology's potential. However, Bustami emphasized that the primary data point for founders is not just market traction, but the successful navigation of complex regulatory pathways. This requires a significant reallocation of resources—shifting focus from rapid feature deployment to ensuring safety, reliability, and compliance with FDA standards.Shifting the MedTech CultureThe core impact of this discussion lies in the cultural shift it highlights for the industry. As timelines for FDA approval remain uncertain, the ability to maintain team morale and investor confidence becomes a critical operational metric. Bustami noted that building in a regulated industry requires a foundation of trust rather than speed. This signals a broader trend where medtech startups must balance the pressure of hyper-growth with the ethical and legal responsibilities of patient safety.The Future of AI in Healthcare RegulationLooking ahead, the medtech landscape will likely see a consolidation of companies that prioritize long-term compliance over short-term hype. As more AI copilots enter the market, the winners will be those founders who master the art of 'slow and steady' innovation. The next wave of medical breakthroughs will depend not just on algorithmic superiority, but on the ability to build sustainable organizations capable of weathering the regulatory storm.

Salesforce's AI Roadmap Strategy Artificial intelligence continues to advance at a dizzying clip, forcing enterprises to develop and release new products quicker than ever or risk becoming irrelevant to a faster-moving competitor. Salesforce believes it has found a strategy that allows it to keep up even if it isn’t clear where AI is headed next. The customer management software giant is crowdsourcing its AI roadmap in real time. Crowdsourcing AI Development Salesforce is certainly not the only company to work intimately with its customers for feedback on its products. However, it’s notable considering the sheer size of the company, the pace of new product launches or fixes to existing ones, and the granular level of these relationships. These aren’t annual or even quarterly discussions. Salesforce is meeting with some customers as often as once a week. The Role of Customer Feedback “The 18,000 customers are a wellspring of information and a wealth of information that is really needed to get to customer success,” Jayesh Govindarajan, executive vice president at Salesforce AI, told TechCrunch in a recent interview. “The stack that we’ve built has resonated with these customers. Over time we can get context to be better, and as it gets better, and LLMs get better, agent systems do more and more fully autonomous behaviors. That’s a long-running innovation track and we’re going to invest in that.” Rapid Product Releases Salesforce credits its customers for the rate of its product releases. The company told TechCrunch that by letting its customers lead the way, it is able to build an AI product roadmap that can quickly react to where AI technology is headed. Real-World Impact Engine, a travel management platform, is one of the companies within Salesforce’s customer feedback loop. And it’s not a casual relationship. The company’s operations team meets with Salesforce weekly, according to Engine founder and CEO Elia Wallen. Through the partnership, Engine gets access to AI tools before they’re released. Wallen said the access helps Engine stay competitive and get more value out of these tools than it would otherwise. The Future of AI Development This strategy also allows the company to roll out solutions and workflows built by users to its broader customer base too. Federal credit union PenFed has been able to slim down its tech stack by working closely with Salesforce, Shree Reddy, the company’s chief innovation officer and executive vice president, told TechCrunch.