Tech
AI coding assistant Supermaven raises cash from OpenAI and Perplexity co-founders
Jacob Jackson was all-in on AI early in his career.
Jackson co-founded Tabnine, the AI coding assistant that went on to raise close to $60 million in venture backing, while still a computer science student at the University of Waterloo. After selling Tabnine to Codata in 2019 (during his final exams), Jackson joined OpenAI as an intern, where he worked until 2022.
It’s at that juncture Jackson had the urge to start a company again, one focused on supporting common developer workflows.
“In the years since I built Tabnine, tools like ChatGPT and Github Copilot have changed the way developers work,” Jackson told TechCrunch. “It’s a really exciting time to be working on developer tools because the underlying technology has improved so much since I started Tabnine — which has led to many more developers becoming interested in using AI tools to accelerate their workflow.”
So Jackson started Supermaven, an AI coding platform along the lines of Tabnine but with a few quality of life and technical upgrades.
Supermaven’s in-house generative AI model, Babble, can understand a lot of code at once, Jackson says, thanks to a 1 million-token context window. (In data science, tokens are subdivided bits of raw data — like the syllables “fan,” “tas” and “tic” in the word “fantastic.”)
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). Long context can prevent models from “forgetting” the content of recent docs and data, and from veering off topic and extrapolating wrongly.
“Our large context window helps reduce the frequency of hallucinations because it lets the model draw answers from the context in situations where it would otherwise have to guess,” Jackson said.
One million tokens is a big context window, indeed. But it’s not bigger than AI coding startup Magic’s, which is 100 million tokens. Meanwhile, Google’s recently introduced Code Assist tool matches Supermaven’s context at 1 million tokens.
So what are Supermaven’s advantages over rivals? Well, Jackson claims that Babble is lower-latency thanks to a “new neural architecture.” He wouldn’t elaborate beyond saying that the architecture was developed “from scratch.”
“Supermaven spends 10 to 20 seconds processing a developer’s code repository to become familiar with its APIs and the unique conventions of its codebase,” Jackson said. “With lower latency because of our in-house model serving infrastructure, our tool remains responsive while working with the long prompts that come with large codebases.”
The market for AI coding tools is a large and growing one, with Polaris Research projecting that it’ll be worth $27.17 billion by 2032. The vast majority of respondents in GitHub’s latest dev poll say that they’ve adopted AI tools in some form, and over 1.8 million people — and ~50,000 businesses — are paying for GitHub Copilot.
But Supermaven — along with startup competitors like Cognition, Anysphere, Poolside, Codeium, and Augment — have ethical and legal challenges to overcome.
Businesses are often wary of exposing proprietary code to a third party; for instance, Apple reportedly banned staff from using Copilot last year, citing concerns about confidential data leakage. Some code-generating tools trained using restrictively licensed or copyrighted code have been shown to regurgitate that code when prompted in a certain way, posing a liability risk (i.e., developers that incorporate the code could be sued). And, because AI makes mistakes, assistive coding tools can result in more mistaken and insecure code being pushed to codebases.
Jackson said that Supermaven doesn’t use customer data to train its models. He did admit, however, that the company retains data for a week to “make the system quick and responsive,” he said. On the subject of copyright, Jackson didn’t explicitly deny that Babble was trained on IP-protected code — only that it was “trained almost exclusively on publicly available code rather than a scrape of the public internet” to “reduce exposure to toxic content during training.”
Customers don’t appear to be dissuaded. Over 35,000 developers are using Supermaven, Jackson says, and a sizeable chunk are paying for the premium Pro ($10 per month) and Team ($10 per month per use) plans. Supermaven’s annual recurring revenue reached $1 million this year on the back of a user base that’s grown 3x since the platform’s February launch.
That momentum got the attention of VCs.
Supermaven this week announced its first outside funding: a $12 million round led by Bessemer Venture Partners and high-profile angel investors including OpenAI co-founder John Schulman and Perplexity co-founder Denis Yarats. Jackson says that the plan is to spend the money on hiring developers (Supermaven has a five-person team presently) and developing Supermaven’s text editor, which is currently in beta.
“We plan to grow significantly through the end of the year,” he added. “Despite headwinds for tech overall, the market for coding copilots has been growing quickly. Our growth since our launch in February — as well as our most recent funding round — position us well as we head into next year.”
Tech
Exclusive: Google deepens Thinking Machines Lab ties with new multi-billion-dollar deal
Former OpenAI executive Mira Murati’s startup, Thinking Machines Lab, has signed a new multi-billion-dollar agreement to expand its use of Google Cloud’s AI infrastructure, including systems powered by Nvidia’s latest GPUs, TechCrunch has exclusively learned.
The deal is valued in the single-digit billions, according to a source familiar with the matter, and includes access to Google’s latest AI systems built atop Nvidia’s new GB300 chips, alongside infrastructure services to support model training and deployment.
Google has been actively striking a number of cloud deals with AI developers as it aims to wrap together its AI computing offerings with other cloud services like storage, a Kubernetes engine, and Spanner, its database product. Earlier this month, Anthropic signed an agreement with Google and Broadcom for multiple gigawatts of tensor processing unit (TPUs) capacity (these are Google’s custom-designed AI chips for machine learning workloads).
But the competition is fierce. Just this week, Anthropic also signed a new agreement with Amazon to secure up to 5 gigawatts of capacity for training and deploying Claude.
Earlier this year, Thinking Machines partnered with Nvidia in a deal that included an investment from the chipmaker. But this is the first time the lab has struck a deal with a cloud services provider. The deal is not exclusive, so Thinking Machines may use multiple cloud providers over time, but it’s still a sign that Google is looking to lock in fast-growing frontier labs early.
