Latest AI News
Final 4 days to save up to $680 on your TechCrunch Disrupt 2026 pass
You don’t attendTechCrunch Disruptto sit in the audience. You go to gain leverage. If 2026 is a build year, a fundraise year, a hiring year, or a scale year, this is where momentum compounds. With just 4 days left before Super Early Bird pricing ends on February 27 at 11:59 p.m. PT, this is your opportunity to save up to $680 on your pass and secure your spot at the center of the tech ecosystem.Register here to save. From October 13 to 15 at Moscone West, 10,000+ founders, operators, and VCs will converge for three days of high-signal conversations and deal-making. Disrupt is not just content. It is access. You get: Last year alone, more than 20,000 curated meetings took place. In 2026, upgraded networking tools will make those connections even more targeted and efficient. One conversation can change your trajectory. AtDisrupt, that is the point. Disrupt has long been a stage for founders and investors who define eras. These are the kinds of voices that are candid, tactical, and often unfiltered. Previous speakers have included leaders of category-defining startups and top-tier venture firms, including: In 2025, Disrupt featured 200+ onstage conversations with 250+ leaders shaping AI, venture capital, hardware, growth strategy, and more. Expect that same caliber of insight in 2026. Keep an eye on theevent pageas the agenda rolls out. Startup Battlefieldreturns with 200 pre-Series A companies competing for $100,000 in equity-free funding, global visibility, and direct investor access. Alumni include Discord, Cloudflare, and Trello. If you want to see what and who is next, and hear directly from top VCs on what it takes to scale a viable startup, the Disrupt stage is where it happens. More than 300 startup exhibitorswill showcase new products across the venue, especially in the Expo Hall, where deal flow and discovery collide. You are not just observing trends. You are seeing them before they scale. From October 11 to 17, TechCrunch Disrupt Side Events take place across the Bay Area, including breakfasts, cocktail hours, panels, and founder meetups that extend the connections beyond the main stage. The main event is powerful. The surrounding ecosystem makes it even stronger. Super Early Bird pricing ends February 27 at 11:59 p.m. PT. If you plan to be in the rooms where capital moves, companies scale, and ideas turn into industries, now is the time to lock it in. Register now:
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Oura launches a proprietary AI model focused on women’s health
Ouraannouncedon Tuesday that it’s launching its first proprietary AI model to enable its AI chatbot, Oura Advisor, to deliver personalized insights around women’s health. The company says the model supports questions spanning the full reproductive health spectrum, from early menstrual cycles through menopause. The new model is rolling out in Oura Labs, the company’s opt-in, experimental feature hub within the Oura app. Oura says the new model draws on established medical standards, research, and knowledge sources reviewed by its in-house team of board-certified clinicians and women’s health experts. It also integrates biometric signals and long-term trends to deliver personalized guidance. As people areincreasingly turning to AI chatbotsforhealth guidance, from cycle changes to perimenopause symptoms, Oura says there is a need for models designed specifically for women. “This custom model is a fundamental shift in how we responsibly deploy AI in health to meet the needs of our members,” said Ricky Bloomfield, MD, chief medical officer at Oura, in a press release. “Women’s health is too complex—and too often overlooked—to rely on one-size-fits-all systems. By designing a model specifically for women and grounding it in trusted clinical science and real-world biometric data, we’re setting the standard for how responsible intelligence should be built and expanded across more areas of health, pairing rigorous science with the lived, longitudinal data that makes Oura uniquely powerful.” The launch of the new women’s health AI model comes as Oura Chief Commercial Officer Dorothy Kilroytold TechCrunchlast October that the company’s fastest-growing user segment isn’t gym rats, it’s women in their early twenties. When a user asks Oura Advisor a women’s health question, the chatbot prompts the new model to reference its research and knowledge sources while also analyzing the user’s relevant biometric signals across sleep, activity, cycle and pregnancy data, stress, and more. The new model is intentionally designed to be non-dismissive, reassuring, and emotionally supportive, the company notes. However, it’s not designed to be a doctor, as users shouldn’t use the chatbot for a diagnosis or treatment plan. Oura says the model is hosted entirely on Oura-controlled infrastructure, and that conversations are never shared or sold. Users who want to access the new model can opt into Oura Labs by navigating to the drop down menu on the upper left corner of the Oura app.
