AI startup Magic targets $1.5B valuation in funding round

US-based startup Magic, which specialises in developing artificial intelligence models for software writing, is reportedly negotiating with investors for a sum exceeding $200 million as part of its latest funding round.

Three sources familiar with the deal-making who spoke to Reuters on condition of anonymity, noting that the discussions are private, expect the round to value the company at approximately $1.5 billion.

Within just a few months of its last funding, Magic is now negotiating a significant new investment round that could inflate its valuation threefold. This is occurring despite Magic not having any products for sale or a concrete revenue stream. Jane Street, expected to invest, has not commented on these discussions, according to Reuters.

The rapid rise in Magic’s valuation stands out even more because the company is small compared to most startups, with just over 20 employees. PitchBook reported that the company’s February funding round valued it at $500 million. Since its founding in 2022, Magic has raised $140 million from investors such as Nat Friedman and Daniel Gross’s NFDG Ventures and Alphabet’s CapitalG.

It is also one of many signs that the venture financing community has focused on one of the most promising applications of generative AI technologies: automated software development. Building a tool that can assist or even replace human software developers with AI represents one of the most significant cost-saving opportunities in tech today. As such, investors are betting big on these tools.

The potential of this space has recently attracted even more investor excitement, partly driven by the success of Microsoft’s GitHub Copilot. Augment, one of the most prominent AI coding startups recently raised $252 million; this was followed by Cognition, which secured $175 million at a $2 billion valuation in a funding round led by Founders Fund.

Investors view GitHub Copilot’s success as a strong indicator of market potential. GitHub reported a 40% year-over-year revenue increase in its latest quarter, driven mainly by Copilot, which has amassed 1.3 million paid subscribers. Brian Dudley, partner at Adams Street Partners, commented on this trend: “The success of Microsoft has validated the commercial market for AI code assistants, leading everyone to believe there is clear market demand and a customer willingness to pay for the right product. The opportunity is enormous, with likely multiple winners in this category.”

While currently available AI coding assistants like GitHub Copilot or OpenAI’s ChatGPT can suggest code completions, the next frontier in this field is the development of AI systems capable of designing and writing entire software applications without human intervention. Magic and a few other startups are pursuing this ambitious goal by training proprietary large language models specifically for coding tasks. This endeavour is capital-intensive, requiring significant investments in data acquisition, computational resources, and energy.

Magic intends to allocate its new funding towards enhancing its AI models, with a particular focus on improving their capacity to support long-context windows. This refers to AI systems capable of processing larger amounts of data in a single query, potentially offering a competitive edge in the market. However, one source familiar with Magic’s technology stated that the company is able to handle a significant amount of context because it uses methods different from the traditional ‘transformer models’ like those in OpenAI’s GPT series, on which most large language models rely.

Importantly, Magic is not alone in this endeavour. TechCrunch reported in June that another startup, Paris-based Poolside AI, is also in discussions with investors about raising as much as $450 million at a valuation north of $2 billion. Like Magic, Poolside AI currently lacks commercially available products.

This surge of investment in AI-powered coding tools underscores the tech industry’s growing focus on automating and enhancing software development processes, potentially heralding a significant shift in how software is created and maintained in the future.

(Photo by Alexander Grey)

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Tags: AI, coding, programming