SiMa.ai Expands Strategic Collaboration with Synopsys to Accelerate Automotive AI Innovation

Transforming ADAS and In-Vehicle Infotainment Breakthroughs with Innovative ML IP, Chiplets, and System-on-Chip Reference Architectures

SAN JOSE, Calif., July 30, 2025 /PRNewswire/ -- SiMa.ai, a pioneer in ultra-efficient machine learning system-on-chip (MLSoC) platform, today announced the next phase of their strategic collaboration with Synopsys, the leading provider of engineering solutions from silicon to systems, to accelerate AI innovation for the automotive industry.

This collaboration will combine SiMa.ai's energy-efficient ML processing with Synopsys' automotive IP and design tools to develop advanced chiplet architectures and reference SoC designs optimized for Advanced Driver Assistance Systems (ADAS) and In-Vehicle Infotainment (IVI). 

"Automotive AI presents exciting challenges and massive potential," said Krishna Rangasayee, CEO of SiMa.ai. "With Synopsys' ecosystem and proven design tools, we can fast-track our ML innovation into automotive platforms."

Addressing Critical Industry Needs

As vehicles become increasingly autonomous and connected, automakers face mounting demand for intelligent, efficient AI processing. This collaboration focuses on overcoming key industry challenges, including:

• Ultra-low power consumption for EVs and hybrids
• Real-time processing for safety-critical ADAS functions
• Scalable designs for diverse performance needs
• Cost-effective architectures for broad market adoption
• Compliance with automotive-grade functional safety

"The automotive industry's transformation toward intelligent, software-defined vehicles requires unprecedented levels of AI processing efficiency and reliability," said Ravi Subramanian, Chief Product Management Officer at Synopsys. "Our partnership with SiMa.ai is driven by strong interest from mutual customers to combine Synopsys' proven automotive IP portfolio and design engineering expertise with SiMa.ai's innovative machine learning acceleration technologies to deliver solutions that meet the unique demands of automotive AI applications."

Enabling Faster Development with Advanced tools:

The expanded collaboration integrates SiMa.ai's ML simulators into Synopsys' design platforms:

• Platform Architect™: Enabling exploration of architectural options and model ML requirements optimized for automotive OEM specific ADAS/IVI workloads.
• Virtualizer™ Development Kit (VDK): Enabling early software development and testing across the automotive ecosystem.
• ZeBu® Emulation: Providing pre-silicon power, performance, and efficiency validation, supported by 95-97% accuracy between pre-silicon power emulation estimates and actual silicon.

Benefits for OEMs and Tier1s

This collaboration helps automotive customers:

• Accelerate ADAS feature development like object detection, lane keeping assistance, automated parking, and collision avoidance systems.
• Enhance infotainment experiences with AI-powered voice recognition, gesture control, personalized user interfaces, and advanced multimedia processing.
• Reduce time-to-market and development risk with proven IP and reference designs.
• Achieve strict automotive safety and reliability standards.
• Utilize Synopsys consulting to streamline development.

Availability

Machine learning accelerator IP and associated software will be available from SiMa.ai for early access customers by mid-2026 with production release targeted for end of 2026. Machine learning IP Chiplet that integrates technologies from both the companies will be available by mid-2027.

About SiMa.ai

SiMa.ai is pioneering ultra-efficient machine learning system-on-chip (MLSoC) platforms that deliver breakthrough performance-per-watt for edge AI applications. The company's innovative sparse neural network processing architecture and comprehensive software stack enable customers to deploy advanced AI capabilities across automotive, industrial, and consumer applications while meeting strict power, cost, and latency requirements. Learn more at www.sima.ai.

This press release contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934. Actual results may differ materially from those projected in the forward-looking statements.

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SOURCE SiMa.ai