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Meta strikes up to $100B AMD chip deal as it chases ‘personal superintelligence’
Meta plans to purchase potentially up to $100 billion worth of AMD chips, enough to drive roughly six gigawatts of data center power demand, the companies announced Tuesday. As part of the multiyear agreement, AMD has issued Meta a performance-based warrant for up to 160 million shares of AMD common stock — or about 10% of the company — for $0.01 each, structured to vest alongside certain milestones. The full stock award is conditional on AMD’s share price, which would need to hit $600 for Meta to receive its final tranche,per The Wall Street Journal. AMD’s stock closed at $196.60 on Monday. Under the agreement, Meta will purchase AMD’s MI540 series of GPUs and its latest generation of CPUs. CPUs are increasingly becoming a core pillar of the AI inference compute stack because they’re efficient, easier to scale, and don’t tie companies solely to Nvidia. “The CPU market is absolutely on fire,” AMD CEO Lisa Su said Tuesday morning during an investor briefing. “There is significant demand. It has continued to grow, and it really is a result of the AI infrastructure deployments as inferencing scales, as agentic AI scales, and our portfolio is in an extremely good position.” AMD has been slowly gaining ground as AI firms look to reduce their reliance on Nvidia, which has been the longstanding leader in AI chips and has charged a premium for the title. Last October,AMD and OpenAI struck a similardeal trading equity for an agreement to buy chips. Meta CEO Mark Zuckerberg said the firm’s partnership with AMD is “an important step” as it diversifies its compute and works toward “personal superintelligence.” Zuckerberg has defined personal superintelligence as AI systems designed to deeply understand and empower individuals in their everyday lives. Meta has pledged to invest at least$600 billion in U.S. data centersand AI infrastructure over the next several years, including a projected capital expenditure spend of$135 billion in 2026.Meta recently unveiled plans for a $10 billiongas-powered data center campusin Indiana designed for 1 gigawatt of compute capacity. The AMD partnership comes a couple of weeks after Meta struck amultiyear dealto expand its data centers with millions of Nvidia’s latest CPUs and GPUs. The Facebook-maker is also working on its own in-house chips but hasreportedlyhit delays. This article has been updated with more information from AMD CEO Lisa Su.
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Music generator ProducerAI joins Google Labs
The generative AI music tool ProducerAI will become part of Google Labs, the companyannouncedon Tuesday. Backed by The Chainsmokers, the ProducerAI platform allows users to write natural language requests — something like “make a lofi beat”– to generate music. It uses Google DeepMind’sLyria 3music-generation model, which can turn text and even image inputs into audio outputs. Google announced last week that itsLyria 3capabilities would be introduced into the flagship Gemini app, but ProducerAI makes it possible for users to communicate with the AI model more like it’s a “collaboration partner,” to use the words of Elias Roman, Google Labs’ Senior Director of Product Management. “ProducerAI has allowed me to create in new ways,” Roman wrote in a blog post. “I’ve experimented with new genre blends, expressed how I feel with personalized birthday songs for my loved ones, and made custom workout soundtracks for myself and friends.” Google also shared that three-time Grammy-winning rapper Wyclef Jean used the Lyria 3 model and Google’s Music AI Sandbox on his recent song “Back From Abu Dhabi.” “This is not just a machine where you’re clicking a button a hundred times, and then you’re done. It’s a careful kind of curation where you’re going through and saying, ‘Oh, I think that’s something we can use,’” said Jeff Chang, Director of Product Management at Google DeepMind, in avideothe company put out. Jean recalls wanting to know what a flute would sound like in a track he already recorded, and being able to use Google’s tools to quickly add a flute sound to the mix. “What I want everybody to understand […] is you’re in the era where the human has to be the most creative,” Jean said in the video. “There’s one thing that you have over the AI: a soul. And there’s one thing that AI has over you: the infinite information.” Some musicians have ardentlyopposed the use of AI toolsin the music-making process, since it’s almost a given that a generative AI tool was trained on copyrighted data from artists without their consent. Hundreds of musicians, including stars like Billie Eilish, Katy Perry, and Jon Bon Jovi, signed an open letter in 2024 calling on tech companies not to undermine human creativity with AI music generation tools. A cohort of music publishers also recentlysuedthe AI company Anthropic for $3 billion, claiming that the company illegally downloaded more than 20,000 copyrighted songs, including sheet music, song lyrics, and musical compositions. (Anthropic was already ordered by the court to offer a$1.5 billionsettlement to authors whose books were pirated for AI training.) Other artists, however, have embraced the potential of this technology as a way to improve audio quality, rather than as a creative aid. Paul McCartney usedAI-powered noise reduction systems— the kind of technology that allows Zoom or FaceTime to block out unwanted background noises on your video calls — to clean up a decades-old, low-quality John Lennon demo. The resulting “new” Beatles track, “Now and Then,” won a Grammy in 2025. Meanwhile, AI music generation tools like Suno have created synthetic music that sounds real enough to top charts on Spotify and Billboard. Telisha Jones, a 31-year-old in Mississippi, used Suno to turn her (supposedly organic) poetry into the viral R&B song “How Was I Supposed To Know” and signed a record deal with Hallwood Media in a deal reportedly worth$3 million. The law remains unclear on the legality of using copyrighted works as training data — one federal judge, William Alsup,ruled last yearthat training on copyrighted data is legal, but pirating it is not.
