SiMa.ai, a Silicon Valley–based startup producing embedded machine learning (ML) system-on-chip (SoC) platforms, today announced that it has raised a $70 million extension funding round as it plans to bring its second-generation chipset, specifically built for multimodal generative AI processing, to market.
According to Gartner, the market for AI-supporting chips globally is forecast to more than double by 2027 to $119.4 billion compared to 2023. However, only a few players have started producing dedicated semiconductors for AI applications. Most of the prominent contenders initially focused on supporting AI in the cloud. Nonetheless, various reports predicted a significant growth in the market of AI on the edge, which means the hardware processing AI computations are closer to the data gathering source than in a centralized cloud. SiMa.ai, named after “seema,” the Hindi word for “boundary,” strives to leverage this shift by offering its edge AI SoC to organizations across industrial manufacturing, retail, aerospace, defense, agriculture and healthcare sectors.
The San Jose–headquartered startup, which targets the market segment between 5W and 25W of energy usage, launched its first ML SoC to bring AI and ML through an integrated software-hardware combination. This includes its proprietary chipset and no-code software called Palette. The combination has already been used by over 50 companies globally, Krishna Rangasayee, the founder and CEO of SiMa.ai, told TechCrunch.
The startup touts that its current generation of the ML SoC delivered the highest FPS/W results on the MLPerf benchmark across the MLPerf Inference 4.0 closed, edge and power division categories. However, the first-generation chipset was focused on classic computer vision.
As the demand for GenAI is growing, SiMa.ai is set to introduce its second-generation ML SoC in the first quarter of 2025 with an emphasis on providing its customers with multimodal GenAI capability. The new SoC will be an “evolutionary change” over its predecessor with “a few architectural tunings” over the existing ML chipset, Rangasayee said. He added that the fundamental concepts would remain the same.
The new GenAI SoC would adapt to any framework, network, model and sensor — similar to the company’s existing ML platform — and will also be compatible with any modality, including audio, speech, text and image. It would work as a single-edge platform for all AI across computer vision, transformers and multimodal GenAI, the startup said.
“You cannot predict the future, but you can pick the vector and say, hey, that’s the vector I want to bet on. And I want to continue evolving around my vector. That’s kind of the approach that we took architecturally,” said Rangasayee. “But fundamentally, we really haven’t walked away or had to drastically change our architecture. This is also the benefit of us taking a software-centric architecture that allows more flexibility and nimbleness.”
SiMa.ai has Taiwan’s TSMC as the manufacturing partner for both its first- and second-generation AI chipsets and Arm Holdings as the provider for its compute subsystem. The second-generation chipset will be based on TSMC’s 6nm process technology and include Synopsys EV74 embedded vision processors for pre- and post-processing in computer vision applications.
The startup considers incumbents like NXP, Texas Instruments, STMicro, Renaissance and Microchip Technology, and Nvidia, as well as AI chip startups like Hailo, among the competition. However, it considers Nvidia as the primary competitor — just like other AI chip startups.
Rangasayee told TechCrunch that while Nvidia is “fantastic in the cloud,” it has not built a platform for the edge. He believes that Nvidia lacks adequate power efficiency and software for edge AI. Similarly, he asserted that other startups building AI chipsets do not solve system problems and are just offering ML acceleration.
“Amongst all of our peers, Hailo has done a really good job. And it’s not us being better than them. But from our perspective, our value proposition is quite different,” he said.
The founder continued that SiMa.ai delivers higher performance and better power efficiency than Hailo. He also said SiMa.ai’s system software is quite different and effective for GenAI.
“As long as we’re solving customer problems, and we are better at doing that than anybody else, we are in a good place,” he said.
SiMa.ai’s fresh all-equity funding, led by Maverick Capital and with participation from Point72 and Jericho, extends the startup’s $30 million Series B round, initially announced in May 2022. Existing investors, including Amplify Partners, Dell Technologies Capital, Fidelity Management and Lip-Bu Tan also participated in the additional investment. With this fundraising, the five-year-old startup has raised a total of $270 million.
The company currently has 160 employees, 65 of whom are at its R&D center in Bengaluru, India. SiMa.ai plans to grow that headcount by adding new roles and extending its R&D capability. It also wants to develop a go-to-market team for Indian customers. Further, the startup plans to scale its customer-facing teams globally, starting with Korea and Japan and in Europe and the U.S.
“The computational intensity of generative AI has precipitated a paradigm shift in data center architecture. The next phase in this evolution will be widespread adoption of AI at the edge. Just as the data center has been revolutionized, the edge computing landscape is poised for a complete transformation. SiMa.ai possesses the essential trifecta of a best-in-class team, cutting-edge technology, and forward momentum, positioning it as a key player for customers traversing this tectonic shift. We’re excited to join forces with SiMa.ai to seize this once-in-a-generation opportunity,” said Andrew Homan, senior managing director at Maverick Capital, in a statement.
