AI Coding Assistant Supermaven Secures $12M Funding from Tech Industry Leaders

AI coding assistant Supermaven raises cash from OpenAI and Perplexity co-founders

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."

Supermaven nabs $12M for its AI coding assistant - SiliconANGLE

Supermaven Inc., a startup with an artificial intelligence coding assistant of the same name, today announced that it has closed a $12 million funding round led by Bessemer. The investment also included contributions from several angel investors. The group included OpenAI co-founder John Schulman, Perplexity AI Inc. co-founder Denis Yarats and Intercom Inc. co-founder Eoghan McCabe. Supermaven distributes its AI assistant in the form of an extension for popular code editors, the applications that developers use to write software. The assistant can analyze the snippet of code that an engineer is writing and generate autocomplete suggestions. Moreover, it's capable of generating new snippets from scratch based on natural language instructions from the user. Supermaven supports two dozen programming languages. The list includes Java, Python and other enterprise mainstays as well as more specialized syntaxes such as Assembly. The latter language, which gives developers direct access to low-level processor features, is used to program systems such as connected devices. Supermaven's assistant is powered by an internally-developed AI model called Babble that debuted in June. It's 2.5 times the size of the company's previous neural network and was trained on a larger corpus of code. It's also faster: Supermaven says that Babble can generate code suggestions three times quicker than the competition, which reduces wait times for developers. Another selling point of the model is its context window. Supermaven says that Babble can ingest four million characters' worth of code, which allows it to map out an application's entire code base in some cases. This can improve the quality of the AI's programming suggestions when it tackles tasks that require an understanding of how an application's modules interact with one another. Alongside Babble-powered code suggestions, Supermaven provides a sidebar called Supermaven Chat that it embeds into the user's code editor. The feature offers access to large language models from OpenAI, Anthropic PBC and other AI companies. Developers can ask those models for programming advice and then paste the AI-generated suggestions from the Supermaven Chat sidebar into their code editor's main window. Supermaven will use its newly raised capital to build a code editor of its own. The reason, Chief Executive Officer Jacob Jackson explained in a blog post, is that some of the features Supermaven hopes to build for its AI assistant require the ability to display interface elements "inline with the code" written by developers. Third-party editors provide limited support for such interface customization.