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OpenAI COO says ‘we have not yet really seen AI penetrate enterprise business processes’
Earlier this month, OpenAI launched a new platform calledOpenAI Frontier for enterprises to build and manage agents, but OpenAI COO Brad Lightcap said that businesses haven’t yet seen AI adoption at scale. “One of the interesting things and some of the inspiration for the work we’ve been doing lately around OpenAI Frontier is we have not yet really seen enterprise AI penetrate enterprise business process,” the AI exec said on the sidelines of theIndia AI summit held last week in New Delhi. “You’ve got really powerful AI systems that any person can use in their individual capacity. And enterprises are these highly complex organizations with a lot of people, teams, all having to work together, a lot of context. There are very complex goals that have to be achieved using a lot of different systems and tools.” There is a lot of talk aroundAI agentstaking over business processesand claiming that“SaaS is dead”.While these predictions have moved SaaS stocks at times, they haven’t really come true. In fact, Lightcap said OpenAI wasa massive Slack user last year, indicating how much AI firms are still reliant on traditional enterprise software. In January,OpenAI CFO Sarah Friar posted that the company’s revenue is on the rise, with the startup ending 2025 with over $20 billion in annualized revenue. Lightcap said that demand is strong, without sharing any numbers. “We almost always find ourselves having to manage too much demand. We are still an organization that is growing, and so there is this global demand factor that we would love to be able to meet, and we are working as best as we can to be able to meet,” Lightcap said. At the same time, OpenAI is thinking about how to quantify success in the enterprise. Lightcap said that OpenAI will try to measure Frontier’s impact based on “business outcomes, not on seat licenses.” (The comapny hasn’t yet shared pricing for Frontier.) “Frontier is a way for us to experiment iteratively with how to actually bring AI into the really messy and complex areas of businesses that I think if we get that right, we’re going to learn a lot about both businesses and also AI systems,” Lightcap noted. Days after TechCrunch’s conversation, OpenAI partnered with consultancies likeBoston Consulting Group (BCG), McKinsey, Accenture, and Capgeminito deploy its technology in an enterprise push. Even rival Anthropic launched plugins for finance, engineering, and design for enterprises to build agents based on Claude. Meanwhile, the company doesn’t have a clear path of integrating recently acquired open-source tool OpenClaw, but Lightcap said that it gives OpenAI “a glimpse into the future” where agents can do “almost anything you want them to be able to do on a computer.” In keeping with the India AI summit, OpenAI has made a number of recent announcements around its business in the world’s largest market. The company said India was the second biggest user base of ChatGPT outside the U.S., withmore than 100 million weekly users. Lightcap said that voice as a modality is picking up in India and enabling OpenAI to reach more people. “Voice is so important here. And voice models now feel good enough and also good enough to run in low-latency and low-bandwidth environments, where you really can start to enable access to technology for a group of people who maybe were more disenfranchised than not,” Lightcap said. The company also signed an enterprise contract for the usage of its tools and to deploy compute. Lightcap noted India is fourth in India in terms of enterprise seats in Asia, which is low for a populous country, and OpenAI has a lot of scope to expand here. The AI company is also set to open two new offices in India in Mumbai and Bengaluru. However, these are likely to be sales and go-to-market offices. When I asked Lightcap if these offices would include technical talent, he said, “Never say never.” There is also a fear of job impact, especially in countries like India, where the IT services and BPO (Business Process Outsourcing) industry is prominent, as AI tools automate some of the tasks. In the past few weeks, Indian IT companystocks have dippedas the market is taking into account the fact that areas like coding might require fewer humans. Lightcap said that the company is being “grounded” in what it has observed in terms of jobs market. “Our view is that over time, jobs will change. I think we don’t yet know where, how, or what, but it seems inevitable that work will look different in the future than it looks today. And that’s natural, that’s part of the business cycle. It’s part of the global and dynamic economy that we live in. And so I think what we have to do is be able to obviously have empathy for where jobs are changing at a high rate,” he noted.
