Majestic Labs has emerged from stealth with $100 million in funding – a $10 million seed round and $90 million Series A round. The company’s cofounder and CEO Ofer Schacham is an Israeli who lived in Silicon Valley for many years but recently returned to Israel.
Schacham was talking about AI long before ChatGPT burst onto the scene three years ago. Twenty years ago, he was asked by the US Defense Advanced Research Projects Agency (DARPA), to develop AI processors for military needs after completing his doctorate at Stanford.
Schacham was hired by Google and was responsible for developing the computer vision chips for Pixel devices, and became head of AI processors for Google’s edge devices. Mark Zuckerberg took him to set up Meta’s chip lab to develop its metaverse headsets and for years he managed the entire chip division from Israel. After being the “chip czar” of Sergey Brin then Mark Zuckerberg for most of his career, Schacham is now his own man at Majestic Labs, which he founded with his former colleagues at Meta and Google – Sha Rabii and Masumi Reynders.
Majestic Labs has been founded to challenge Nvidia in its soft underbelly – the inefficiency of its memory components, an issue that severely limits the computational capacity of each individual processor and dictates the need for companies interested in training complex language models to buy more and more expensive graphics processors – the same components that are so critical for training AI models. Nvidia itself benefits from this inefficiency because it sells more processors.
In the meantime, the problem is not solved and is even burdening Nvidia and OpenAI. Altman’s Law, a rule of thumb that is somewhat analogous to Moore’s Law in the world of chips, says the cost of AI processing is equal to the square of the number of its users and when the number of AI queries increases dramatically not only in chat engines, but also in creating videos, or creating documents, the industry reaches a boiling point, literally, where not only the cost increases, but also the temperature in data centers, which in turn slows down the chips. One of the main bottlenecks of the graphics processors that dictate this – whether they are Nvidia, AMD or Google processors – is the limited active memory on each chip – up to 192 gigabytes of memory in each – which requires the purchase of many expensive chips, and this problem is being solved by Majestic Labs
Majestic does not offer its own graphics processor, as do more successful competitors like AMD, or less successful ones like Intel, SambaNova, Cerebras and Groq, but replaces Nvidia’s AI server with its own server – a very ambitious vision that includes not only a dedicated processor developed in Israel, but also a new server structure that connects to each graphics processor huge amounts of memory with higher bandwidths than anything currently seen on the market – the result is equivalent to connecting up to 1,000 times more memory to each graphics processor compared to the Nvidia, AMD or Google AI servers, according to the company. It does all this from a modest office in a building on the border of Kfar Saba and Hod Hasharon. The company has 50 employees, half of whom are in Israel.
Majestic Labs has declined to say at what valuation the money has been raised but “Globes” estimates that the company’s valuation is $300-400 million. The seed round was led by Lux Capital and the Series A round was led by Bow Wave Capital. Other investors include SBI, Upfront, Grove Ventures, Hetz Ventures, QP Ventures, Aidenlair Global and TAL Ventures, the only Israeli fund in the larger $90 million financing round.
Schacham says, “The industry is trying to run language models with trillions of parameters in aggregate and all this on processors whose maximum memory capacity does not exceed 192 gigabytes. At home, our AI uses are no longer satisfied with scanning a QR code and decoding it: we ask the chat several questions a day, upload a 150-page document and ask it to translate it into Chinese and create images from scratch using verbal descriptions, so the memory requirement is estimated in terabytes of data on processors that can work in gigabytes.”
By rebuilding the server, the company claims, Majestic Labs is able to increase memory accessibility by up to a thousand times compared with existing solutions, improve the server’s computing performance by more than 50 times, and actually save 10 or 20 Nvidia servers for every server it sells.
The experience of the three founders, who were hired by Zuckerberg himself to run Meta’s chip lab, their doctorates and hundred patents they have registered in the US over the years, and their connections in the industry play a major role and allow them to talk to many potential customers and develop servers for them that will meet their future needs in 2027. “We know how to work and understand their product requirements,” says Schacham.
Majestic Labs is not the only startup that intends to compete with Nvidia. it is challenged by US companies that have developed dedicated AI chips such as SambaNova, Cerebras, Groq and Tenstorrent, as well as Israel’s NextSilicon.
“The company was founded for the AI era,” says Schacham, without referring to the rivals by name. “And while many companies try to come from a hardware or “hardened” solution, As the chip giants launch another solution that doesn’t improve the memory problem, the models continue to grow and change, so it’s important that the solution is flexible and programmable. One of the lessons I learned the hard way as a chip development manager, as someone who spent 12 years at Google and Meta, is that software is king. The bottleneck in training large models can probably be solved at the system level, not by launching this or that chip.”
Schacham doesn’t believe there is a bubble in the AI industry, but he distinguishes between companies that will become bigger and those that will disappear: “As early as 2014, I drove the first prototypes of Google’s autonomous cars, and when I visited their data centers and saw how with AI efficiency increased by 20%, I understood where the future was going,” he says. “Without a doubt, every field that AI touches will change rapidly. I saw it from the cockpit at Google, seeing it in the areas of image processing.
“But is there a bubble? AI is growing at a dizzying pace, and there are companies that are justifiably valued at an ever-increasing value, but there are also companies that are overvalued and won’t survive. AI will be a greater revolution than all the other revolutions that preceded it, but not every company that enters will survive. Is Google and Meta’s spending on purchasing capital equipment to run AI unjustified? I don’t think so – tell me how many times you use ChatGPT or try an AI engine to renovate images.”
Published by Globes, Israel business news – en.globes.co.il – on November 10, 2025.
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