Murati left her job as OpenAI’s chief technologist and founded Thinking Machines in February 2025. The company, which soon afterwards raised a $2 billion seed round at a $12 billion valuation, has remained highly secretive, but launched its first product in October. Dubbed Tinker, it’s a tool that automates the creation of custom frontier AI models.
Wednesday’s deal provided some insight into what Thinking Machines is developing. In a press release, Google noted that it can support the startup’s reinforcement learning workloads, which Tinker’s architecture relies on. Reinforcement learning is a training approach that has underpinned recent breakthroughs at labs, including DeepMind and OpenAI, and the scale of the Google Cloud deal reflects how computationally expensive that work can get.
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Thinking Machines is among the first Google Cloud customers to access its GB300-powered systems, which offer a 2X improvement in training and serving speed compared to prior-generation GPUs, per Google.
“Google Cloud got us running at record speed with the reliability we demand,” Myle Ott, a founding researcher at Thinking Machines, said in a statement.
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Tech
The most interesting startups showcased at Google Cloud Next 2026
Google Cloud Next is taking place this week in Las Vegas, and one clear message has emerged: Google wants AI startups on its cloud. To that end, it made several startup-related announcements.
The most significant is that the tech giant has earmarked a new $750 million budget to help its Cloud partners sell more AI agents to enterprises. This funding is available to partners ranging from startups to the big consulting firms. It can be used for costs like Gemini proof-of-concept projects, Google forward-deployed engineers, cloud credits, and deployment rebates.
Google also highlighted a long list of startups that are using Google Cloud, either newly signed or expanding their footprint. Among them are a few standout names:
Lovable is expanding its use of Google Cloud by launching a new coding agent through Google’s enterprise app marketplace. Lovable is the fast-growing vibe coding startup and was on a $400 million ARR track as of February, it said.
Notion, Silicon Valley’s favorite AI-infused document productivity app, most recently valued at about $11 billion, is using Gemini models to power its text and image generation features.
Gamma, an AI-powered PowerPoint killer recently valued at a $2.1 billion valuation, is using Google’s state-of-the-art image model Nano Banana 2 and other Google Cloud features.
Inferact, the commercial inference startup from the creators of the popular open-source project vLLM, is accessing Nvidia’s GPUs through Google Cloud, in addition to using the tech giant’s AI stack.
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ComfyUI, the popular open-source tool for creating AI-generated images and multimedia, also offers access to Nano Banana 2 and is using other Cloud features.
Other startups that received the Google Cloud shout-out this year include:
ChorusView, which makes AI-powered smart tags that track the condition and movement of goods in real time.
Emergent AI, a vibe coding platform.
ExaCare AI, which makes AI software for post-acute medical care facilities.
Insilica, which creates AI-generated regulatory-compliant chemical safety reports.
Optii, which makes AI-enhanced hotel operations software.
Parallel AI, which builds web search and research APIs built for AI agents.
Proximal Health, which makes AI-powered software that automates the insurance claims adjudication process.
Reducto, which does AI-powered document parsing.
Stord, which handles e-commerce fulfillment and parcel operations.
Stylitics, which makes AI image generation software for retailers for tasks like outfit styling and product bundles.
Temporal, a developer cloud environment built to prevent failures.
Vapi, which makes dev tools for building conversational voice agents.
Vurvey Labs, which conducts synthetic market research via AI agents.
Wand, an in-game assistant for single-player PC games.
Watershed, which makes software that helps enterprises report on and manage sustainability programs.
ZenBusiness, an all-in-one back-office tool for small businesses that includes an AI chat assistant.
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Tech
Duolingo is now giving free users access to advanced learning content
Duolingo announced on Wednesday that its advanced language learning content is now available for free across nine languages: English, Spanish, French, German, Italian, Portuguese, Japanese, Korean, and Chinese. Users can access this content through the web, iOS, and Android devices.
This advanced content is at the B2 level on the Common European Framework of Reference for Languages (CEFR), which is the international standard for language skills that schools and employers recognize. B2 level content refers to learning materials without translations, complex scenarios, and specialized vocabulary.
The new offering will include features like “Advanced Stories,” which helps with reading comprehension, and DuoRadio, a podcast-like audio experience for listening comprehension.
Now that Duolingo users can tap into this advanced learning content for free, they can level up their skills, whether that’s practicing for job interviews, prepping for studying abroad, or tackling complex news articles, films, and books without relying on translations.
The company says this positions it as the only free app to offer advanced-level learning across these nine languages at no cost. While competitors like Babbel and Busuu offer advanced courses, they typically require paid subscriptions. For instance, Busuu has some CEFR-aligned courses up to the B2 level, but the free version is pretty limited and doesn’t offer lessons like grammar explanations, so users need to pay for full access.
Previously, Duolingo only provided free courses that capped at A2 or B1 levels, mainly focusing on basic communication skills.
The company is positioning this free advanced learning offering as an enticing opportunity for job seekers, framing language learning as a practical pathway to improving employability in an increasingly global workforce.
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This comes at a time when the job market remains highly competitive and overall growth has slowed. Research from the American Council on the Teaching of Foreign Languages shows that learning a second language can raise someone’s employability by as much as 50%.
“Reaching job-ready proficiency in a new language used to be out of reach for most people,” Bozena Pajak, head of learning science at Duolingo, said in a statement. “It took years of expensive classes or immersive experiences that not everyone could access.”
Duolingo’s decision to offer advanced learning for free is also a strategy to increase its free user base. In its Q4 earnings report, the company stated that it has 52.7 million daily active users, demonstrating 30% growth compared to the previous year. This number is higher than its paid subscriber base, which stands at 12.2 million. However, Duolingo’s shares fell after the company projected that the year-over-year bookings growth rate for Q2 2026 is expected to experience a slight decline.
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