{"id":87967,"date":"2025-08-01T00:52:38","date_gmt":"2025-08-01T00:52:38","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2025\/08\/01\/female-founded-semiconductor-ai-startup-sixsense-raises-8-5m\/"},"modified":"2025-08-01T00:53:44","modified_gmt":"2025-08-01T00:53:44","slug":"female-founded-semiconductor-ai-startup-sixsense-raises-8-5m","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2025\/08\/01\/female-founded-semiconductor-ai-startup-sixsense-raises-8-5m\/","title":{"rendered":"Female-founded semiconductor AI startup SixSense raises $8.5M"},"content":{"rendered":"

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A Singapore-based deep tech startup known as SixSense<\/a> has developed an AI-powered platform that helps semiconductor producers predict and detect potential chip defects on manufacturing traces in actual time.<\/p>\n

It has raised $8.5 million in Sequence A bringing its whole funding to round $12 million. The spherical was led by Peak XV\u2019s Surge (previously Sequoia India & SEA), with participation from Alpha Intelligence Capital, FEBE, and others.<\/p>\n

Based in 2018 by engineers Akanksha Jagwani (CTO) and Avni Agarwal (CEO), SixSense goals to deal with a elementary problem in semiconductor manufacturing: changing uncooked manufacturing information, from defect photographs to tools indicators, into real-time insights that assist factories forestall high quality points and enhance yield.<\/p>\n

Regardless of the sheer quantity of information generated on the fab ground, what stood out to the co-founders was a shocking lack of real-time intelligence.<\/p>\n

Akanksha brings a deep understanding of producing, high quality management, and software program automation by her expertise constructing automation options for producers like Hyundai Motors and GE and led product growth at startups like Embibe. Agarwal provides technical expertise from her time at Visa, the place she constructed large-scale information analytics methods, a few of which have been later protected as commerce secrets and techniques. A talented coder with a powerful background in arithmetic, she had lengthy been all for making use of AI to conventional industries past fintech.<\/p>\n

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Picture Credit:<\/strong>SixSense<\/span><\/figcaption><\/figure>\n

Collectively, the duo evaluated sectors from aviation to automotive earlier than touchdown on semiconductors. Regardless of the semiconductor trade\u2019s status for precision, inspection processes stay largely guide and fragmented, Agarwal instructed TechCrunch. After talking with greater than 50 engineers, it grew to become clear there\u2019s important room to modernize how high quality checks are accomplished, she added.<\/p>\n

Fabs at present are crammed with dashboards, SPC charts, and inline inspection methods, however most solely show information with out additional evaluation, Agarwal mentioned. \u201cThe burden of utilizing it for decision-making nonetheless falls on engineers: [they must] spot patterns, examine anomalies, and hint root causes. That\u2019s time-consuming, subjective, and doesn\u2019t scale effectively with growing course of complexity.\u201d<\/p>\n

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Techcrunch occasion<\/p>\n

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SixSense gives engineers with early warnings to deal with potential points earlier than they escalate with capabilities similar to defect detection, root trigger evaluation, and failure prediction.<\/p>\n

SixSense\u2019s platform can be particularly designed for use by course of engineers relatively than information scientists, Agarwal mentioned. \u201cCourse of engineers can fine-tune fashions utilizing their very own fab information, deploy them in below two days, and belief the outcomes \u2014 all with out writing a single line of code. That\u2019s what makes the platform each highly effective and sensible.\u201d<\/p>\n

The aggressive panorama consists of in-house engineering groups utilizing instruments like Cognex and Halcon, inspection tools makers integrating AI into their methods, and startups together with Touchdown.ai and Robovision.<\/p>\n

SixSense\u2019s AI platform is already in use at main semiconductor producers like GlobalFoundries and JCET, with greater than 100 million chips processed up to now. Clients have reported as much as 30% quicker manufacturing cycles, a 1-2% increase in yield, and a 90% discount in guide inspection work, the founders mentioned. The system is appropriate with inspection tools that covers over 60% of the worldwide market.<\/p>\n

\u201cOur goal clients are large-scale chipmakers \u2014 together with foundries, outsourced semiconductor meeting and check suppliers (OSATs), and built-in system producers (IDMs),\u201d Agarwal mentioned. \u201cWe\u2019re already working with fabs in Singapore, Malaysia, Taiwan, and Israel, and are actually increasing into the U.S.\u201d<\/p>\n

Geopolitical tensions, particularly between the U.S. and China, are reshaping the place chips are made, driving new manufacturing investments throughout the globe.<\/p>\n

\u201cWe\u2019re seeing fabs and OSATs develop aggressively in Malaysia, Singapore, Vietnam, India, and the U.S. \u2014 and that\u2019s a tailwind for us. Why? As a result of we\u2019re already primarily based within the area, and plenty of of those new amenities are beginning contemporary \u2014 with out legacy methods weighing them down. That makes them way more open to AI-native approaches like ours from day one,\u201d Agarwal instructed TechCrunch. <\/p>\n<\/div>\n