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Nimble raises $47M to give AI agents access to real-time web data
Believe it or not, web search is still thriving as an industry. As businesses invest in using AI agents to make the most of their data, there’s demand for tools that not only scrape the web to inform what those AI bots do, but also return those results in a way that’s easier to use with modern data tools. That’s the promise behind web search startupNimble, which recently raised a $47 million Series B round, led by Norwest. The New York company’s platform employs AI agents to search the web in real time, verify, and validate the results, and then structure the information into neat tables that can then be queried like a database. That last part is crucial here. LLMs and AI agents are great for searching the web, connecting results from a variety of sources, and analyzing them, but they often return the results in plain text, which can be difficult to work with at an enterprise level. And that’s before you factor in hallucinations, the risk of the agent misunderstanding your instructions, or the use of unreliable sources. By validating and structuring results into tables, Nimble lets companies use web data as if it were already part of their existing databases. The startup also integrates with enterprise data warehouses and data lakes — large centralized repositories where businesses store and analyze data — offered by the likes of Databricks and Snowflake. That means its AI agents can plug into a business’s trove of data, using it to build context, and shape how search results are structured and returned. In effect, this lets enterprises have live, structured web data as part of their existing data environments, Nimble CEO and co-founder Uri Knorovich (pictured above, middle) told TechCrunch. Such integrations also allow Nimble’s software to remember constraints — such as how you want the search to be performed, or which data sources to tap. This is particularly useful for applications such as competitor analysis, pricing research, know-your-customer (KYC) processes, brand monitoring, deep research, and financial analysis. (Knorovich noted that Nimble works to ensure all customer data remains within customers’ data infrastructure to comply with data retention and security policies.) To that end, the startup has partnered with Databricks, Snowflake, AWS and Microsoft to help streamline enterprise deployments that require access to internal data sources. (Databricks also participated in this Series B.) “Models can do a lot of things, but most production AI fails aren’t because the models are not good enough — it’s because of a data failure,” Knorovich said. “What we’re seeing today is that enterprises don’t need more AI; they need AI with good, reliable web search […] If you nail it down, if you can choose what your agent can search and cannot search, this is the tipping point for enterprises to say, ‘hey we can actually trust AI. We can actually put AI to work in more use cases’.” Knorovich says the ability to search the web in real time at scale, and validate and structure search results, is what sets Nimble apart from other data brokers already in the space. The startup currently has more than 100 customers, with the majority of its revenue coming from large enterprises, Fortune 500 companies, and even some Fortune 10 companies, including major retailers, hedge funds, banks, and consumer packaged goods companies, as well as some AI-native startups. “Nimble is tackling a problem that has existed for years without a proper solution and is now becoming of critical urgency,” Assaf Harel, partner at Norwest, said in a statement. “Trusted live web data is increasingly becoming a prerequisite for AI agents performing critical business decisions.” The Series B also saw participation from returning investors Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData. Proceeds from the round will be used to expand R&D in multi-agent web search and a governed data layer that processes and validates search results. Nimble has now raised a total of $75 million.
