Deep tech booty based on Singapore Six It has developed a AI -powered platform, which helps semiconductor manufacturers to predict and detect potential chip defects in real -time production lines.
It has raised $ 8.5 million in series A, bringing its total funding to about $ 12 million. The round was driven by the wave of Peak XV (former Sequoia India & Sea), participating in Alpha Intelligence Capital, Febe and others.
Founded in 2018 by engineers Akkshasha Jagwani (CTO) and AVNI Agarwal (CEO), Sixsense aims to tackle a fundamental challenge in the manufacture of semiconductors: Converting raw production data, from defect to equipment, in real -time ideas that help the quality of quality. the performance.
Despite the huge volume of data created on the Fab floor, what stood out to co -founders was a stunning lack of intelligence in real time.
Akansha brings a deep understanding of construction, quality control and automation of software through the experience of creating automation solutions for manufacturers such as Hyundai Motors and GE and the development of LED products in newly established companies such as Embibe. Agarwal adds technical experience since its time to Visa, where it has created large -scale data analysis systems, some of which were later protected as commercial secrets. A specialized encoder with a strong background in mathematics, he has long been interested in applying AI to traditional industries beyond Fintech.
Together, the twin evaluated the fields from the Air Force in the automotive industry before landing on semiconductors. Despite the reputation of the semiconductor industry for precision, inspection procedures remain largely manual and fragmented, Agarwal told TechCrunch. After talking to more than 50 engineers, it became clear that there is a significant room for modernizing the way in which quality controls are made, he added.
FABs today are full of control panels, SPC charts and Inline inspection systems, but most only show data without further resolution, Agarwal said. “The weight of its use to make decisions still falls on engineers: [they must] Signs, research the abnormalities and trace elements. This is time -consuming, subjective, and does not escalate well with the increasing complexity of the processes. ”
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Sixsense provides timely warnings to deal with possible issues before escalating with possibilities such as defects detecting, analyzing the basic causes and failure to fail.
The Sixsense platform is also specifically designed to be used by process engineers and not by data scientists, Agarwal said. “Process engineers can refine models using their own FAB data, develop them in less than two days and trust the results-without writing a single order of code. This makes the platform both strong and practical.”
The competitive landscape includes internal mechanical groups using tools such as Cognex and Halcon, inspection equipment manufacturers that incorporate AI into their systems and newly established businesses, including landing.
Sixsense’s AI platform is already used in large semiconductor manufacturers such as Globalfoundries and JCET, with more than 100 million brands to date. Customers have reported up to 30% faster production cycles, an increase of 1-2% in performance and a 90% decrease in inspection work, the founders said. The system is compatible with inspection equipment covering more than 60% of the world market.
“Our target customers are large-scale chipmakers-including foundry, external semiconductor assembly and OSATS and integrated manufacturers (IDMS),” Agarwal said. “We are already working with Fabs in Singapore, Malaysia, Taiwan and Israel. They are now expanding to the US”
Geopolitical tensions, especially between the US and China, are reshaping where they are becoming chips, leading new investments in construction around the world.
“We see Fabs and Osats expanding aggressively to Malaysia, Singapore, Vietnam, India and the US-and this is a queue for us, because Agarwal said in the area.
