Singapore-based startup SixSense has raised US$8.5 million in a series A round led by Peak XV’s Surge, with participation from Alpha Intelligence Capital, FEBE, and others, bringing its total funding to about US$ 12 million.

SixSense develops an AI platform that helps semiconductor manufacturers detect and predict chip defects on production lines in real time.

Founded in 2018 by Akanksha Jagwani and Avni Agarwal, the company focuses on converting production data into insights to improve chip quality and yield.

SixSense says its platform is used by major manufacturers, including GlobalFoundries and JCET, and claims it has processed over 100 million chips.

The startup’s customers include foundries and outsourced semiconductor assembly and test providers in Singapore, Malaysia, Taiwan, and Israel, and it is now expanding into the US.

SixSense operates in a competitive sector alongside established industrial software providers and startups like Landing.ai and Robovision.

The company is expanding its presence in the US as global chip manufacturing investments shift amid geopolitical tensions.

🔗 Source: TechCrunch

🧠 Food for thought

1️⃣ Semiconductor boom creates quality control pressures at unprecedented scale

The semiconductor industry’s explosive growth is creating massive quality challenges that traditional inspection methods can’t handle effectively.

The industry experienced 19% growth in 2024 and is projected to reach $697 billion in sales by 2025, driven primarily by AI and data center demands1.

This rapid scaling coincides with increasingly complex manufacturing requirements, where device miniaturization below 10nm increases complexity and reduces manufacturing yields2.

As chip features continue shrinking, even tiny contaminants have significant impact on production quality, making contamination control critical at every stage of manufacturing2.

SixSense’s reported results, including 30% faster production cycles and 1-2% yield improvements, become increasingly valuable when applied across this rapidly expanding production volume.

The combination of explosive demand growth and tighter quality requirements creates a strong economic case for AI-powered inspection systems that can scale with production volumes while maintaining precision.