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New Relic launches new AI agent platform and OpenTelemetry tools
Companies are increasingly launching software to build and monitor AI agents in an effort to get enterprises to adopt AI. New Relic is no different. As the data observability company launches an AI agent platform of its own, it knows it isn’t the only game in town. New Relic on Tuesday unveiled a no-code agentic platform that lets enterprises put together data observability AI agents that monitor a company’s data to catch bugs and issues before they disrupt products. Called New Relic Agentic Platform, it lets companies deploy pre-built agents and manage existing bots as well. It also supports the model context protocol (MCP), which connects AI applications to external data sources, and integrates with other New Relic tools. New Relic isn’t looking to be the only platform that companies use to manage and deploy all of their AI agents, Brian Emerson, the startup’s new chief product officer, told TechCrunch. Instead, the aim is to offer clients the same agent-building capabilities they are getting elsewhere for observability as well. “We’re not building this as general purpose,” Emerson said. “We’re building it for outcomes that we care about inside observability. It’s also a world that allows us to work with the rest of the ecosystem or tools that exist out there, but bring it back into the context of problems we’re trying to solve around our personas and the observability domain.” Software that lets users manage AI agents has proliferated in recent months as companies look to figure out how to quell enterprises’ fears about giving AI agents access to their data and software. Salesforce was arguably the first to release an agent platform in late 2024, calling itAgentforce. OpenAI launched its own version of the technology,OpenAI Frontier, earlier this year. Research organization Gartner hascalledsuch agent platforms “necessary infrastructure” and a critical component of getting enterprises to adopt AI. Sticking with the theme of increasing enterprise tech adoption, New Relic also revealed new tools focused on OpenTelemetry (OTel), an open-source observability framework. The company said its application performance monitoring (APM) agents are now equipped with OTel capabilities, letting enterprises manage OTel data streams alongside their other data sources in one place. This is aimed at solving a previous fragmentation problem that was holding up mass enterprise adoption of the OTel framework. “Just send your OTel data to us,” Nic Benders, chief technology strategist at New Relic, said. “What we’ve discovered in this process is that it’s kind of a burden for a lot of teams out there in the world to run all of the OTel [data] collectors. So having a OTel like fleet management is something that’s very important.”
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Anthropic launches new push for enterprise agents with plugins for finance, engineering, and design
On Tuesday, Anthropic unveiledits new enterprise agents program, its most aggressive push yet to integrate agentic AI into everyday workplaces. In an official briefing, Anthropic’s head of Americas, Kate Jensen, told reporters that the new system would finally deliver on the promise of agentic AI. “2025 was meant to be the year agents transformed the enterprise, but the hype turned out to be mostly premature,” Jensen said. “It wasn’t a failure of effort. It was a failure of approach.” Under the new program, companies can use the plug-in system to deploy pre-built agents to help with common enterprise tasks, including financial research and engineering specifications. The result is a major opportunity to grow Anthropic’s enterprise client base — and a significant threat to SaaS products currently performing those functions. “We believe that the future of work means everybody having their own custom agent,” Anthropic product officer Matt Piccolella told TechCrunch. Much of the enterprise agents program draws on previously announced technology, particularly Claude Cowork and the plugin system, which was announced in research previewon January 30th. The systems launched today are largely focused on making those tools easier to deploy within a company, including private software marketplaces, controlled data flows, and customized plugins. The result is a system for deploying Claude-powered agents with the same controls a corporate IT department would expect when deploying software. “Admins want to be able to have really, really, really tailored workflows and skills for their specific organization,” Piccolella said. “And this allows the admin of a Claude Cowork organization to be able to do this in a very centralized way.” The stock plugins included at launch take aim at particular departments present within most companies, including agents designed for finance, legal, and HR departments. Each plugin includes basic skills common across different companies, although Anthropic expects that companies will modify each plugin to bring it in line with unique needs and customs. In the case of finance, the stock plugin gives Claude the basic information and data flows necessary to perform market and competitive research, financial modeling, and other common tasks for finance teams. The HR plugin includes skills for generating job descriptions, onboarding materials, and offer letters, among others. The launch also includes a number of new enterprise connectors, including integrations for Gmail, DocuSign, and Clay, among others. Previously unavailable, these connectors will allow agents to pull in data and context directly from the linked system.
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Bharat1 AI Research & Innovation City to Launch AI Superpark in Bengaluru with NVIDIA
The 5,00,000 square feet B1 AI Superpark will anchor a larger four million square feet AI district, aiming to host 25,000 researchers.
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HCL GUVI Partners with OpenAI to Integrate AI Tools Into Learning Programmes
HCL GUVI also concluded the India Impact Buildathon, which drew over 40,000 participants across 100+ cities.
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Canva Buys Cavalry & MangoAI to Boost Creative, Ad Tech
The twin acquisitions target motion design and AI-driven advertising performance optimisation.
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Xflow Raises $16.6 Mn to Simplify Cross-Border Payments for Indian Businesses
Fintech startup Xflow raised $16.6 million from General Catalyst, Stripe and PayPal Ventures to make cross-border payments easier.
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