SixSense secures $8.5M for AI-powered chip defect detection
SixSense, a Singapore-based deep tech startup, has secured $8.5 million in Series A funding, bringing its total capital raised to approximately $12 million. The company specializes in an AI-powered platform designed to help semiconductor manufacturers predict and detect potential chip defects on production lines in real time. The round was led by Peak XV’s Surge (formerly Sequoia India & SEA), with participation from Alpha Intelligence Capital, FEBE, and other investors.
Founded in 2018 by engineers Akanksha Jagwani (CTO) and Avni Agarwal (CEO), SixSense was established to tackle a critical issue in semiconductor manufacturing: the conversion of vast amounts of raw production data – from defect images to equipment signals – into actionable, real-time insights. Despite the immense data generated on the factory floor, the co-founders identified a surprising lack of immediate, intelligent analysis.
Avni Agarwal highlighted the industry’s reliance on manual and fragmented inspection processes, despite its reputation for precision. She noted that while fabs are equipped with dashboards and inline inspection systems, these often merely display data without deeper analysis. “The burden of using it for decision-making still falls on engineers: they must spot patterns, investigate anomalies, and trace root causes,” Agarwal explained, emphasizing that this process is time-consuming, subjective, and struggles to scale with increasing process complexity.
The leadership team brings complementary expertise to the venture. Akanksha Jagwani has a strong background in manufacturing, quality control, and software automation, having developed solutions for companies like Hyundai Motors and GE. Avni Agarwal, a skilled coder with a mathematics background, previously built large-scale data analytics systems at Visa and was keen to apply AI to traditional industries beyond fintech.
SixSense’s platform empowers engineers with early warnings, enabling them to address potential issues before they escalate. Its capabilities include real-time defect detection, root cause analysis, and failure prediction. Crucially, the platform is designed for use by process engineers, not data scientists. Agarwal emphasized its practicality: “Process engineers can fine-tune models using their own fab data, deploy them in under two days, and trust the results — all without writing a single line of code. That’s what makes the platform both powerful and practical.”
While the competitive landscape includes in-house engineering solutions, integrated AI from inspection equipment makers, and other startups like Landing.ai and Robovision, SixSense has already made significant inroads. Its AI platform is currently deployed at major semiconductor manufacturers such as GlobalFoundries and JCET, having processed over 100 million chips to date. Customers have reported substantial improvements, including up to 30% faster production cycles, a 1-2% boost in yield, and a 90% reduction in manual inspection work. The system is also widely compatible, working with inspection equipment that covers over 60% of the global market.
SixSense targets large-scale chipmakers, including foundries, outsourced semiconductor assembly and test providers (OSATs), and integrated device manufacturers (IDMs). The company is currently operating with fabs in Singapore, Malaysia, Taiwan, and Israel, with plans for expansion into the U.S. The ongoing geopolitical shifts, particularly between the U.S. and China, are reshaping the global semiconductor landscape, spurring new manufacturing investments worldwide. Agarwal views this as a significant tailwind for SixSense. “We’re seeing fabs and OSATs expand aggressively in Malaysia, Singapore, Vietnam, India, and the U.S.,” she stated. “Many of these new facilities are starting fresh – without legacy systems weighing them down. That makes them far more open to AI-native approaches like ours from day one.”