SiMa.ai raises $150M Series C at $1.45B valuation for on-device AI chips

SiMa.ai, a startup building chips and software that let machines run AI models directly on the device, has raised $150 million in a Series C round that values the company at $1.45 billion, according to TechCrunch.

The round was co-led by Fidelity Management & Research Company and Amplify, with participation from Alter Venture Partners, Dell Technologies Capital and StepStone Group. The new funding brings SiMa.ai's total capital raised to more than $500 million, TechCrunch reports.

A sharp step up in valuation

According to PitchBook data cited by TechCrunch, the startup was previously valued at $960 million following an $85 million Series B in July 2025. The Series C therefore lifts the company's valuation by roughly half in the span of about fourteen months, and pushes it past the billion-dollar mark for the first time.

Keeping AI on the hardware

SiMa.ai was founded in 2018 by Krishna Rangasayee, who previously served as chief operating officer at AI chipmaker Groq. The company focuses on energy-efficient processors paired with software that enables devices such as robots, drones and cameras to handle AI workloads locally, without sending data back and forth to the cloud.

That local-first design matters for machines that need to make split-second decisions. Removing the cloud round-trip cuts latency and reduces reliance on network connectivity, which are practical constraints for equipment operating in factories, in the air or in the field.

According to TechCrunch, SiMa.ai is betting that its low-latency performance and its comparatively affordable chips — positioned against Nvidia's GPUs — will help it capture the growing market for physical AI devices, a category that includes humanoid robots alongside more conventional machines.

Competition in a crowded silicon market

The edge AI chip segment is attracting significant attention as device makers look for alternatives to power-hungry data center GPUs. SiMa.ai's pitch rests on two levers: efficiency, so that battery-powered or thermally constrained devices can run meaningful models, and cost, since Nvidia's hardware is expensive relative to many embedded budgets.

The involvement of institutional investors such as Fidelity and StepStone, alongside strategic backer Dell Technologies Capital, signals confidence that demand for on-device inference hardware will scale with the broader push into robotics and autonomous machines.

Why it matters

This round is a notable milestone for edge AI hardware. Most of the current AI investment boom has flowed toward data center infrastructure and the large models that run there, but a parallel market is forming around physical AI — robots, drones and sensing devices that need intelligence at the point of action rather than in a remote data center.

SiMa.ai's $1.45 billion valuation shows investors are now paying unicorn prices for silicon aimed squarely at that shift. It also illustrates the emerging competition facing Nvidia: rather than challenging the company in the data center, a new generation of chip startups is targeting workloads where efficiency, latency and price matter more than raw training throughput.

If robots and autonomous devices proliferate as many in the industry expect, the chips that let them think for themselves — quickly, cheaply and without a network connection — could become a foundational layer of the hardware stack. SiMa.ai now has over $500 million in total funding to make its case that it can supply that layer.