Tech secures $70M funding to introduce a multimodal GenAI chip, a Silicon Valley-based startup producing embedded ML system-on-chip (SoC) platforms, today announced it has raised a $70 million extension funding round as it plans to bring its second generation chipset, specially designed for multimodal. generative AI processing, on the market.

According to Gartner, the global market for AI-enabled chips is expected to more than double by 2027 to $119.4 billion from 2023. However, only a few players have started producing semiconductors dedicated to AI applications. Most major competitors initially focused on supporting AI in the cloud. Nonetheless, various reports predict significant growth in the edge AI market, meaning that the hardware processing of AI calculations is closer to the data collection source than in a centralized cloud., named after Seema, the Hindi word for frontier, is working to capitalize on this shift by offering its cutting-edge AI SoC to organizations in industrial manufacturing, retail, aerospace, defense, agriculture and health.

The San Jose-based startup, which targets the market segment between 5W and 25W power consumption, has launched its first ML SoC to integrate 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 more than 50 companies around the world, Krishna Rangasayee, founder and CEO of, told TechCrunch.

The startup touts that its current generation of ML SoCs delivered the highest FPS/W results on the MLPerf benchmark in the closed split, Edge, and Power MLPerf Inference 4.0 categories. However, the first generation chipset focused on classic computer vision.

As demand for GenAI increases, is expected to introduce its second-generation ML SoC in the first quarter of 2025, with a focus on providing its customers with multi-modal GenAI capability. The new SoC will be an “evolutionary change” from its predecessor with “some architectural tweaks” compared to 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 would also be compatible with any modality, including audio, speech, text and image. This would work as a single platform for all AI across computer vision, transformers and multimodal GenAI, the startup said.

“You can’t predict the future, but you can choose the vector and say: this is the vector I want to bet on. And I want to continue to evolve around my vector. That’s kind of the approach we took architecturally,” Rangasayee said. “But fundamentally, we didn’t really give up or have to radically change our architecture. This is also the advantage of adopting a software-centric architecture that allows for more flexibility and agility. has Taiwan’s TSMC as a manufacturing partner for its first and second generation AI chipsets and Arm Holdings as a supplier for its computing subsystem. The second-generation chipset will be based on TSMC’s 6nm process technology and will feature integrated Synopsys EV74 vision processors for pre- and post-processing in computer vision applications.

The startup considers incumbents such as NXP, Texas Instruments, STMicro, Renaissance and Microchip Technology and Nvidia among its competitors, as well as AI chip startups like Hailo. However, he sees Nvidia as the main competitor, just like other AI chip startups.

Rangasayee told TechCrunch that while Nvidia is “fantastic in the cloud,” it hasn’t built a platform for the edge. He believes that Nvidia lacks energy efficiency and adequate software for cutting-edge AI. Likewise, he claimed that other startups building AI chipsets are not solving problems in the system and are simply offering ML acceleration.

“Among all our peers, Hailo did a very good job. And it’s not us who are better than them. But from our point of view, our value proposition is quite different,” he said.

The founder added that offers higher performance and better power efficiency than Hailo. He also said that the system software of is quite different and efficient to GenAI.

“As long as we’re solving customer problems, and we’re doing it better than anyone else, we’re in a good position,” he said.’s new all-stock financing, led by Maverick Capital and with participation from Point72 and Jericho, extends the startup’s $30 million Series B round, originally 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 raised a total of $270 million.

The company currently has 160 employees, including 65 at its R&D center in Bangalore, India. plans to increase this headcount by adding new roles and expanding its R&D capacity. She also wants to develop a marketing team for Indian customers. Additionally, the startup plans to expand its customer-facing teams globally, starting with Korea and Japan, then moving to Europe and the United States.

“The computational intensity of generative AI has precipitated a paradigm shift in data center architecture. The next phase of this evolution will be the widespread adoption of AI at the edge. Just as the data center has been revolutionized, the edge computing landscape is on the verge of a complete transformation. has the essential trifecta of a best-in-class team, cutting-edge technology and forward momentum, positioning it as a key player for customers navigating this tectonic shift. We are excited to join forces with to capture this once-in-a-generation opportunity,” Andrew Homan, Senior Managing Director at Maverick Capital, said in a statement.


Back to top button